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Jump directly to the FAQ category most relevant to you. We have organized over 60 frequently asked questions into clear.

General

Who we are, our mission, hub-and-spoke architecture, milestone billing, and what sets Pixel Tech™ apart from every other enterprise vendor.

Getting Started

First steps, discovery process, proof-of-concept engagements, onboarding timelines, and what to expect when you begin working with Pixel Tech™.

Products

Deep-dive into individual Pixel Ecosystem products, their AI features, standalone vs. integrated modes, and how 65+ products work together.

AI & Automation

Our AI-native architecture, predictive capabilities, computer vision, RAG chatbots, custom model training, and responsible AI governance.

Ecosystem Integration

How hub-and-spoke connects every product, data flows between suites, API access, and building a unified enterprise data layer.

Security & Compliance

Certifications, encryption standards, data residency, GDPR and CCPA compliance, audit trails, and AI-powered threat monitoring.

Pricing & Implementation

Milestone-based billing, subscription plans, ROI timelines, training, support tiers, and ongoing managed services options.

Industry-Specific

Tailored answers for manufacturing, natural stone, textiles, exhibitions, distribution, retail, healthcare, and professional services.

General

About Pixel Tech™

Answers to the most common questions about who we are, what we do, and how we are different from other enterprise.

Pixel Tech™ is an AI-first enterprise technology company that builds and implements a comprehensive ecosystem of 65+ integrated products. Our solutions span ERP, CRM, inventory management, RFID tracking, chatbots, voice automation, AR/VR, and more — all powered by native AI. Founded by industry veterans with 25+ years of combined experience at Bank of America, Merrill Lynch, Fidelity, and Accenture, we serve 10+ industries with a unique milestone-based delivery model. Our growth is majority referral-driven, meaning every client comes through recommendations from satisfied customers.

We serve 10+ industries including manufacturing, natural stone, textiles, distribution, retail, exhibitions & events, professional services, healthcare, and more. Each industry has tailored AI solutions that address specific operational challenges, from RFID inventory for stone yards to predictive maintenance for manufacturing plants.

Four key differentiators: (1) AI-native architecture where intelligence is built into every product from day one, not bolted on as an afterthought, (2) 65+ integrated products in a hub-and-spoke ecosystem that eliminates data silos, (3) Founder-led with 25+ years of Wall Street and Fortune 500 experience directly engaged in every strategic engagement, (4) Milestone-based billing where you pay only when deliverables are approved. Our majority referral-driven growth proves clients love what we build.

Aman Jain (CEO & Chief Architect) brings 25+ years of enterprise technology leadership at Bank of America, Merrill Lynch, and Fidelity Investments where he built systems processing hundreds of billions in daily transactions. Garima Jain (CTO) brings 16+ years of technology consulting and implementation experience at Accenture delivering complex transformations for Fortune 500 clients across multiple continents. Together, they bring unmatched depth in building mission-critical enterprise systems at global scale.

The Pixel Ecosystem is our comprehensive platform of 65+ AI-powered enterprise products organized into four suites: Core Enterprise (ERP, Accounts, Inventory, Projects, Service), Commerce & Growth (Cart, Trade Portal, Catering), Engagement & Automation (Engage, BOTs, Voice, Reality), and Industry Specialized (RFID, Exhibitions, PMC). All products share a common AI engine and connect through our hub-and-spoke architecture.

Our “Pay on Milestones Met” model divides every project into clear, measurable milestones with defined deliverables and acceptance criteria. You only pay when a milestone is completed and formally approved by you. This ensures complete alignment between project progress and payment, giving you full control over your investment and eliminating the risk of paying for unfinished or unsatisfactory work. If a milestone does not meet your requirements, you do not pay until it does.

Every single client we have today came through referrals from existing satisfied clients. We do not employ sales teams, run cold outreach campaigns, or use aggressive sales tactics. This organic growth model is the strongest possible proof of client satisfaction — our clients love our solutions enough to stake their professional reputation by recommending us to their peers and business networks.

Our hub-and-spoke architecture is a design pattern where a central AI hub connects all products (spokes) through standardized interfaces. The hub provides shared services: authentication, AI/ML engine, data model, event bus, and analytics. Each spoke (product) operates independently but seamlessly shares data and intelligence through the hub, eliminating data silos and enabling cross-product AI insights that would be impossible with disconnected point solutions.

Yes! We offer personalized demos tailored to your industry and specific requirements. Our solutions architects will walk you through relevant products, demonstrate real AI capabilities in action with your industry's data patterns, and discuss how the Pixel Ecosystem addresses your specific business challenges. Book a demo today and see AI-native enterprise technology in action.

Pixel Tech™ is headquartered in India with a global client base spanning Asia-Pacific, Middle East, and North America. Our cloud-based platform serves clients worldwide with data residency options in multiple regions for regulatory compliance. Real clients include our client, our client, our client, our client, and Trellis HK across manufacturing, natural stone, textiles, and exhibition industries.

Getting Started

Getting Started Questions

Everything you need to know about beginning your journey with Pixel Tech™. From the first discovery call to going live.

Our discovery process is thorough and founder-led. It begins with a complimentary consultation where Aman Jain (CEO) or Garima Jain (CTO) personally assess your operational challenges, current technology landscape, business goals, and growth plans. This is followed by a detailed requirements mapping workshop where we document workflows, pain points, integration needs, and success metrics. The output is a tailored proposal with recommended Pixel Ecosystem products, a phased implementation roadmap, clear milestones with acceptance criteria, and a transparent cost breakdown. The entire discovery phase typically takes 1-2 weeks and carries no obligation.

Single-product deployments typically go live in 4-8 weeks. However, many clients see working functionality much sooner. Our agile, milestone-based approach delivers features incrementally, so you can start using core capabilities while advanced features are still being configured. For example, basic ERP financial modules can be operational in 3 weeks while AI-powered forecasting models are being trained on your historical data. The key advantage of our approach is that you are never waiting months to see value — you see progress at every milestone.

That is exactly what the discovery consultation is for. Unlike vendors who push their entire portfolio, we recommend only the products that address your specific challenges. Our founders have 25+ years of combined enterprise experience and can quickly identify the highest-impact starting points for your business. Many clients are surprised that we recommend starting with fewer products than they expected — because our focus is on delivering measurable value, not maximizing initial deal size. You can always expand later through the modular Pixel Ecosystem.

