Selected work

Built, measured, shipped.

Product work, client deliveries — anonymized where required — and public internal R&D, all held to the same engineering standard: measured, reproducible, shipped.

Kyberos — an agent that acts

[ Product · Built on our research ]

Context

Most assistants answer; we wanted an agent that acts. One interface that can research a topic, browse the web on your behalf, plan a real-world outing, and hand back structured results.

Constraint

Long-horizon tasks fall apart without structured planning — and users only trust an agent they can watch. The system had to stream its plan, steps, and reasoning live, not just its final answer.

System we built

A production agent platform built directly on our published GATS research: a three-layer planner (symbolic domains → learned statistics → frontier LLM) drives a tiered tool registry — web search and reading, structured report synthesis, an autonomous browser agent that streams live frames into the UI, voice conversation, and MCP integrations — over a server-sent-events pipeline, with a React front end that renders the agent's working "mind" in real time.

Outcome

The planning framework from the paper doing the planning in a live product: deterministic tool routing, auditable step timelines, and research-grade capabilities in front of real users.

Stack

  • GATS planner
  • FastAPI + SSE
  • React 19
  • Claude
  • headless-browser agent
  • MCP
  • Firestore

The research behind it →

Generative materials studio

[ Client delivery · Games tooling ]

Context

Game artists juggle a chain of disconnected tools to produce game-ready materials. Teams shipping across Unity, Unreal, Godot, and the web needed one pipeline from idea to engine-ready material set.

Constraint

Outputs had to be seamlessly tileable, physically based, and reproducible — with every channel inspectable before export — running entirely in the browser.

System we built

A browser-based studio with a guided, linear workflow: text prompt or reference image in → seamless tileable texture generation → refinement tools → a full PBR map stack (albedo, normal, roughness, metallic, ambient occlusion, height, emission) with per-channel preview → packaged export for the major engines and formats.

Outcome

One connected pipeline replacing several standalone tools, with deterministic generation so a team can reproduce any material from its inputs — from solo modders to studio art teams.

Stack

  • browser-first
  • generative image models
  • PBR map derivation
  • PNG / WebP / glTF export

Live trading-competition platform

[ Client delivery · Real-time web ]

Context

Make markets a spectator sport: a risk-free tournament where players trade virtual assets for their country's standing and watch the leaderboard move in real time.

Constraint

Real-time everything — live prices across forex, crypto, and commodities; rankings and broadcast alerts that update as trades land — with zero real money, so trust rides on the simulation being fair and consistent.

System we built

A dashboard-style web app on a modern React/Next.js stack: an embedded trading terminal over live multi-asset market feeds, WebSocket-driven leaderboards for players and countries, a broadcast layer with major-trade alerts, and a tournament engine with group stages and countdowns.

Outcome

A running competition platform that balances spectacle with functional trading mechanics — entertainment-grade presentation over exchange-grade data plumbing.

Stack

  • Next.js
  • WebSockets
  • live market feeds
  • ranking engine
  • simulated execution

GATS Planning Framework

[ Internal R&D · Published research ]

Context

LLM agents fail on long tasks because they re-derive the world from scratch at every step. Planning needs memory and structure, not just bigger prompts.

Constraint

Deterministic, auditable behavior — the property enterprise deployments actually require and most agent stacks can't offer.

System we built

A planning framework combining graph memory, layered world models, and tree search for efficient long-horizon reasoning — published on arXiv as GATS.

Outcome

A published, citable framework and the architectural playbook we use when a client's agent has to be right, not just plausible.

Stack

  • Python
  • graph memory
  • world models
  • tree search

Read the research →

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