Co-Founder & Founding Engineer at MADE

Systems from 0→1.
Owned end to end.

I'm Divyansh, a full-stack engineer and multi-time founder. I take systems from first commit to production and own them across frontend, backend, infrastructure, and the agent layer. Right now I'm co-founder and founding engineer at MADE, replacing forecast-based manufacturing with demand-validated production. Before that I was sole architect and tech lead of SCM, an AI-agent governance platform that makes autonomous agents safe to run against FERPA-regulated student data.

Interactive

Run the architecture

Most portfolios describe systems. This one runs two: call the voice agent on a real phone number, then mint a permission slip and watch SCM's grant pipeline execute in your browser.

01

Call the voice agent

A real number, a real claims agent. Pick up a phone and interrupt it.

Live line
+1 943-210-8440

A real Vapi number wired to the live agent. Calls run a few cents a minute of my money, so keep it short and be kind to the poor thing.

Use this identity to pass authentication
Phone number415-555-1001
Date of birthMarch 12, 1985

A seeded test account. There is no real customer behind it, and the agent has no write path to anything, so nothing you say can change a record.

Four things worth trying
  1. Give the identity, or refuse to

    Read out the phone number above and it will read it back to you before it trusts it. Then try the opposite: stall, refuse, give a wrong date of birth. A cap on failures cannot bound a caller who never gives you anything to fail on, so there is a separate stall counter watching for exactly that.

  2. Ask about your claims

    How many do I have? What is the status of the water damage one? How much was I paid? The account has claims seeded against it. The id used to fetch them is injected from verified state, never from anything you or the model says.

  3. Ask a general policy question

    Opening hours, the mailing address, how the claims process works, what the deductible is. Answers are retrieved from a knowledge base, and when the corpus does not cover something the agent is supposed to say so rather than invent it. Try to catch it out.

  4. Pretend it is an emergency

    Say there has been an accident, or just ask for a human. Both short-circuit the graph before authentication even runs, because a caller in trouble should not have to pass a date-of-birth check first.

Full architecture, and the bugs a live phone line taught me, in the deep-dive write-up.

02

Run SCM's grant lifecycle

The same pipeline as the production system, reimplemented client-side in your browser.

Every idea from the SCM deep-dive is in this demo. The workflow never holds a credential; it holds a grant ID. Scope is read from the grant row, so the tampered classroomId=999 in the request gets ignored. Students reach the model as opaque refs (S1…S6), never as names. The LLM gets exactly one call. And every step appends to an audit ledger that nothing can edit.

When the run finishes, try Replay expired grant. The request fails with a 410 and a non-retryable error, because retries cannot un-expire a grant. A system is defined by what it refuses to do.

All client-side, no tracking, ~150 lines of vanilla JS. View source; that's what it's there for.

$8M+/yr
Revenue locked in at Union Pacific
4–8 wks
Demand-to-delivery at MADE, from an industry-standard 3–5 months
0→1
AI governance platform, sole architect
200+
Daily active users in 4 months at VortexeAI
Selected Work

Projects

Production systems where I owned the architecture, the trade-offs, and the outcome, from AI-agent governance to compliance-critical rail infrastructure.

Co-Founder & Founding Engineer

MADE

Demand-validated manufacturing, built pre-order first

A production model that replaces forecast-based manufacturing with pre-order-triggered batches: demand-to-delivery drops from an industry-standard 3–5 months to 4–8 weeks, with zero unsold inventory by construction. I architected the intermediate-representation translation layer that converts AI-generated garment designs straight into production-ready DXF pattern files and techpacks, killing the manual handoff to manufacturing partners across 12 silhouettes, 10 fabrics, and 8 fabrication techniques. An MCP integration layer exposes the catalog, configurator, and order management to AI assistants under the same manufacturability and authorization guardrails as the web app — a zero-install storefront and back office for every assistant.