Yes. For enterprises evaluating multiple vendors, we offer structured proof-of-concept (POC) engagements. A typical POC runs 2-4 weeks and demonstrates our platform working with a subset of your actual data and workflows. POCs are milestone-based — you agree on specific success criteria upfront and pay only if those criteria are met. This gives you hands-on evidence of AI capabilities, integration feasibility, and user experience quality before committing to a full implementation.

We guide you through this with a structured onboarding checklist. Typical requirements include: current workflow documentation or process descriptions, sample data exports from existing systems, user role definitions and permission requirements, integration endpoint details for connected systems, and business rules or compliance requirements. Our team works with your staff to gather and validate this information — we do not expect you to produce extensive documentation on your own. The goal is to get your knowledge into our platform with minimal disruption to daily operations.

We design implementations to minimize disruption to your operations. Your team's involvement typically includes: a project sponsor (1-2 hours/week for decisions), subject matter experts (2-4 hours/week during discovery and validation phases), IT contact for infrastructure and integration coordination, and end-user champions for feedback during UAT testing. Our team handles the heavy lifting of configuration, data migration, customization, and training preparation. Most clients tell us we require significantly less of their time than previous enterprise implementations because our founders know the right questions to ask upfront.

Yes, and we strongly recommend it for mission-critical processes. Parallel running is a standard phase in our implementation methodology. During this period, your team operates both old and new systems simultaneously to validate data accuracy, verify workflow completeness, and build confidence before cutover. Our AI engine can even compare outputs between systems automatically, flagging discrepancies for human review. Parallel periods typically last 2-4 weeks depending on process complexity. The milestone for final cutover is only approved when you are fully confident in the new system.

Go-live is carefully orchestrated with a detailed runbook. Our team provides dedicated go-live support with senior engineers on standby for immediate issue resolution. A war room is established for the first 48 hours with real-time monitoring dashboards. Key activities include final data sync from legacy systems, user access verification, critical workflow validation, and performance monitoring. Post-go-live, we provide intensive hypercare support for 2-4 weeks with dedicated resources. Our AI monitoring proactively detects anomalies before users encounter them, ensuring a smooth transition.

Hypercare is the intensive post-go-live support period where our team provides elevated service levels. During hypercare (typically 2-4 weeks after go-live), you receive extended support hours, faster response times, a dedicated support engineer assigned to your account, daily check-in calls, proactive monitoring with immediate intervention, and rapid hotfix deployment for any issues. This ensures that any edge cases or unexpected scenarios are addressed immediately rather than through normal support channels. Hypercare transitions smoothly into your ongoing support plan with a formal handover process.

Change management is integrated into every implementation, not treated as an afterthought. Our approach includes: stakeholder mapping to identify champions and resistors early, role-specific training programs that show users how the new system improves their daily work, regular communication cadences that keep the organization informed of progress, feedback loops during each milestone where users can influence the solution, and quick-win identification to build momentum and demonstrate value early. Our AI-powered training platform also provides in-context help and guided walkthroughs that reduce the learning curve significantly.

Products

Product Questions

Detailed answers about individual products in the Pixel Ecosystem, their capabilities, AI features, and how they work.

You can absolutely start with individual products. Many clients begin with Pixel ERP™ or Pixel Inventory and add more products as they see value. The ecosystem is modular — each product works standalone but becomes exponentially more powerful when connected with others through our hub-and-spoke architecture, enabling cross-product AI insights.

Every product includes AI capabilities natively: predictive analytics, anomaly detection, intelligent recommendations, NLP-powered search, automated workflows, and more. We use proprietary AI models for language intelligence, open-source AI models for specialized ML tasks, and dedicated GPU infrastructure for AI image generation and LTX-2 workloads. This is not a bolt-on AI layer — intelligence is built into the core data models, business logic, and user interfaces from day one.

Pixel ERP™ is our AI-powered enterprise resource planning platform covering financial management, procurement, manufacturing operations, project accounting, and business intelligence. It features AI-driven financial forecasting with 94% accuracy, automated reconciliation, intelligent purchase recommendations, real-time analytics dashboards, and seamless integration with all other Pixel Ecosystem products.

Pixel IoT supports UHF, HF, and NFC readers from major manufacturers. We offer our own branded readers and tags optimized for our platform, plus compatibility with third-party hardware. Solutions include handheld readers for mobile scanning, fixed portal readers for automated tracking, and desktop encoders for tag programming. View RFID hardware →

Pixel Engage™ (Bots) is our conversational AI platform using LLMs with RAG (Retrieval-Augmented Generation) architecture. It integrates with your ERP, CRM, and knowledge base to provide contextual, accurate responses — not scripted chatbot answers. Deploy across web, mobile, WhatsApp, and messaging platforms for customer support, internal helpdesk, sales assistance, and automated workflows.

Yes, Pixel Cart™ supports both B2C and B2B e-commerce with features like customer-specific pricing tiers, bulk ordering with quantity discounts, RFQ and quote management, credit terms with approval workflows, multi-warehouse fulfillment, and AI-powered product recommendations. Fully integrated with Pixel ERP™ for seamless order-to-fulfillment automation.

Pixel Exhibitions is our AI-powered trade show and event management platform covering the complete exhibition lifecycle: booth allocation with AI floor plan optimization, exhibitor management, visitor registration, RFID badge scanning for real-time attendance tracking, AI-powered lead scoring, and comprehensive post-event analytics and ROI reporting.

Pixel Reality is our AR/VR platform for product visualization, virtual showrooms, training simulations, and remote assistance. Clients use it for visualizing natural stone slabs in customer spaces (reducing returns by 35%), virtual factory tours, equipment maintenance training, and immersive product catalogs that drive higher engagement and conversion rates.

Pixel Voice is our AI-powered voice automation platform for customer service IVR systems, voice search, and hands-free enterprise operations. It uses advanced speech-to-text and text-to-speech with natural language understanding to handle complex business interactions, routing, and data lookups without requiring callers to navigate menu trees.

Pixel Trade Portal is a B2B platform connecting manufacturers, distributors, and retailers with AI-powered demand matching, catalog management, order workflows, pricing negotiations, shipping coordination, and credit management. Ideal for natural stone, textiles, and manufacturing where complex multi-party B2B transactions are the norm.

Integration

Ecosystem Integration Questions

One of the biggest advantages of the Pixel Ecosystem is that every product connects seamlessly through our AI-powered.

