ICS Compute helps enterprises connect data foundations, governance, GenAI architecture, and implementation into secure, production-ready business systems.
Move beyond disconnected pilots and bring Data & GenAI into real business workflows with the architecture, controls, and delivery approach required for enterprise operations.
Enterprise interest in GenAI has moved quickly, but many initiatives remain isolated from the data, governance, and business systems they need to operate in production.
AI initiatives are often developed independently across different teams, with no shared architecture or implementation direction.
The data required by AI remains distributed across systems, formats, and ownership boundaries.
Security, access, lineage, monitoring, and accountability are frequently addressed after the pilot has already been built.
A working proof of concept does not automatically become a stable, scalable, and measurable enterprise system.
ICS Compute brings the critical layers of enterprise Data & GenAI implementation into one accountable engagement.
Build a trusted and accessible foundation for analytics and AI workloads across the enterprise.
Establish access controls, lineage, monitoring, auditability, and responsible AI guardrails from the beginning.
Design production-ready RAG, AI agents, model orchestration, evaluation, and observability.
Embed AI into the applications, processes, and decisions teams already use.
Give teams governed access to internal knowledge, documents, policies, product information, and operational data.
Extract, classify, validate, and process information from contracts, invoices, reports, claims, and other complex documents.
Build agents that retrieve context, use approved tools, perform defined tasks, and escalate decisions when human review is required.
Modernize fragmented data environments and create a governed foundation for analytics and future AI use cases.
ICS Compute helps enterprises move from a defined business use case to a system that can be deployed, monitored, governed, and continuously improved.
Review the current initiative, priority use cases, data readiness, architecture, governance requirements, integration points, and expected outcomes.
Define the target architecture, business workflow, access model, success metrics, and implementation roadmap.
Develop the data pipelines, GenAI application, integrations, evaluation processes, and governance controls.
Deploy with monitoring, observability, cost controls, performance tracking, and continuous optimization.
Production readiness is measured through real operational impact, including:
Reduced analytical query costs by [approved figure] while improving query performance by [approved figure].
Improved infrastructure availability and reduced recovery time to [approved figure].
Improved release frequency and operational stability through a managed cloud environment.
Review your current initiative with ICS Compute and identify the gaps across data, architecture, governance, integration, and operational readiness.
The assessment is designed to provide a practical view of what is ready, what is missing, and what should happen next.
Eligible Data & GenAI workloads may receive up to USD 10,000 in AWS Credits.*
*Terms & Conditions Apply.