Venkata Peetla
Venkata Peetla — professional headshot

Venkata Peetla

Principal AI Architect

I architect digital employees that own a whole role: verification, public-records research, or adjudication, inside the customer's current systems. The public 6-spine path is the reference pattern for governance, retrieval, and eval gates — not the production runtime. Full catalog is 18 products / 17 repos.

Principal AI Architect · SNH AI · Digital employees for regulated operations

Executive briefLinkedInLeadershipEmbed method

Signal

Writing and proof — not launch spam

Decision-first posts and one flagship essay tied to the live spine. Calendars and outreach logs stay in the architecture portfolio — not here as marketing wallpaper.

FDE Field Method

Discovery → wedge → HITL → handoff — how the architecture lands in the customer org.

Flagship essay

Why I split multi-agent OS from governance — with live proof, not a manifesto.

Substack

Weekly architecture decisions — not launch spam.

ADR post calendar (S5)

Ten decision-first posts tied to ADRs and the review path.

Golden path artifact

Replayable ask→RAG→govern→meter JSON — stranger can verify.

NIST AI RMF one-pager

Govern/Map/Measure/Manage mapped to controls I actually run.

FinOps ROI one-pager

Cost as a constraint, with meter proof from the golden path.

AWS ephemeral receipts

AegisAI ECS apply→destroy. I refuse always-on EKS for portfolio theater.

GCP serverless receipts

Cloud Run FinOps/ERAG — scale-to-zero, Always Free–friendly.

Cloud free-tier split

What stays warm on Render vs what I prove with ephemeral receipts.

Current Role

Principal AI Architect

SNH AI · Regulated operations · background screening · since Sep 2026

SNH AILucid MotorsVolvo CarsKaiser PermanenteSparity (Apple / Google clients)

Technical Review

The reference stack, live

Full portfolio
01Agent governanceGatewayHITLPolicy

AegisAI

Runtime control plane for agent fleets — gateway, policy, HITL, and audit.

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

Decision

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

Signal

Website deploy tools forced through approval_required policy on live platform.

Limitation

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

What shipped: AegisAI: gateway-first governance control plane →

  • AI Gateway SDK with OPA policy evaluation
  • Human-in-the-loop for high-risk tool calls
  • Agent registry with in-memory persistence (Postgres planned)
  • Governed orchestrators: content pipeline, stock research
Open live platformGitHubDeep dive
02Multi-agent OSLangGraph16 IntentsRAG Lab

Venkat AI Platform

Multi-agent OS with three orchestrators, seven RAG strategies, and gateway-wrapped delivery.

Three LangGraph orchestrators, seven RAG strategies, loop patterns (ReAct · Reflection · Plan-Execute), and gateway-wrapped delivery to Slack, Telegram, and WhatsApp.

Decision

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

Signal

16 routed intents · 7 retrieval strategies · AegisAI gateway on notify channels.

Limitation

Vector store optional on free tier; Enterprise RAG adapter bridges to governed RAG platform.

What shipped: Venkat AI Platform: three LangGraph orchestrators live →

  • Platform · Deep Research · Architecture Review orchestrators
  • Enterprise RAG adapter as 7th retrieval strategy
  • AegisAI gateway on notify channels
  • Specialist agents: Web, Knowledge, Critic, Planner
Open live platformGitHubDeep dive
03Knowledge layerHybrid RAGAccess ControlGraph Expansion

Enterprise RAG Platform

Access-aware hybrid RAG with ingest, citations, and optional HITL gates.

Authorization before ranking, hybrid retrieval, cross-encoder rerank, decline-to-answer, citation traceability, AegisAI HITL bridge, and Langfuse trace export.

Decision

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

Signal

golden-eval-registry CI · adversarial suite · JWT Principal when PRODUCTION_STRICT=1.

Limitation

Default live demo is Demo mode (body Principal) with sticky banner; Strict/JWT is the Principal review path (ADR-0006). Free-tier corpus re-ingests after cold start.