All Pixel Ecosystem products share data through the central hub layer in our hub-and-spoke architecture. The hub provides a unified data model where information from every product is normalized, indexed, and made available for cross-product queries. When a sales order is created in Pixel Cart™, the inventory is automatically reserved in Pixel Inventory, the financial projection updates in Pixel Accounts, and the AI engine recalculates demand forecasts across the board — all in real time without any manual data entry or batch synchronization.

Absolutely. Every Pixel product exposes a comprehensive REST API with full CRUD operations, pagination, filtering, and webhook support. We provide pre-built connectors for popular business platforms including accounting software, payment gateways, messaging services, CRM platforms, and e-commerce marketplaces. For custom integrations, our system integration team builds bespoke connectors using our middleware layer that handles data transformation, error handling, retry logic, and audit logging. The goal is to make Pixel products a seamless part of your existing technology landscape while you transition at your own pace.

The event bus is the real-time communication backbone of the Pixel Ecosystem. Every action in any product publishes an event (e.g., “OrderCreated”, “InventoryLow”, “InvoicePaid”) to the central event bus. Other products subscribe to relevant events and react accordingly. This real-time architecture enables real-time automation: when Pixel IoT detects a low stock level, the event bus notifies Pixel ERP™ to generate a purchase order, Pixel Engage™ (Bots) to alert the procurement team, and the AI engine to update demand forecasts. Events are guaranteed delivery, ordered, and fully auditable.

Cross-product AI intelligence is the most powerful advantage of an integrated ecosystem over point solutions. Because all data flows through the central AI hub, our models can identify patterns that span multiple business domains. For example, the AI engine can correlate sales trends from Pixel Cart™, inventory levels from Pixel Inventory, production schedules from Pixel ERP™, and supplier lead times from Pixel Trade Portal to generate highly accurate demand forecasts. A standalone inventory system can only see stock levels — our ecosystem AI sees the complete picture and makes smarter decisions as a result.

When you add a new product to your Pixel Ecosystem instance, it automatically connects to the central hub and gains access to relevant shared data. Historical data from your existing products enriches the new product's AI models from day one. For example, if you add Pixel Accounts after using Pixel ERP™ for a year, the accounting module immediately benefits from a year of transaction history, vendor patterns, and financial trends already in the data model. There is no separate data migration or integration project — new products simply plug into the existing hub.

Data consistency is maintained through the hub layer using eventual consistency patterns with strong consistency for critical operations. Master data (customers, products, vendors) is managed centrally and propagated to all products. Transactional data uses saga patterns for multi-product operations — if any step fails, compensating transactions roll back the entire operation. An AI-powered reconciliation engine continuously validates data consistency across products and automatically resolves discrepancies or flags them for human review when needed.

Yes. The beauty of the hub-and-spoke model is that each product (spoke) operates independently with its own user interface, permissions, and workflows. Your finance team uses Pixel Accounts, your warehouse team uses Pixel Inventory, your sales team uses Pixel Cart™ — each with role-specific views and capabilities. But behind the scenes, the hub ensures all data is synchronized and the AI engine has a 360-degree view of your operations. Departments benefit from seamless cross-functional data without needing to learn or interact with products outside their domain.

Every Pixel product provides REST APIs with comprehensive endpoint coverage. API capabilities include: CRUD operations for all entities, advanced filtering and pagination, real-time webhooks for event notification, bulk operations for data import/export, file upload and management, reporting and analytics endpoints, and AI model inference endpoints for custom applications. API documentation is auto-generated, interactive, and includes code examples in multiple languages. Developer sandbox environments are available for testing. Rate limits are generous and configurable for enterprise clients.

Cross-product automation is built on the event bus and workflow engine in the hub layer. You can create workflows that trigger actions across multiple products: a customer inquiry in Pixel Engage™ (Bots) can create a lead in Pixel Engage™, schedule a follow-up in the calendar, and notify the sales team. A production completion event in Pixel ERP™ can trigger quality inspection in the mobile app, update inventory counts in Pixel Inventory, generate shipping documents, and notify the customer through Pixel Engage™. Workflows are configured through a visual builder with drag-and-drop logic — no coding required for standard automations.

Yes. The Pixel Ecosystem includes a unified executive dashboard that aggregates KPIs, alerts, and analytics from all active products. Dashboards are role-based — a CEO sees company-wide financial and operational metrics, a warehouse manager sees inventory and fulfillment KPIs, and a sales director sees pipeline and revenue data. The AI engine powers smart widgets that surface insights, anomalies, and recommendations based on cross-product data analysis. Dashboards are fully customizable with drag-and-drop widgets, configurable alerts, and scheduled report delivery via email.

AI & Automation

AI & Automation Questions

AI is the hero of every Pixel Tech™ product. These questions cover our AI capabilities, technology stack, and how.

Our AI stack includes proprietary AI models for large language model capabilities, open-source AI for specialized ML models, and dedicated GPU infrastructure for compute-intensive tasks like AI image generation image generation and LTX-2 video processing. We use deep learning framework for custom model training, AI orchestration framework for RAG pipelines, and a proprietary feature store for production ML serving across all ecosystem products.

AI-native means intelligence is built into the core architecture from the beginning — data models, business logic, user interfaces, and workflows are all designed around AI capabilities. Bolt-on AI adds ML features on top of existing legacy architecture, resulting in disconnected AI that cannot access full context. Our hub-and-spoke architecture ensures every product shares data through the central AI engine, enabling insights that bolt-on approaches simply cannot achieve.

Accuracy depends on the specific model and data quality. Our financial forecasting achieves 94% accuracy on cash flow predictions. Demand forecasting typically reaches 85-90% accuracy after initial training. Anomaly detection achieves 97%+ precision in production environments. RFID read accuracy with ML error correction exceeds 99.5%. All models improve over time as they learn from your specific business data patterns.

Yes, extensively. AI models are trained on your specific business data to optimize accuracy for your context. Custom prediction models, industry-specific classification rules, personalized recommendation engines, and tailored automation workflows are all configurable through admin interfaces or via our AI automation services. Our team helps fine-tune models during implementation.

We implement a comprehensive AI governance framework including bias detection in training data, model validation with fairness metrics, explainability tools for model decisions, human-in-the-loop review for critical decisions, and regular model audits. Our approach follows responsible AI principles aligned with GDPR, CCPA, and emerging AI regulations. Read our whitepaper on AI governance for details.

