SV.Résumé
Field Journal — Vol. 2026Washington, DCAI Engineer

ShrikanthVilvadrinath

An AI built this site. I built the AI.

▸ currently building

I build production autonomous systems — agentic mortgage platforms, manufacturing ERPs, clinical AI pipelines, and live agent-to-agent networks that run without me in the room.

See the workRésumé idle · checking telemetry
Scroll — Field Note 01

Field Note 01 — Who

I'm an AI engineer finishing an MS in Data Science at the University of Maryland (4.0), after IIT Madras and an engineering degree in Ahmedabad. My work is multi-agent orchestration — LangGraph workflows, Temporal-backed pipelines, MCP servers, and A2A agent teams.

I care about the unglamorous parts: durability, recoverability, interpretability, and systems that fail gracefully at 3am. The fun part is when a fleet of agents ships real work while I sleep.

— Shrikanth

Now
AI Engineer
Based
Washington, DC
Studying
MS Data Science · UMD (4.0)
Obsessed with
agents that ship while I sleep

Field Note 02 — The Machine

I don't vibe-code. I command a team of agents.

I run an autonomous multi-agent stack in production. OpenClaw brokers structured task envelopes between agents — Kratos orchestrates, Loki scouts, Mimir writes and publishes, Hermes keeps the books — communicating asynchronously over Google ADK's A2A protocol and self-correcting around the clock.

A 'Justice League' of build agents ships code through the same envelope system, each commit attributed to the hero that wrote it. The newsroom ingests live feeds, reasons over them, and publishes — no human trigger.

Yes, agents helped build the site you're reading. That's the point: a generic AI site hides where it came from. This one shows you — because the origin is a system most engineers can't build.

Pantheon — live newsroom Control dashboard Source

agent roster — live

A2A over Google ADK · brokered by OpenClaw · running on a DigitalOcean VPS

Field Note 03 — Work

A handful of systems I designed, shipped, and left running on their own. Selected entries — newest first.

  1. 2026LIVE

    The Pantheon — Autonomous A2A Newsroom

    A real-time agent-to-agent newsroom where autonomous agents publish articles, monitor live feeds, and surface oracle data with no human trigger. Agents run 24/7 on a DigitalOcean VPS via OpenClaw + Hermes, communicating over Google ADK's A2A protocol and self-correcting around the clock.

    Live in production — the same agent team helped build this site.

    Next.jsSupabaseOpenClawHermesGoogle ADK / A2ADigitalOceanVercel
    stack
    Next.js · OpenClaw · Hermes · Google ADK (A2A) · Supabase · DigitalOcean
    architecture
    Kratos orchestrates → Loki scouts → Mimir writes/publishes → Hermes audits. Task envelopes over A2A.
    what it does
    Ingests live feeds, reasons over them, and publishes articles 24/7 — no human in the loop.
    what it is, really
    A software org staffed by agents. I'm the only human, and I'm mostly asleep.
    fun fact
    This very portfolio was partly built by the same Justice League of build-agents.
  2. 2026PRODUCTION

    Agentic Loan Origination System

    A multi-tenant mortgage platform that takes a borrower from application through AI document review, income verification, and underwriting decisioning — role-specific portals, ULDD compliance export, and multi-investor rate pricing. Built end-to-end at Confer Solutions AI.

    Every origination stage made durable and fully recoverable via Temporal.

    Next.jsTypeScriptTemporal.ioLangGraphMCPSupabaseBullMQ
    stack
    Next.js · Temporal.io · LangGraph · 4× MCP servers · Supabase · BullMQ · Redis
    architecture
    Temporal workflows per origination stage; MCP servers for doc retrieval, data extraction & encrypted multi-party email.
    what it does
    Application → AI doc review → income verification → underwriting decision, across role-specific portals.
    what it is, really
    A loan officer, an underwriter and a compliance team — compressed into a recoverable state machine.
    fun fact
    ULDD compliance export + multi-investor rate pricing, the parts nobody puts in a demo.
  3. 2026PRODUCTION

    StoneFactory ERP

    A full manufacturing ERP — sales orders, purchasing, CRM, production planning, inventory, wastage tracking, and multi-level approvals — plus a React Native PWA giving field teams real-time production access from the factory floor. The second production platform I shipped at Confer Solutions AI.

    One system from sales order to shop floor, on web and mobile.

    Next.jsFastifyDrizzleRedisTurborepoReact Native (Expo)
    stack
    Next.js · Fastify · Drizzle · Redis · Turborepo · React Native (Expo)
    architecture
    Turborepo monorepo; Fastify + Drizzle services; a PWA client for the floor.
    what it does
    Sales → purchasing → production planning → inventory & wastage → multi-level approvals.
    what it is, really
    The boring-but-load-bearing software a real factory runs its day on.
    fun fact
    Field teams check live production from their phones — offline-tolerant PWA.
  4. 2026LIVE

    Git Gardener — Agentic Repo Intelligence

    Connect any GitHub repo and get a full health analysis with an LLM-generated reorganisation plan. A FastAPI backend decomposes each repo into a Temporal activity chain that classifies files, scores complexity, and ranks a cleanup roadmap by impact — with automatic retries and per-repo drill-down.

    Temporal-powered ingestion with GitHub OAuth; results persisted in Postgres.

