Venkata Peetla — professional headshot
Open to opportunities

Principal AI architect — production agent systems you can inspect before we talk.

I design and ship governed agent platforms — orchestration, policy gates, enterprise RAG, and eval discipline. Panels start on a 5-spine review path; the full catalog and open repos are there when you want depth.

19 years at Google, Kaiser, Volvo, and Lucid · multi-agent platforms in production · reference stack you can fork, not slide-deck AI.

After 19 years building systems under real operational constraints, I treat agents as governed distributed systems—not prompts with tools.

For engineering panels → 5-spine review path (4 live + ADR hub) · Full catalog (12 catalog platforms)

19+

Years in enterprise systems

10→2

Agent ops staffing reduction

Multi-$M

Revenue & savings delivered

12

Production platforms shipped

20+

Engineers led

5

Governed AI platforms in stack

Govern the agent before it changes the business.

Start with AegisAI (governance), then orchestration, access-aware RAG, and a governed publish path. Labs and curriculum patterns stay in the full catalog — not the panel path.

5-spine review path (4 live + ADR hub)
Canonical case study

AegisAI

Monitor → Govern → Remediate — a runtime control plane for tool authorization, policy violations, HITL approvals, signed audit, and agent registry lifecycle.

Reviewer evidence

Control plane over agent builder — enterprises need governance across fleets, not another chat UI.

Website deploy tools forced through approval_required policy on live platform.

Registry defaults to in-memory on free tier; Postgres path documented for production.

Venkat AI Platform

LangGraph stateful graphs over linear chains — enterprise workflows need checkpoints and HITL.

Inspect supporting case study

Enterprise RAG Platform

Authorization before ranking — vector DB is implementation; access control is architecture.

Inspect supporting case study

AI Content Factory

AegisAI gateway blocks publish until policy allows — side effects never bypass governance.

Inspect supporting case study
Flagship thesis

From Multi-Agent OS to Agent Governance

Why VAP and AegisAI are complementary layers — not competing products.

Read the essay
Eval discipline

golden-eval-registry — regression gates wired into real CI

Six suite kinds (RAG answer, harness QA, repo fix, mission gate, graph HITL, brief gate). Enterprise RAG and AegisLoop fail builds on regression — not just validate fixtures. Running one suite for the first time found and fixed a real bug in its own fixture.

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