Our platform includes: financial forecasting (cash flow, revenue, cost predictions), demand forecasting (inventory optimization, production planning), predictive maintenance (equipment failure prediction from sensor data), lead scoring (sales opportunity ranking), churn prediction (customer retention alerts), quality prediction (defect probability scoring), and anomaly detection across all operational data streams.

Yes. Computer vision is used for quality inspection in manufacturing (detecting defects on production lines), document processing (OCR with intelligent data extraction), product recognition for inventory, natural stone slab classification and matching, and AR product visualization through Pixel Reality. AI image generation on dedicated GPU cloud powers our image generation capabilities for product catalogs and marketing.

RAG (Retrieval-Augmented Generation) in Pixel Engage™ (Bots) works by: (1) Indexing your ERP data, knowledge base, support history, and documentation into a vector database, (2) When a user asks a question, relevant context is retrieved from the vector store, (3) The LLM generates a response using both the retrieved context and its language capabilities, (4) Response is validated against source data for accuracy. This ensures accurate, contextual answers grounded in your actual business data.

Yes. Our platform supports custom model training through: (1) AutoML pipelines for common prediction tasks requiring minimal ML expertise, (2) Custom model training using deep learning framework with our managed training infrastructure, (3) Fine-tuning pre-trained models on your domain-specific data, (4) A/B testing framework for comparing model performance in production. Our AI automation team provides hands-on support for complex custom models.

The central AI engine sits in the hub of our architecture and provides shared intelligence services to all product spokes: unified data model for cross-product ML training, shared feature store for consistent ML features, model serving infrastructure for real-time predictions, real-time trigger system for automated AI actions, and a feedback loop that continuously improves models based on user interactions across all products.

Technical

Technical Questions

Detailed technical information about our platform architecture, technology stack, security, compliance.

Backend: enterprise backend framework for API services. Database: scalable cloud database for cloud database data, with managed relational storage where needed. Cloud: AWS infrastructure with global CDN CDN. Mobile: cross-platform mobile framework for cross-platform mobile apps. Frontend: lightweight reactive framework and utility-first CSS framework for responsive web interfaces. AI/ML: proprietary AI models, open-source AI, dedicated GPU cloud GPU (AI image generation/LTX-2), deep learning framework, AI orchestration framework. Monitoring: CloudWatch, Datadog integration.

We offer flexible deployment options: cloud-hosted (AWS primary, Azure and GCP available), on-premise, and hybrid. Cloud-hosted is the most popular option with 99.9% uptime SLA and managed infrastructure. On-premise deployment is available for organizations with strict data sovereignty requirements. Hybrid models let you keep sensitive data on-premise while using cloud for compute-intensive AI workloads.

SOC 2 Type II audited, ISO 27001 certified, GDPR compliant, CCPA compliant. Security includes AES-256 encryption at rest, TLS 1.3 in transit, RBAC with MFA enforcement, comprehensive audit logging, intrusion detection systems, AI-powered security monitoring, and regular penetration testing by independent third-party security firms. Full security documentation is available on request.

Yes. Our platform offers REST APIs with 100% endpoint coverage, webhooks for real-time integration, pre-built connectors for popular platforms, and custom integration capabilities. We have proven integrations with SAP, Oracle, Salesforce, Tally, QuickBooks, Shopify, WooCommerce, Razorpay, Stripe, WhatsApp, Slack, and Microsoft Teams. Our integration services team builds custom connectors for unique requirements.

Our structured migration process: (1) Data assessment and gap analysis, (2) Schema mapping and transformation rules, (3) Automated validation scripts with quality checks, (4) Test migration with full data verification, (5) Parallel running period for comparison, (6) Final cutover with documented rollback plan. Our team handles the complexity so you experience a smooth transition with zero data loss. See our migration documentation for details.

99.9% uptime SLA for cloud-hosted services, measured monthly. Service credits if we fall below: 10% credit for 99-99.9%, 25% for 95-99%, 50% for below 95%. Scheduled maintenance is excluded and always communicated 48+ hours in advance during off-peak hours. Enterprise plans can negotiate 99.95% or higher SLAs with dedicated infrastructure.

Our platform auto-scales based on demand using container orchestration. scalable cloud database provides automatic throughput scaling for database operations. CDN distribution handles traffic spikes for static content. Read replicas and caching layers handle concurrent read-heavy workloads. We have successfully scaled for clients processing millions of RFID reads per day and thousands of concurrent users.

Multi-region deployment with automated failover, daily backups with point-in-time recovery, and documented DR procedures tested quarterly. Standard plan: RPO 1 hour, RTO 4 hours. Enterprise plan: near-zero RPO with real-time cross-region replication, RTO under 30 minutes. All DR procedures are documented and tested regularly with results shared in quarterly business reviews.

Yes. All web interfaces are responsive for mobile browsers. We offer native mobile apps built with cross-platform mobile framework for specific use cases: RFID scanning, field service management, sales force automation, warehouse operations, and exhibition check-in. Offline-first architecture ensures functionality in low-connectivity environments like warehouses and remote stone quarries.

Extensive customization through: configurable workflows with visual builders, custom fields and forms, business rule engines with conditional logic, report builders with drag-and-drop design, dashboard designers, API-driven extensions, webhook-triggered automations, and custom module development. Our consulting team can build bespoke features specific to your unique business requirements.

Security & Compliance

Security & Compliance Questions

Enterprise-grade security is non-negotiable. Learn about our comprehensive security posture, compliance certifications,.

We implement encryption at every layer. Data at rest is encrypted using AES-256, the same standard used by financial institutions and government agencies. Data in transit uses TLS 1.3 for all API communications, webhooks, and user interfaces. Database-level encryption ensures that even if storage media were physically accessed, data would be unreadable. Encryption keys are managed through a dedicated key management service with automatic key rotation. For clients with specific key management requirements, we support customer-managed encryption keys (CMEK) where you retain full control of encryption key lifecycle.

Our platform and operations are SOC 2 Type II audited (covering security, availability, processing integrity, confidentiality, and privacy), ISO 27001 certified for information security management, GDPR compliant for European data protection, and CCPA compliant for California consumer privacy requirements. We conduct annual third-party audits and share audit reports with enterprise clients under NDA. Our infrastructure providers maintain additional certifications including PCI DSS, HIPAA, and FedRAMP that our platform inherits. Industry-specific compliance requirements are addressed during the implementation phase.