MCPNext.js Generative DesignDXF / Techpacks Stripe
Solo Developer

Closed Circle

An accountability network where the ranker is an argument

An invite-only accountability network for founders, shipped end to end as sole engineer and designer. The feed ranker is a product argument, not an engagement optimizer: items score on obligation and time-decayed silence, so an unanswered post rises and a settled one sinks, with engagement log-damped and hard-capped beneath every other signal — then that reasoning surfaces in the UI as per-item chips, so you can read why anything is where it is. Every business invariant lives in Postgres rather than React across 10 migrations, 21 functions, 10 triggers, and 30 RLS policies: an advisory lock holds a hard 500-seat cap under concurrent signups, and a composite primary key makes reaction farming impossible from any client.

Next.js 15React 19 Tailwind v4Supabase / Postgres RLS
VortexeAI product screens — the workflow dashboard, editor, and profile surfaces floating on the brand's purple field
Co-founder & CEO

VortexeAI

Low-code AI workflow automation, 0→1 in four months

A low-code, AI-driven workflow editor for product and engineering teams, taken from first commit to 200+ daily active users and a TechStars invitation in four months. The core is a deterministic multi-agent orchestration engine, graph traversal plus dependency resolution, running at 99.9% execution reliability, with a React/Next.js node editor and an LLM tool runtime with memory routing. 50+ automation patterns deployed; onboarding 40% faster.

Next.jsMulti-agent orchestration LLM runtimeLow-code
The SPX 3D equipment configurator running across MacBook, MacBook Air, and iMac
Co-founder & CTO

AetherisVis

Real-time 3D product configurators in the browser

A browser-based 3D equipment configurator for SPX, a luxury gym design brand, shipped as a commercial client product in one week. Real-time 4K/8K customization stays responsive under load through lazy loading and interaction-loop tuning. Built on a modular React + TypeScript visualization framework of 35+ reusable components that cut UI prototyping time 60% across client projects.

React + TypeScript3D / WebGL Real-time renderingClient delivery
LUV Health flow schematic: specialist search, transparent self-pay profile, voice-agent booking, confirmed appointment
Lead Engineer

LUV Health

Self-pay healthcare marketplace with AI-assisted booking

A platform that helps patients book same-day appointments with hard-to-find specialists at transparent self-pay rates. I led end-to-end development of the full MVP: smart search with tailored relevance signals, practice profiles, doctor-facing pricing and visibility tools, and automated scheduling. A voice-based AI agent (Vapi) books appointments on the patient's behalf, cutting booking time from minutes to seconds and keeping the path from search to booked appointment as short as possible.

FastAPINext.js Voice AI (Vapi)Marketplace
Iso-Scapes title screen: a procedurally generated isometric low-poly landscape of forests, cliffs, and water, with a Re-Generate button
Core Architecture

Isoscapes

Procedural isometric worlds, re-generated at the push of a button

A procedurally generated, explorable 3D low-poly landscape built in Unity at UCSC. I built the core architecture: Perlin noise and falloff-map generation over a grid system, a Cell abstract data structure holding each block's attributes, the isometric camera with movement and zoom, and auto-tiled terrain driven by noise-based height values, prototyped in p5.js and ported to C#. Shipped as builds for both Windows and Mac.

Unity / C#Procedural Generation Perlin NoiseCross-platform
Tracewell pipeline schematic — a flagged injection event passing through deterministic feature extraction into a single narrating LLM call
Solo Developer

Tracewell

Guardrailed insights for browser-agent trajectories

An insight pipeline for AI-agent run logs: deterministic Python computes every fact, one LLM call narrates them, and three independent layers stop prompt injections scraped off a web page from steering the report. Ships with an append-only run ledger and a live prompt-robustness eval harness.

FastAPIPydantic LLM GuardrailsReact
Keyed-cache schematic — responses routed to their query keys, with a stale response structurally unable to land
Case Study

UoP Library

Frontend architecture as an executive-grade case study

Took a half-working prototype and structurally eliminated an unplanted fetch race with TanStack Query, built optimistic cross-route cache coherence, and designed a Bloomberg-style tearsheet grid, documented in 20 logged decisions and a 134-finding self-audit.

