A CIO-and-platform-team track for running AI coding agents fleet-wide in an Indian enterprise — stand up a Center of Excellence, pick vendors, then operate the live agent estate with managed settings, MCP security, AgentOps observability, and deterministic hooks.
For: CIOs, platform/IT teams, and AI Center-of-Excellence leads at Indian enterprises (1,000-50,000 employees)
Follow the steps in order. Each link opens an existing guide in the Learn Hub.
How to build and scale an AI CoE in Indian enterprises
Stand up an AI Center of Excellence before scaling agents.
Open guide3-year TCO, lock-in risk, exit strategy, SLA — OpenAI vs Anthropic vs Google vs Azure vs Bedrock
Pick the right coding-agent vendors with a defensible TCO and lock-in view.
Open guideNIST AI RMF + ISO 42001 mapped to DPDP Act — policy, risk, model lifecycle
Author the governance policy — NIST AI RMF / ISO 42001 mapped to the DPDP Act.
Open guideGovern Claude Code fleet-wide — managed settings via admin console/MDM/on-disk JSON, deny rules, version pinning, spend caps, Compliance API, headless CI
Govern Claude Code fleet-wide with managed settings, version pinning, and headless CI.
Open guideSet up Claude Code hooks (PreToolUse, PostToolUse, Stop, SessionStart) for non-hallucinating guardrails — veto risky Bash, scan writes for secrets, govern headless CI runs.
Add deterministic, non-hallucinating guardrails at the tool-call level via hooks.
Open guideSecure Model Context Protocol at enterprise scale — tool poisoning, rug-pulls, over-privileged agents, credential sprawl, and mitigations: least-privilege scopes, signed/version-locked tools, a governed gateway.
Secure the MCP integration layer — least-privilege scopes and a governed gateway.
Open guideGovern the running AI-agent estate — control-plane comparison (OpenAI, MS Agent 365/A2A, Anthropic, Gemini Enterprise), agent inventory, per-action safeguards
Operate the running agent estate — inventory, observability, and per-action safeguards.
Open guideRegulator-specific AI compliance for Indian banks, NBFCs, brokers, AMCs, insurers
Map the agent estate to BFSI regulator obligations (RBI, SEBI, IRDAI).
Open guideDPDP Act 2023 + data localisation for AI workloads, sovereign cloud, encryption, CISO matrix
Lock down data residency and security under the DPDP Act.
Open guideTime-saved vs revenue-uplift vs cost-avoidance formulas + 12-month ROI plan
Measure and report the ROI of the agent platform to leadership.
Open guideBy mid-2026 the question for Indian IT leaders is no longer whether to let developers use AI coding agents — it's how to govern a fleet of them safely. Once a team adopts Claude Code, Cursor, or Codex at scale, the hard problems become fleet-wide policy, deterministic guardrails, MCP security, and observability of what every agent actually did. This path is the CIO-and-platform-team run for an Indian enterprise: stand up a Center of Excellence, choose vendors with eyes open, then operate the live agent estate with managed settings, hooks, a governed MCP gateway, and AgentOps — all mapped to DPDP, RBI, SEBI, and IRDAI obligations.
That path is about deploying foundation models (Bedrock vs Vertex vs Azure) and writing the governance policy. This path is specifically about running AI coding agents at scale — the developer-facing toolchain (Claude Code, hooks, MCP) plus the operational layer (AgentOps) that governs the live agent estate. They complement each other.
No. The path uses Claude Code as the concrete example for managed settings and hooks because its enterprise admin layer is well-documented, but the governance principles — policy authoring, deterministic guardrails, MCP security, observability — apply across Cursor, Codex, and others. The vendor-selection guide helps you decide what to standardize on.
It's a strong, regulator-aware foundation — agent observability and audit trails are framed as the records a BFSI auditor will ask for. As always for regulated sectors, have your compliance and legal teams review the final posture before production. The RBI/SEBI/IRDAI guide tells you exactly what to bring to that review.
Managed settings pushed via admin console or MDM sit above local developer config and cannot be overridden, and hooks run as deterministic code rather than model suggestions — so a PreToolUse veto fires regardless of what the model decides. The hooks and managed-settings guides cover the exact precedence rules and how to enforce a fleet-wide kit.
Done with this path? Try another one.
See all 10 learning paths