We offer data residency options across multiple global regions including Asia-Pacific, Europe, North America, and Middle East. You choose where your data is stored during onboarding, and that choice is enforced at the infrastructure level — your data never leaves the specified region unless you explicitly configure cross-region replication for disaster recovery. For organizations with strict data sovereignty requirements, we offer on-premise deployment where data never leaves your own data center. Hybrid models allow certain data classes to remain on-premise while leveraging cloud compute for AI workloads.

Role-based access control (RBAC) is enforced across all Pixel Ecosystem products. Administrators define roles with granular permissions controlling access at the feature, record, and field level. Authentication supports multi-factor authentication (MFA) with TOTP authenticator apps, SSO integration with popular identity providers, IP whitelisting for sensitive operations, session management with configurable timeouts, and device trust verification. Password policies are configurable to match your organization's security standards. All authentication events are logged in the immutable audit trail for compliance and forensics.

Comprehensive audit logging captures every user action, data change, system event, and API call across the entire Pixel Ecosystem. Audit logs are immutable, tamper-evident, and retained for configurable periods (default 7 years for compliance). Real-time monitoring dashboards show system health, security events, and performance metrics. AI-powered anomaly detection monitors user behavior patterns and alerts on suspicious activity such as unusual access times, bulk data exports, or privilege escalation attempts. Automated compliance reports can be generated on demand for internal audits, regulatory examinations, or client due diligence reviews.

AI model security is a core focus area. Client training data is isolated at the infrastructure level — your data is never used to train models for other clients. Models are versioned and access-controlled so only authorized users and systems can invoke them. Training pipelines run in isolated compute environments with no internet access. Model outputs are validated against business rules before being acted upon. We implement differential privacy techniques where applicable to prevent model inversion attacks. Our AI governance framework includes bias testing, fairness metrics, and regular audits to ensure models remain ethical and accurate.

We conduct independent third-party penetration testing quarterly, covering network infrastructure, application layer, API security, and social engineering vectors. Continuous automated vulnerability scanning runs daily across all production environments. A responsible disclosure program allows security researchers to report vulnerabilities. Critical findings are remediated within 24 hours, high severity within 72 hours. Penetration test summary reports are available to enterprise clients under NDA. We also perform internal security assessments before every major release and maintain a bug bounty program for ongoing community security testing.

Your data is your data — always. If you choose to leave, we provide a complete data export in standard formats (CSV, JSON, XML) with full schema documentation. The export includes all transactional data, master data, documents, reports, audit logs, and AI model configurations. We provide a 90-day transition period after contract termination for data extraction and verification. After the transition period and your written confirmation, all your data is securely deleted from our systems including backups, with a certificate of destruction issued. There are no data hostage scenarios — we earn your business every day through value, not lock-in.

We maintain a documented incident response plan tested quarterly through tabletop exercises and live drills. The plan covers detection (AI-powered monitoring and alerting), containment (automated isolation of affected systems), eradication (root cause analysis and remediation), recovery (service restoration and verification), and post-incident review (lessons learned and process improvement). Clients are notified of security incidents affecting their data within 24 hours via designated contacts. Detailed incident reports including timeline, impact assessment, and remediation actions are provided for all significant events. Our founder-led approach means Aman or Garima personally oversee response for critical incidents.

Yes. Beyond our baseline certifications, we support industry-specific compliance requirements during implementation. For healthcare clients, we implement additional controls aligned with health data protection standards. For financial services, we support regulatory reporting requirements and trade surveillance. For manufacturing, we support quality management system standards and material traceability. For clients operating in the EU, we ensure full GDPR compliance including data processing agreements, privacy impact assessments, and data protection officer support. Compliance requirements are documented during discovery and validated as part of milestone acceptance criteria.

Pricing & Implementation

Pricing & Implementation FAQ

Everything you need to know about pricing models, implementation timelines, ongoing support, training, and the return.

Pricing depends on products selected, number of users, deployment model, and support tier. SaaS products are available on monthly or annual subscriptions with volume discounts. Custom development follows our milestone-based billing model where you pay only on approved deliverables. No hidden fees, no per-transaction charges, no surprise costs. Contact our team for a personalized quote.

Timelines vary by scope: single product deployments typically take 4-8 weeks, multi-product implementations 8-16 weeks, and full ecosystem rollouts 3-6 months. Our agile, milestone-based approach means you see working software early and can start using features as they are completed. Phased rollouts reduce risk and allow for user feedback integration during implementation.

We offer personalized demos and proof-of-concept engagements rather than generic free trials. This approach ensures you see how our solutions address your specific business challenges with your actual data scenarios and industry context. Free sandbox environments are available for developers to test API integrations. Book a demo to get started.

All plans include standard support (business hours email/ticketing, Pixel Engage™ (Bots) AI assistant 24/7). Premium plans add extended hours, phone support, and quarterly business reviews. Enterprise plans include dedicated account managers, on-site support, custom SLAs, and 24/7 human support. Our managed services option handles full platform management.

Comprehensive training is included in every implementation: admin training for system configuration, end-user training for daily operations, train-the-trainer sessions for internal knowledge transfer, and ongoing learning resources including documentation, video tutorials, and webinars. Training is tailored to each user role and skill level, delivered both online and on-site.

Absolutely. Most clients start with 1-2 products addressing their most critical needs, then expand as they see results. Our modular ecosystem makes it easy to add products incrementally. Each new product integrates seamlessly with existing ones through the hub-and-spoke architecture, and previous configurations are preserved during expansion.

Yes. Our managed services team handles ongoing platform management, monitoring, updates, security patches, performance optimization, and proactive issue resolution. This allows your team to focus on business operations while we ensure the technology runs smoothly, securely, and at peak performance. SLAs cover response times, resolution times, and uptime guarantees.

If a milestone does not meet the agreed acceptance criteria, you do not pay for it. We continue working until the deliverable meets your requirements at no additional cost. This model protects your investment and ensures quality. Clear communication, regular demos during development, and formal acceptance criteria defined upfront minimize any misalignment.

Yes, we collaborate closely with client IT teams. Our engagement models include: (1) Full implementation where we handle everything, (2) Joint delivery where we work alongside your team with knowledge transfer, (3) Enablement where we train your team to manage the platform independently. Knowledge transfer is a core part of every engagement to build internal capability.