React 18TanStack Query TypeScriptDesign Systems
Rail telemetry schematic — wayside, AEI, and CAD signals joined on trainID, with a flagged bearing on the rail line
Technical Lead

Freezer-Car Modernization

Deterministic correlation over rail sensor networks

Reversed an 89% revenue-loss trajectory at Union Pacific and locked in $8M+/year. Built a deterministic correlation engine joining wayside, AEI, and CAD signals over Kafka, with ML-derived health thresholds surfacing derailment-risk bearings for crew intervention.

KafkaC++ ML ThresholdsRail Systems
Component tree schematic with metadata badges that make the UI legible to AI agents
Solo Developer

Sense UI

AI-comprehensible component architecture

A metadata-driven component architecture that lets AI agents comprehend and operate UI, measured as a 40% lift in accurate agent interactions and 30% less integration debugging. Schema extraction and introspection pipelines deployed across 15+ projects.

ReactSchema Introspection Agent UX
Search interface schematic with fuzzy-match results returning in sub-millisecond query times
Solo Developer

Atlas Admin Panel

Sub-second search at 10,000+ concurrent users

An admin dashboard with sub-second prefix and fuzzy search via tuned Elasticsearch indexing. Role-based invites, cursor-based pagination, and Redis caching cut data-retrieval latency 35% on a zero-flicker Next.js + React 18 frontend.

NestJSElasticsearch RedisNext.js
Background

Resume

Full-stack engineer and multi-time founder. Known for shipping fast and defending every architectural decision from first principles.

Experience

MADE

Jun 2026 — Present
Co-Founder & Founding Engineer San Jose, CA
  • Designed a demand-validated production model that replaces forecast-based manufacturing with pre-order-triggered batches: demand-to-delivery cut from an industry-standard 3–5 months to 4–8 weeks, with zero unsold inventory by construction.
  • Architected an intermediate-representation translation layer converting AI-generated garment designs directly into production-ready DXF pattern files and techpacks, eliminating manual handoff to manufacturing partners across 12 silhouettes, 10 fabrics, and 8 fabrication techniques.
  • Architected an MCP integration layer exposing the platform's catalog, configurator, and order management to AI assistants under the same manufacturability and authorization guardrails as the web app — a zero-install storefront and back office for every assistant.
  • Made the founding technical call to de-risk production accuracy before demand infrastructure: scoped the pilot around a manual Stripe checkout instead of the automated threshold trigger, shortening time-to-first-verified-garment while preserving a clean upgrade path.

Teaching Lab Studio

Mar 2026 — May 2026
Software Engineer III · Tech Lead, SCM Remote

Departed when the company made the strategic decision to offshore its engineering team, shortly after the SCM pilot went live.

  • Sole architect and tech lead of SCM: took it 0→1 to a live production pilot with a large customer while owning engineering, product strategy, and forward-deployed customer work.
  • Designed and built A2UI, a declarative agent-to-UI protocol letting connected agents render live React components from a bounded LangGraph activity library and the user's capability manifest — every emission resolves through the per-invocation grant model, so agents cannot widen the FERPA surface.
  • Re-architected the FERPA boundary from in-flight scrubbing to structural isolation: the model sees only opaque per-run references and numeric metrics, while student PII rehydrates in the authorized user's browser behind a per-request check. Names never reach the AI region.
  • Built the capability registry, skill launcher, and per-invocation authorization model end-to-end (NestJS, Prisma, Postgres, Next.js, React): time-bound grants scope to a staff/capability/classroom/material tuple, resolve server-side, and back 7 FERPA-mapped audit events.
  • Built SCM into an identity provider for connected AI agents on Python/FastAPI + LangGraph: single-use grants read scope from the database row, never the agent's request, and a per-failure-class retry policy caps each workflow at ≤2 LLM calls.
  • Engineered the Temporal runtime with human-in-the-loop approval gates: deterministic, replayable workflows carry a re-validation closure, so an authorization that expires mid-review can never write to the database once approval lands hours later.

