ZENOUZ.ai
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Projects

Public work selected for clarity and substance.

Each project is here because it says something concrete about how AI should be built, used, or explained.

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ZenInvest

ZenInvest is an open-source investing system that brings screening, research, debate, and execution into one governed workflow. A multi-vendor committee separates strategy, skeptical review, and risk assessment; a proactive macro layer sets the market regime; and deterministic Python controls retain final veto power over capital. It runs autonomously cycle to cycle, but every cycle is pausable, auditable, and gated by hard rules no model can override.

Retail investors face information overload, fragmented workflows, and too many opaque tools. ZenInvest is designed to reduce that burden without pretending judgment can be outsourced.

PythonFastAPIReactSQLiteMulti-LLMLightGBMDockerSlack
Read the ZenInvest briefView ZenInvest on GitHub
Why it belongs here
  • Agentic architecture that stays inspectable
  • Operator-supervised autonomy
  • Learns only behind hard gates
  • Technical product posture over return promises
Portfolio

Working systems with clear boundaries.

Each project states what works, what remains experimental, and where human judgment stays in control.

activeEvidence-grounded job search intelligence

ZenGrowth

A local-first, auditable career operating system spanning role discovery, grounded applications, interviews, offers, and the first 90 days — while keeping personal data on your own machine.

  • Hard grounding gates reject any number or named entity a draft can't trace back to verified evidence
  • Structure-preserving CV tailoring realigns the summary and reorders evidence-backed lines instead of rewriting
  • Interview, offer, onboarding, and departure workflows preserve context beyond the application
  • Deterministic, explainable scoring with each material action recorded in an audit trail
  • Python
  • FastAPI
  • SQLModel
  • React 19
  • Claude
  • Tavily
  • SQLite
  • Docker
Read the ZenGrowth briefView ZenGrowth on GitHub
From the lab

5 more projects, documented as R&D briefs.

Earlier-stage work lives in the lab until it earns a full project page. Each brief covers the idea, the engineering, and the pattern worth reusing.

Research & EducationZenArena

Can an agent get better without changing its weights?

ZenArena puts one of agentic AI's favourite claims — that memory makes agents better — under a falsifiable test, using chess and a Stockfish truth signal to measure whether governed memory beats remembering everything.

Research & VisionZenForecast

Forecasting as a loop, not a number on a slide

ZenForecast is an open-source, governance-first Python framework that treats forecasting as a continuous predict → decide → act → learn loop — with interchangeable models, leakage-free backtesting, and an audit trail behind a single API.

Research & EducationZenLab

Measure before you build: a sandbox for de-risking agentic AI

ZenLab is an offline-first research monorepo spanning 21 AI/ML topics across 10 tracks — a place where agentic techniques must earn their way into production designs through experiments instead of hype.

Independent InnovationStitch

Prove it in physics first: a digital twin for a canal-cleaning robot

Stitch is a simulation-first digital twin of an autonomous, wildlife-safe, amphibious litter-collection robot — a six-package ROS 2 / Gazebo system that must pass its full mission in simulated physics before a single part is bought.

Lab projects graduate to full project pages here as they mature. The full collection, including the ZenInvest and ZenGrowth briefs, lives inWriting.