Most clients see measurable ROI within 3-6 months of deployment. AI-driven efficiency gains, reduced manual work, improved accuracy, and better decision-making contribute to rapid payback. Specific results from our clients: 40% efficiency improvement in manufacturing operations, 95% reduction in inventory counting time with RFID, 60% reduction in predictive maintenance downtime, and 35% reduction in product returns with AR visualization.

Comparison

Pixel Tech™ vs Alternatives

How we compare to traditional enterprise software approaches on the factors that matter most to your business.

Factor	Pixel Tech™	SAP / Oracle	Niche SaaS Tools
AI Integration	Native in every product, central engine	Bolt-on modules, extra licensing	Limited or basic automation
Product Range	65+ integrated products, 4 suites	10-20 modules, add-on marketplace	1-3 products per vendor
Implementation Timeline	4-16 weeks, milestone-based	12-24 months typical	Fast but limited scope
Pricing Model	Pay on milestones met	Upfront licenses + hourly services	Per-user subscription
Founder Access	Direct engagement, 25+ years experience	Corporate account managers	Support tickets
Data Integration	Hub-and-spoke, zero silos	Module-level, integration needed	APIs required, silos common
Industry Depth	15+ verticals with domain expertise	Horizontal, requires customization	1-2 verticals maximum
Growth Model	majority referral, client satisfaction driven	Enterprise sales teams	Marketing and sales driven

Explore Products

Pixel Ecosystem Products

Pixel ERP™

AI-powered enterprise resource planning with financial forecasting, procurement automation, and manufacturing operations management.

Pixel IoT

AI-enhanced RFID tracking with ML error correction, real-time analytics, and hardware integration for manufacturing and stone industries.

Pixel Engage™ (Bots)

LLM-powered conversational AI with RAG architecture integrating with ERP and CRM for contextual enterprise chatbot experiences.

Pixel Cart™

AI-powered e-commerce platform with personalized recommendations, dynamic pricing, and B2B/B2C capabilities.

Pixel Exhibitions

Smart event management with booth allocation, RFID badges, AI lead scoring, and comprehensive event analytics.

Pixel Reality

AR/VR platform for product visualization, virtual showrooms, training simulations, and immersive customer experiences.

Industry-Specific

Industry-Specific Questions

Pixel Tech™ serves 10+ industries with AI-powered solutions tailored to each sector's unique challenges. Here are.

For manufacturing, our AI solutions include predictive maintenance that forecasts equipment failures from sensor data before they cause downtime, quality inspection using computer vision to detect defects on production lines in real time, production scheduling optimization that balances capacity, materials, and deadlines, demand forecasting that adjusts production plans based on market signals, energy consumption optimization, and automated compliance reporting. Clients like our client and our client have achieved 40%+ efficiency improvements and significantly reduced unplanned downtime through our AI-powered manufacturing operations suite.

Natural stone inventory management is one of our strongest specializations. Each slab or block is tagged with a durable RFID tag that withstands harsh outdoor and warehouse conditions. Pixel IoT with ML error correction provides 99.5%+ read accuracy even in challenging stone yard environments with metal interference. The system tracks every slab from quarry to customer delivery — capturing dimensions, grade, color patterns, location coordinates, and chain-of-custody history. AI-powered image classification automatically categorizes stone by visual characteristics. Clients like our client have reduced physical counting time by 95% and virtually eliminated inventory discrepancies.

Our textiles solutions cover the entire value chain from fiber to finished garment. AI capabilities include fabric defect detection using computer vision, color matching and consistency monitoring, RFID-based roll and bundle tracking, production planning optimization across dyeing, weaving, and finishing stages, demand forecasting for seasonal fashion cycles, and supply chain visibility from raw material sourcing to retail delivery. The Pixel Trade Portal connects textile manufacturers with buyers globally with AI-powered matching based on specifications, capacity, and delivery capabilities. our client has transformed their textile operations with our full-stack AI solution.

Pixel Exhibitions manages the entire trade show lifecycle with AI at every stage. Features include AI-powered floor plan optimization that maximizes exhibitor satisfaction and visitor flow, RFID badge scanning for real-time attendance and engagement tracking, AI lead scoring that identifies the most promising connections for each exhibitor, automated scheduling for meetings and presentations, real-time crowd density monitoring, and comprehensive post-event analytics with ROI measurement. The platform supports multi-venue, multi-day events with thousands of exhibitors and tens of thousands of visitors. See our exhibitions case study for detailed results.

Distribution companies benefit from AI-powered route optimization, warehouse management with RFID-based picking accuracy improvement, demand forecasting for inventory positioning across multiple warehouses, automated reorder point calculation, dynamic pricing based on market conditions and inventory levels, and real-time shipment tracking with predictive ETA. The hub-and-spoke architecture connects order management, inventory, logistics, and customer communication seamlessly. Our AI reduces distribution costs by optimizing routes, minimizing stockouts, and improving warehouse labor productivity.

Yes. Our healthcare solutions focus on operational efficiency while maintaining strict compliance with health data protection regulations. AI capabilities include appointment scheduling optimization, patient flow management with predictive wait times, medical equipment tracking via RFID, inventory management for pharmaceuticals and supplies with expiry tracking, automated billing and insurance claim processing, and clinical decision support tools. All healthcare deployments include additional security controls, audit mechanisms, and data handling procedures aligned with healthcare industry standards.

Professional services firms use our platform for project management with AI-powered resource allocation, time tracking and billing automation, client relationship management, proposal generation with AI-assisted content, knowledge management with intelligent search across project archives, and financial management including project profitability analysis. Pixel Projects provides Gantt charts, resource heatmaps, milestone tracking, and predictive project health scoring that alerts managers to potential delays before they impact deadlines or budgets.

Retail clients use our platform for multi-location inventory visibility with AI-powered stock transfer recommendations, point-of-sale integration, customer loyalty programs with personalized AI-driven offers, demand forecasting at the store and SKU level, planogram optimization using computer vision, workforce scheduling based on predicted foot traffic, and unified e-commerce plus physical store operations through Pixel Cart™. RFID-enabled stores achieve near-perfect inventory accuracy and can offer buy-online-pickup-in-store experiences with real-time stock visibility.