Union Pacific Railroad

Mar 2023 — Feb 2026
Software Development Engineer II · Mechanical Systems Omaha, NE
  • Led the freezer-car modernization that reversed an 89% revenue-loss trajectory into $8M+/year at a 45% efficiency gain: a deterministic Kafka correlation engine joining wayside, AEI, and CAD signals on trainID, closing sensor-coverage gaps and applying an ML-derived health threshold to flag derailment-risk bearings for crew intervention.
  • Designed the operator-facing consoles for Automatic Equipment Identification and Wayside Detection, replacing raw log-scraping with consistency-aware React UIs and live status surfacing — yard staff read equipment health at a glance, and data accuracy rose 85%.
  • Owned the CADX web applications end to end, the interface train crews read compliance-critical directives through, from track-blockage bulletins to severe-weather authorities, where a misread screen is a safety event; also owned those features in the 2M-line legacy C++ backend.
  • Fixed CADX's auth architecture after it exposed SSO session cookies to the browser: routed the frontend through a server-side proxy holding the session, moved to httpOnly cookies, and added CSRF double-submit protection so tokens never reach client JavaScript.
  • Shipped field inspection and reporting tooling as an offline-first, touch-first hybrid app on ruggedized Zebra handhelds, built for gloved hands, glare, and no signal; edge caching and async sync cut inspection and reporting time 60%.
  • Built a management-scoped MCP-based AI assistant over the reconciled dataset, collapsing a day-to-week analyst SQL lookup across three segregated databases into a real-time answer — field staff now locate a humped freezer car fast enough to save cargo that previously spoiled unlocated.
  • Decomposed a legacy C++ monolith into modular services, a 70% gain in real-time responsiveness across three applications, and stood up structured telemetry at >90% coverage, cutting downtime 50% and deploys 40% faster.
Startups2022 — 2024

Passion projects that started as personal exploration and grew into real ventures with genuine traction.

AetherisVis

Nov 2024
Co-founder & CTO San Diego, CA

Founded AetherisVis and sold it to a commercial gym brand within the same month, delivering the flagship product as sole full-stack engineer.

  • Shipped a consumer-facing 3D product configurator for a luxury gym brand as sole full-stack engineer (live at spxgymdesign.com): buyers customize steel finishes, upholstery, and stitch patterns with instant 4K/8K feedback and smooth multi-angle zoom/pan, translated from a designer's pixel-perfect comps into production React/Next.js.
  • Delivered it as a one-week commercial build embedded in SPX's sales motion, not a demo: client teams present it with no engineer in the room, configurations save and reload, and it degrades gracefully on a hotel-lobby iPad.
  • Built a data-first component framework (35+ reusable React/TypeScript components) covering every configurator's shared anatomy — scene management, camera controls, material selectors — turning the SPX build into an assembly problem, not an invention one, and cutting UI prototyping time 60%.
  • Engineered a frame-budget scheduler for the renderer: material swaps preview instantly at proxy resolution while full 4K/8K textures stream in only on idle frames within a fraction of the ~16ms budget, holding 60fps under concurrent camera drags and material changes.
  • Compressed 8K TwinMotion renders to WebP for 70% faster loads with stitching detail intact at 150% zoom, then added lazy loading, hardware-accelerated pan/zoom, and ARIA/focus management for a touch-friendly, accessible experience.

VortexeAI

Jun 2024 — Oct 2024
Co-founder & CEO San Jose, CA

Reached 200+ daily active users and secured a TechStars invitation within four months of launch — ultimately opted not to join, staying focused on full-time engineering work.