What shipped: Golden eval registry gates real CI builds →

  • Access-aware filtering before semantic ranking
  • Hybrid lexical + semantic retrieval with cross-encoder rerank
  • Decline-to-answer when retrieval confidence is low
  • JWT-verified Principal under PRODUCTION_STRICT · adversarial golden suite
Open live platformGitHubDeep dive
04Model PlaneSLMPEFTvLLM

ModelForge

Model Plane control surface — SLM, PEFT, CUDA vLLM, LLMOps — peer to the agent spine.

Hire-facing Model Plane for SLM bake-offs, PEFT receipts, CUDA vLLM metrics, and LLM gateway enforce+record. Composes DomainForge + upstream vLLM + aegis-llm-gateway (ADR-034).

Decision

One ModelForge flagship beats burying PEFT/vLLM in a teaching drawer (ADR-034).

Signal

Live https://modelforge-gamma.vercel.app/api/v1/posture — PEFT + CUDA vLLM + SLM + gateway all ready; both peft_gpu.json and vllm_cuda.json are real Mistral-7B-Instruct-v0.3 receipts on a rented L4 — real QLoRA SFT + DPO training (peft_gpu.json) and real upstream vLLM serving (vllm_cuda.json, 13.74 tok/s, TTFT p50 371.67ms).

Limitation

PEFT receipt reports real training config/timing, not a quality/win-rate score — DomainForge's S0-S4 eval harness isn't wired to real adapter inference yet (see the receipt's own known_gaps). vLLM metrics are a single dated benchmark run, not an always-on production serve claim.

  • Honest /api/v1/posture (ready vs smoke vs planned)
  • Receipt gallery for PEFT · CUDA vLLM · SLM bake-off
  • Taxonomy glassbox — LoRA · QLoRA · Multi-LoRA · classical ML lane
  • Composes DomainForge train + gateway route + vLLM serve path
  • Panel scripts for buy vs RAG vs PEFT vs self-host
Open live platformGitHubDeep dive
05Content automationLangGraphHITLPublish

AI Content Factory

Governed content pipeline — research, multi-platform drafts, HITL, then publish.

Research → five platform drafts → HITL review → governed publish through AegisAI gateway, OAuth adapters, and scheduled cron pipelines.

Decision

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

Signal

Real LinkedIn/X OAuth publish path when tokens configured.

Limitation

Clerk keys required for full pipeline; invite-only signup in production config.

What shipped: AI Content Factory: governed multi-platform publish →

  • End-to-end research and multi-platform draft generation
  • Clerk auth with human approval gates before publish
  • LinkedIn and X OAuth when tokens configured
  • AegisAI gateway blocks publish until policy allows
Open live platformGitHubDeep dive

Career recommendations

What colleagues say about working with me.

Direct quotes from my public LinkedIn profile — they speak to earlier delivery and collaboration. Current AI-architecture chops show up separately: code, ADRs, review paths.

View all on LinkedIn

“Venkata is a dedicated and talented engineer. He was an important team member in building the new iOS app for MAGNIFI. Venkata worked through fast paced and demanding development cycles without losing momentum; committed to helping keep important product releases on schedule. Venkata is team player and always upbeat and collaborative in his approach to development. I'm excited to see what Venkata will do next and look forward to working with him again in the future.”

Mark Koerner

Former colleague · MAGNIFI iOS program

Worked directly together

LinkedIn profile

“I have enjoyed working with Venkata on the MAGNIFI project. He was hired and immediately jumped into the fire of our first iOS release. He handled it with poise and great skill. He was the sole iOS developer on this project and the release was a success. He continues to work with great skill at building our updates. He was instrumental in helping me optimize my iOS emulation for setting up Appium and Selenium automation framework. I would recommend Venkata for an iOS Developer position.”

Former colleague

MAGNIFI iOS program · QA & automation

Worked directly together

Validate Credentials

Architecture Portfolio

37 ADRs and case studies — what I decided, what I refused, and live links.

Live Platforms

Start on the 6-spine path (incl. ModelForge). Full catalog (18) is for after you're convinced the spine holds.

GitHub

17 catalogued ecosystem repos — one brand: governed agent platforms.

Executive Brief

One-page summary — print to PDF.

LinkedIn

Employment and recommendations — verify SNH AI, then Lucid / Volvo / Kaiser.