Yes. Each industry vertical includes AI-powered compliance and reporting modules tailored to sector-specific regulations. Manufacturing clients get automated quality management reporting, environmental compliance tracking, and safety incident documentation. Healthcare deployments include regulatory audit trail reports and data governance dashboards. Financial services implementations include transaction monitoring and regulatory filing automation. Our AI engine identifies potential compliance gaps proactively and generates pre-formatted reports for regulatory submissions, reducing compliance team workload significantly.

Our platform is configurable to use industry-specific terminology, units of measure, workflow patterns, and document formats. Manufacturing clients see “work orders” and “bill of materials”, stone companies see “slabs” and “blocks”, textile firms see “rolls” and “lots”, exhibition companies see “booths” and “exhibitors”. This is not just cosmetic renaming — the underlying data models, validation rules, and AI models are all tuned for industry-specific patterns. Our founders' experience across multiple verticals means we understand the nuances of each industry deeply, which is reflected in our product design.

Leadership

Ask Questions Directly to Our Founders

Unlike most enterprise technology companies where you interact with sales reps and support agents, Pixel Tech™ is founder-led.

When you book a demo, you are not getting a junior sales person reading from a script. You are meeting with the people.

This founder-led engagement is why every client comes through referrals, why our milestone-based billing works, and why.

Talk to Our Founders

Aman Jain

CEO & Chief Architect

25+ years building mission-critical systems at Bank of America, Merrill Lynch, and Fidelity that processed hundreds of billions.

Garima Jain

CTO

16+ years at Accenture delivering enterprise transformations for Fortune 500 clients across multiple continents. Garima oversees.

Partnerships & Careers

Partnership & Career Questions

Visit our partnerships page to explore program tiers (Referral, Reseller, Implementation, Technology) and apply. Our team reviews applications within 5 business days. Referral partners can start within 1 week with no minimum commitment. Contact partnerships@pixeltech.ai for direct inquiry.

Referral partners earn 10-20% on first-year revenue. Reseller partners earn 20-35% margins on product subscriptions with recurring revenue on renewals. Implementation partners earn referral fees plus their own implementation service revenue. Rates increase with performance tier advancement and quarterly bonuses reward top performers.

Yes! We are always looking for talented people who want to build AI-powered enterprise technology. Visit our careers page for current openings in engineering, AI/ML, product management, and client success. We offer remote-first work, competitive compensation, and the opportunity to work directly with our founders on cutting-edge AI products.

Yes, we offer internship programs in engineering, AI/ML research, and product development. Interns work on real products alongside our engineering team and receive mentorship from our founders. Many interns convert to full-time roles. Check our careers page for current internship opportunities and application deadlines.

Yes, through our Technology Partner program. We provide API access, developer documentation, integration support, and listing in the Pixel Ecosystem marketplace. Technology partnerships are ideal for SaaS vendors, cloud providers, payment processors, IoT hardware manufacturers, and AI/ML tool providers who want to reach our enterprise client base.

Yes, comprehensive partner training includes sales certification (product knowledge, competitive positioning, demo delivery) and technical certification (architecture, implementation, integration). Training is delivered through online courses, live workshops, and hands-on labs. Certified partners receive premium program benefits and preferential deal terms.

We are a founder-led, engineering-first organization. Our culture values: building excellent products over building political capital, honest communication over corporate speak, measurable outcomes over activity metrics, and continuous learning. We operate remote-first with flexible hours, invest heavily in AI research, and believe the best enterprise software is built by people who genuinely care about solving real problems.

Yes, consulting firms are excellent Implementation Partners. We provide full implementation methodology, technical certification for consultants, access to our engineering support team, and joint delivery models for large projects. Many consulting firms add the Pixel Ecosystem to their practice to offer AI-native enterprise solutions alongside their advisory services.

Partners receive co-branded marketing materials, case study development support, event sponsorship opportunities, and marketing development funds (MDF) for joint campaigns. Top-tier partners get dedicated marketing support including content creation, webinar co-hosting, and joint thought leadership publications.

Our hiring process: (1) Application review within 5 business days, (2) Initial technical screen or portfolio review, (3) Technical assessment or coding challenge relevant to the role, (4) Culture fit conversation with team members, (5) Final conversation with founders. The entire process typically takes 2-3 weeks. We provide feedback at every stage and respect candidates' time.

Migration

Migration & Onboarding Questions

Moving from legacy systems to AI-native enterprise technology is a significant decision. These questions address.

Yes, we have extensive experience migrating data from a wide range of enterprise systems including legacy ERP platforms, accounting software, spreadsheet-based operations, custom-built systems, and industry-specific vertical applications. Our migration framework handles data extraction from source systems, schema mapping and transformation, data cleansing and deduplication using AI, validation against business rules, and incremental synchronization during the parallel running period. The AI engine assists in identifying data quality issues, mapping inconsistent formats, and flagging potential problems before they reach production. Our migration documentation provides detailed guidance on the process.

Historical data strategy is determined during the discovery phase. Common approaches include: full historical migration where all past data is brought into the new system (ideal for trend analysis and AI model training), partial migration where a defined period (e.g., 2-3 years) of active data is migrated with older records archived for reference, and summary migration where historical data is aggregated for reporting while detailed records remain accessible in an archive. The AI engine benefits significantly from historical data for model training — the more history available, the more accurate predictions become from day one. We recommend migrating as much historical data as practical for this reason.

This is extremely common and we are well prepared for it. Our AI-powered data cleansing pipeline handles duplicate detection and merging, format standardization across inconsistent records, missing value imputation using intelligent defaults, business rule validation with exception reporting, and entity resolution to link related records across different source systems. The process is transparent — every transformation is logged and exceptions are presented to your team for review and approval. Many clients tell us the migration process alone improved their data quality significantly, providing benefits beyond the new system itself.

Zero data loss is guaranteed through a rigorous multi-step validation process. Every migration includes: automated record count reconciliation between source and target, field-level validation using checksums and business rule verification, user acceptance testing with business users verifying critical records, parallel running period where both systems operate simultaneously, and a documented rollback plan that can restore the original state within hours if needed. Test migrations are performed multiple times before the final cutover, with each iteration addressing any discrepancies found. The milestone for migration completion is only approved when your team confirms data accuracy meets acceptance criteria.

Absolutely. We strongly recommend and support parallel running where your legacy system continues operating alongside the new Pixel Ecosystem deployment. During this period, data can be synchronized between systems (either one-way or bidirectional depending on the scenario), allowing your team to validate the new system while maintaining business continuity. The transition is phased — different departments or processes can move to the new system at different times, reducing risk and allowing for targeted training and adoption support. Legacy system decommissioning happens only when you are fully confident in the new platform.