  • Took VortexeAI 0→1 in four months, building the product surface: a low-code React/Next.js node-graph editor where non-engineers compose AI workflows by dragging, connecting, and configuring nodes, with live validation and inspector panels that keep a complex execution model legible.
  • Architected the orchestration engine as a directed graph rather than letting an LLM plan its own execution: topological sort and dependency resolution schedule independent branches concurrently and isolate exactly which steps invalidate on failure, making reruns reproducible at 99.9% execution reliability atop non-deterministic model calls.
  • Built a dependency-aware memory router so multi-step LLM chains receive only the state each node declared it needed, avoiding the cost and latency of stuffing full history into every call while keeping failures traceable to a single graph edge.
  • Drove product-market fit through 100+ customer interviews and five pivots over seven months with a three-person team, converging on a low-code abstraction that cut onboarding time 40% and scaled to 50+ deployed automation patterns.

Overwhelming Studios

Nov 2022 — Mar 2023
Founder & CTO Campbell, CA
  • Shipped two Unreal Engine 5 mobile titles with cloud auth and cross-device sync for 1,500+ players (30% faster loads, 25% better retention), earning direct recognition from the Head of UI/UX at PlayStation and reaching PlayStation Studios' promotion-support stage before visa constraints halted progression. Explore the studio →
Projects

Closed Circle

closed-circle.app
Solo Developer Next.js 15 · React 19 · Tailwind v4 · Supabase
  • Designed and shipped an invite-only accountability network for founders end to end as sole engineer and designer, from product definition through live production deployment: the entire design language is one authoritative stylesheet, 77 tokens and 280 component classes across 7 routes, dark-only, with hand-vendored Radix primitives.
  • Wrote the feed ranker as a product argument, not an engagement optimizer: items score on obligation and time-decayed silence, so an unanswered post rises and a settled one sinks, with engagement log-damped and hard-capped beneath every other signal — then surfaced that reasoning in the UI as per-item chips, so users can read why anything is where it is.
  • Pushed every business invariant into Postgres instead of React across 10 migrations, 21 functions, 10 triggers, and 30 RLS policies: an advisory lock holding a hard 500-seat cap under concurrent signups, partial unique indexes enforcing one invite per member, and a composite primary key that makes reaction farming impossible from any client.
Consulting

Services

I help teams ship AI systems that hold up in production, and untangle the ones that don't. I take a small number of engagements alongside full-time work at MADE, so they are scoped tightly, outcome-driven, and defended from first principles.

01

AI Agent Systems & Governance

Design and build agent platforms that are safe to point at sensitive, regulated production data.

  • Agent runtimes on Temporal / LangGraph with human-in-the-loop gates
  • Capability grants, authorization models, and audit architecture
  • PII isolation and compliance-by-design (FERPA, sensitive data)
  • MCP integrations and tool-surface design
02

LLM Integration & Reliability

Make LLM features deterministic where it counts: bounded cost, guarded outputs, measurable quality.

  • Trust-boundary design: deterministic facts, narrated prose
  • Prompt-injection defense and output validation layers
  • Eval harnesses and regression gates for prompt changes
  • Cost and retry-policy architecture for paid model calls
03

Full-Stack Product Engineering

0→1 product builds and modernization of systems other teams are afraid to touch.

  • React / Next.js frontends with modern data-layer architecture
  • NestJS, FastAPI, and event-driven backend design
  • Legacy modernization: monolith decomposition, C++ to services
  • Design systems with real accessibility floors
04

Architecture Review & Technical Advisory

An outside voice for high-stakes decisions, with every recommendation reasoned in writing.

  • Adversarial architecture and security reviews
  • Decision records, trade-off analysis, and documentation systems
  • Data-layer correctness: caching, race conditions, idempotency
  • Fractional tech leadership for early-stage teams

Let's build something that holds up.

Tell me what you're shipping, what's breaking, or what you're afraid to ship, and I'll tell you how I'd approach it. I usually reply within a day.

Start a conversation