    Next.jsFastAPIPythonPostgreSQLTemporal.ioDocker
    stack
    FastAPI · Temporal.io · Next.js · PostgreSQL · SQLAlchemy · Docker
    architecture
    Each repo → a Temporal activity chain (classify → score → rank) with automatic retries.
    what it does
    Reads a repo and hands back a cleanup roadmap ranked by impact.
    what it is, really
    A senior engineer's first-day 'let me reorganise this' instinct, automated.
    fun fact
    Built it because I kept doing repo archaeology by hand. Now Gardener does it.
  5. 2025PRODUCTION

    Clinical Intake AI — Longevity Imaging

    An agentic patient-intake platform for a longevity imaging centre. AI agents extract and structure form data, run eligibility checks, and send automated follow-ups end-to-end with no manual handoff. A document-intelligence layer runs diagnostic reports through an LLM pipeline with an interactive Q&A interface.

    Reduced review time ~35% and resolved 90%+ of queries autonomously across 100+ reports.

    Next.jsTypeScriptLangGraphLangChainOllamaSupabasePython
    stack
    LangGraph · LangChain · Ollama · Next.js · Supabase · Python
    architecture
    Intake agents + a document-intelligence LLM pipeline that standardises clinical terms.
    what it does
    Forms → structured data → eligibility checks → automated follow-ups, no human handoff.
    what it is, really
    The front desk and a first-pass radiology assistant, working nights.
    fun fact
    ~35% faster review and 90%+ of queries resolved on their own, over 100+ reports.
  6. 2025RESEARCH

    Diffusion / DiT Anomaly Detection

    Industrial surface-defect detection on the MVTec AD dataset using a modular diffusion / DiT-style model — a reproducible training pipeline with custom anomaly scoring and config-driven experiment management. Graduate research at UMD (DATA612).

    PythonPyTorchCondaMVTec AD
    stack
    PyTorch · Python · Conda · MVTec AD
    architecture
    Diffusion reconstruction error vs DiT-style backbones; config-driven experiment runner.
    what it does
    Spots surface defects on industrial parts it has never seen labelled.
    what it is, really
    The 'is this part broken?' question, answered without defect labels.
    fun fact
    Anomaly scoring is custom — the model learns 'normal', then flags the weird.

FIELD NOTE 04 — TRACK RECORD

Where the agents went to work — production systems shipped, not slideware. A few of the rooms I've built in.

0%
faster clinical review
0%+
queries resolved autonomously
0+
diagnostic reports parsed
0
agents running in production

  1. Jan 2026 — May 2026

    Confer Solutions AI

    AI EngineerRemote

    Built two production agentic platforms end-to-end.

    • Agentic Loan Origination System: a multi-tenant mortgage platform taking a borrower from application through AI document review, income verification, and underwriting decisioning — role-specific portals, ULDD compliance export, multi-investor rate pricing. Four MCP servers handle document retrieval, mortgage data extraction, and encrypted multi-party email; Temporal workflows make every origination stage durable and fully recoverable.
    • StoneFactory ERP: a full manufacturing ERP — sales orders, purchasing, CRM, production planning, inventory, wastage tracking, and multi-level approvals — plus a React Native PWA giving field teams real-time production access.
    • Next.js
    • TypeScript
    • Temporal.io
    • LangGraph
    • Supabase
    • BullMQ
    • Redis
    • Turborepo
    • Fastify
    • Drizzle

  2. May 2025 — Dec 2025

    NV Rad Imaging

    AI EngineerTampa, FL (Remote)

    Built an agentic patient-intake platform for a longevity imaging centre — AI agents extract and structure form data, run eligibility checks, and send automated follow-ups end-to-end with no manual handoff.

    • A clinical document-intelligence layer runs diagnostic reports through an LLM pipeline that extracts key terms, standardises terminology, and surfaces an interactive Q&A interface.
    • Reduced review time ~35% and resolved 90%+ of queries autonomously across 100+ reports.
    • Next.js
    • TypeScript
    • Supabase
    • LangGraph
    • Python
    • LangChain
    • Ollama

FIELD NOTE 05 — FOUNDATIONS

Where the groundwork was laid.

Aug 2024 — May 2026
College Park, MD
GPA 4.0 / 4.0

M.S. Data Science

University of Maryland, College Park

Jan 2021 — Dec 2024
Chennai, India
GPA 3.5 / 4.0

B.Sc. Data Science

IIT Madras

Sep 2020 — Jun 2024
Ahmedabad, India
GPA 3.5 / 4.0

B.Tech. Electronics & Communication

Vishwakarma Govt. Engineering College

Marginalia · Honors

  • Rank 5 — DSA Competition, IIT Madras
  • NumPy ML Certification (IITM Proctored Exam)
  • Member, Code:Black — UMD College Park

Field Note 06 — Toolkit

The instruments, indexed. What I reach for when a system has to ship and keep running without me.

Languages

TypeScriptPythonJavaC++SQLR

AI / Agents

LangGraphTemporal.ioOpenClawMCPA2A CommunicationAgent TeamsLangfuseVercel AI SDK@ai-sdk (Anthropic / OpenAI)

Web

Next.jsReactFastifyFastAPIFlaskDjangoReact Native (Expo)

ML / Data

PyTorchTensorFlowscikit-learnPandas

Cloud / Infra

AWS (S3, SageMaker)GCPPostgreSQLSupabaseRedisDockerTurborepoVercelDigitalOceanKafka

Colophon — Get in touch

Let's build something that runs itself.

shri15@terpmail.umd.eduGitHub LinkedIn Résumé

Set in Bricolage Grotesque & Geist Mono. Built with Next.js, deployed on Vercel. Agents helped build this — that's the point. See Field Note 02.

psst — type kratos