User adoption is the most critical factor in enterprise system success, and we take it seriously. Our adoption strategy includes: role-specific training programs delivered in multiple formats (live sessions, recorded videos, documentation), in-application guided walkthroughs powered by AI that help users learn while working, champion networks where enthusiastic early adopters support their colleagues, regular feedback collection and rapid iteration on user-reported pain points, adoption metrics dashboards that track feature usage by department and user, and gamification elements that encourage exploration and mastery. Pixel Engage™ (Bots) provides 24/7 in-app assistance, answering user questions using your specific system configuration and data.

Change resistance is natural and we have proven strategies to address it. Our change management approach starts early with stakeholder engagement during discovery, ensuring key influencers understand the “why” behind the transformation. We identify quick wins that demonstrate immediate value to skeptics. Training is designed to show users how the new system makes their specific daily tasks easier, not just different. The AI assistant in every product reduces the learning curve by providing contextual help. We have found that once users experience AI-powered features like intelligent search, automated data entry, and predictive recommendations, resistance typically transforms into advocacy within 2-4 weeks.

Migration timelines depend on data volume, complexity, source system accessibility, and the number of source systems. Typical ranges: single-system migration with clean data takes 2-4 weeks, multi-system consolidation with moderate complexity takes 4-8 weeks, and large-scale migrations with extensive data cleansing needs take 8-12 weeks. These timelines include multiple test migration cycles, validation, and parallel running. The migration process runs alongside other implementation activities, so it does not extend overall project timelines. Our AI-powered migration tools significantly accelerate schema mapping and data transformation compared to traditional manual approaches.

Yes. During discovery, we document all critical reports and dashboards your organization relies on. These are recreated in the Pixel Ecosystem reporting engine with equivalent or enhanced functionality. Since our platform includes AI-powered analytics, many clients find that migrated reports are significantly more insightful in the new system. We also take this opportunity to consolidate redundant reports, eliminate manual data manipulation steps, and add AI-driven anomaly detection and trend analysis that legacy reporting tools cannot provide. Custom report migration is a defined milestone with formal acceptance testing.

After migration and go-live stabilization, we offer ongoing optimization services. Quarterly business reviews analyze system usage patterns and identify opportunities for efficiency improvement. AI model retraining ensures predictions become more accurate as the system accumulates your operational data. Workflow optimization reviews identify automation opportunities that were not apparent during initial implementation. Performance tuning ensures the platform scales with your growing data volumes. Our managed services team provides proactive recommendations for new features, configuration improvements, and expansion opportunities based on your evolving business needs and the latest Pixel Ecosystem capabilities.

AI Comparison

AI Capabilities Comparison

AI is the hero of every Pixel Tech™ product. See how our native AI capabilities compare to bolt-on AI approaches offered.

AI Capability	Pixel Tech™ (AI-Native)	Traditional ERP + AI Add-on	Standalone AI Tools
Predictive Analytics	Built into every product, cross-product intelligence	Separate module, limited data access	Powerful but siloed, no ERP context
Conversational AI (Chatbots)	RAG-powered BOTs with full ERP/CRM data access	Basic scripted chatbots, limited integration	Advanced NLP but no business data context
Computer Vision	Quality inspection, document processing, AR/VR	Typically not available or separate vendor	Good vision but no enterprise workflow integration
Demand Forecasting	Multi-signal forecasting using sales, inventory, market data	Statistical models on limited historical data	Good models but require manual data preparation
Anomaly Detection	Real-time across all operational data streams	Basic threshold alerts on financial data	Advanced detection but narrow data scope
Process Automation	AI-driven cross-product workflow automation	Rule-based automation within single modules	RPA-style automation without business intelligence
Custom Model Training	AutoML pipelines + managed training infrastructure	Requires separate data science platform	Excellent ML but disconnected from operations
AI Governance	Bias detection, fairness metrics, explainability built-in	Limited or non-existent governance tools	Governance for specific models only

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Still Have Questions?

Our team is here to answer any questions about our AI-powered enterprise solutions, implementation process, pricing.

Frequently Asked Questions

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Industry-Specific

About Pixel Tech™

What is Pixel Tech™?

What industries do you serve?

What makes Pixel Tech™ different from other enterprise software companies?

Who are the founders?

What is the Pixel Ecosystem?

How does the milestone-based billing work?

What does “majority referral growth” mean?

What is hub-and-spoke architecture?

Do you offer demos?

Where is Pixel Tech™ based?

Getting Started Questions

What does the initial discovery process look like?

How quickly can I go live with my first product?

What if I am not sure which products I need?

Do you offer a proof-of-concept engagement?

What documentation do I need to provide during onboarding?

How involved does my team need to be during implementation?

Can I run Pixel Tech™ in parallel with my existing systems?

What happens on go-live day?

What is hypercare support?

How do you handle change management during implementation?

Product Questions

Can I use individual products or do I need the full ecosystem?

How is AI built into your products?

What is Pixel ERP™?

What RFID hardware do you support?

How does Pixel Engage™ (Bots) work?

Is Pixel Cart™ suitable for B2B e-commerce?

What does Pixel Exhibitions do?

What is Pixel Reality?

How does Pixel Voice work?

What is the Pixel Trade Portal?

Ecosystem Integration Questions

How do Pixel Ecosystem products share data?

Can I integrate Pixel products with third-party tools I already use?

What is the event bus and how does it work?

How does cross-product AI intelligence work?

What happens to my data if I add a new product later?

How do you handle data consistency across products?

Can different departments use different products independently?

What APIs are available for custom development?

How do automated workflows span multiple products?

Is there a unified dashboard across all products?

AI & Automation Questions

What AI technologies do you use?

What is the difference between AI-native and bolt-on AI?

How accurate are your AI predictions?

Can AI features be customized for my business?

How do you handle AI bias and fairness?

What predictive capabilities are available?

Do you offer computer vision capabilities?

How does RAG work in Pixel Engage™ (Bots)?

Can I train custom AI models on my data?

What is the AI engine in the hub-and-spoke architecture?

Technical Questions

What is your tech stack?

Is the platform cloud-hosted or on-premise?

What security certifications do you have?

Can I integrate with my existing systems?

How do you handle data migration?

What uptime do you guarantee?

How do you handle scaling?

What about disaster recovery?