Enterprise AI Architecture · Governance · Operations

Enterprise AI, unified — governed, multi-model, in your own cloud.

Every team in your company is buying AI tools separately. No cost visibility, no data governance, no architecture. ECOSYSHUB helps mid-size enterprises deploy Claude, GPT, Llama, and Gemini on one governed platform — without vendor lock-in.

Fixed price. Working pilot in 4 weeks. Led directly by a principal architect — never handed to junior staff.
01The problem

Costs are invisible

Nobody knows what AI actually costs the company each month — or what it will cost at scale.

Data is leaking

Customer and proprietary data flows into consumer AI tools with no PII controls or audit trail.

Locked in by accident

Teams build on whichever model they tried first — not the right model for the job.

Compliance can't answer

Auditors now ask: which data trained which model? What did that agent touch? Reconstructing the answer by hand costs months — and EU AI Act transparency obligations start Aug 2, 2026.

You don't have an AI adoption problem. You have an AI architecture problem.

The compliance clock
97% of organizations are running AI initiatives — only 5% say their data is ready to support them (Dun & Bradstreet, 2026). Regulators no longer accept that gap.
TODAY · GDPR & FDA 21 CFR Part 11 in force — fines to €20M / 4% of turnover AUG 2 2026 · EU AI Act transparency obligations DEC 2 2027 · High-risk AI systems AUG 2 2028 · AI in regulated products — fines to €15M / 3%
Free tool
CostLens — price your AI blueprint in minutes
Chat, RAG, agents, documents, voice — full TCO across models, infra, and people. No signup.
Try Free Calculator CostLens Pro →
02Services
Flagship · Start here

AI Readiness & Architecture Sprint

Fixed price · 4 weeks

From AI chaos to a governed, working multi-model foundation — assessment to live pilot.

  • Current-state & shadow-AI assessment
  • Multi-model architecture blueprint
  • Governance: budgets, PII policy, audit logging
  • Working pilot on your highest-value use case
Scope my Sprint
Compliance

ECOSYSHUB Assurance

Sprint add-on + monthly

Audit-ready AI evidence, built into your infrastructure — not reconstructed by hand when the auditor calls.

  • Model-to-data traceability: which dataset version trained which model
  • Data lineage & versioning across structured + unstructured data (lakeFS-class controls)
  • Controls mapped to EU AI Act Art. 10/12, GDPR, FDA 21 CFR Part 11, NIST AI RMF
  • Monthly evidence packs — chain of custody, agent activity, rollback proof
See a sample evidence pack
Operations · AIforce.ops

AI Integration Engineer

Assessment + monthly

An AI agent that watches your integration estate (OIC, MuleSoft, Boomi, AWS), diagnoses every failure, and drafts the fix for your approval.

  • Integration Health Assessment
  • 24/7 failure diagnosis with root cause
  • Agent-drafted fixes — always human-approved
Assess my estate
03The Sprint — 4 weeks
WEEK 1

Assessment

Map current AI usage (sanctioned and shadow), data sensitivity, and highest-value use cases.

WEEK 2

Architecture

Multi-model blueprint: which models for which workloads, routing strategy, integration patterns.

WEEK 3

Governance

Cost controls, PII policies, audit logging, and an approval framework compliance will sign off on.

WEEK 4

Pilot

A working integration on your top use case with governance live — not a slide deck.

04Why ECOSYSHUB
24+ years of enterprise architecture across Fortune 500 financial services, healthcare, and manufacturing — including large-scale legacy modernization programs.
Multi-model, multi-cloud, hands-on: AWS, GCP, Oracle Cloud, IBM — and daily work with Claude, GPT, Llama, and Gemini.
Governance-first, forged in regulated industries: financial services compliance, healthcare interoperability (FHIR), model risk management.
Educator & advisor: M.Tech (IIT Kanpur), doctoral research at Hasso-Plattner-Institut, advisor to the Strategic AI Program at the University of San Francisco School of Management.
05The Whitepaper
Free download · 13 pages

Architecting Governed Enterprise AI

The reference architecture behind our Sprint: multi-model routing, cost controls, PII guardrails, and audit-ready evidence — mapped to the EU AI Act, GDPR, FDA 21 CFR Part 11, and NIST AI RMF.

  • 6 original architecture infographics
  • The compliance-deadline timeline, decoded
  • Representative cost scenarios (planning estimates)

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06Questions
Which AI models do you work with?

All major providers — Anthropic Claude, OpenAI GPT, Meta Llama, Google Gemini — plus cloud-native options (AWS Bedrock, Azure OpenAI, GCP Vertex AI, OCI Generative AI). Vendor-neutral by design.

We already use ChatGPT Enterprise. Why do we need this?

A single-vendor subscription solves access, not architecture. Different workloads need different models, and you need governance that spans all of them.

Where does everything run?

In your own cloud account. Your data never leaves your compliance boundary — the gateway, guardrails, and evidence generation all run inside your environment.

How big does my company need to be?

The Sprint is designed for organizations of roughly 50–2,000 employees. Smaller businesses can ask about our Foundations package.

Who actually does the work?

Every engagement is led directly by our principal architect. No handoffs to junior staff.

Ready to see where you stand?

Book a free 30-minute AI assessment. You'll leave with three specific observations about your AI posture — whether you hire us or not.

Book My Assessment

Or email raveendra@ecosyshub.com