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ZenInvest

A flagship open project exploring AI-assisted investing with transparency and control.

ZenInvest is an open-source AI investing system built to make research, screening, and execution more structured, transparent, and auditable for retail investors operating with human oversight.

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Product framing

Retail investing is constrained by information overload, research time, execution overhead, emotional decision-making, and opaque alternatives. ZenInvest is designed to reduce that burden without pretending that judgment can be outsourced entirely.

Capability 6,900+ US equities screened
Capability 3-model investment committee
Capability 9 deterministic risk rules with veto power
Stack
  • Python
  • FastAPI
  • React
  • SQLite
  • Multi-LLM
  • Docker
Differentiation

Built as a transparent decision system, not a black-box promise machine.

The core idea is not just automation. It is structured challenge, clear risk handling, and inspectable reasoning.

Open

Open-source and inspectable rather than locked behind a proprietary black box

This is a deliberate product choice intended to make the system more trustworthy, inspectable, and educational for the people using it.

Control

Human-in-control portfolio decisions with explicit reasoning and risk constraints

This is a deliberate product choice intended to make the system more trustworthy, inspectable, and educational for the people using it.

Posture

Designed as a research and product experiment with educational value, not a guaranteed-return machine

This is a deliberate product choice intended to make the system more trustworthy, inspectable, and educational for the people using it.

Architecture and ecosystem

A committee-style system backed by a wider tooling ecosystem.

ZenInvest combines orchestration, data collection, model collaboration, and execution tooling across a broad set of APIs and platforms.

Core architecture

Multi-LLM committee, deterministic guardrails, human oversight.

The product direction combines market intelligence, model-based synthesis, explicit skepticism, and deterministic rules that no model can override. The aim is not to replace judgment, but to give it a better operating system.

Ecosystem
  • Anthropic
  • OpenAI
  • Google
  • Trading 212
  • Brave
  • Tavily
  • Finnhub
  • Alpha Vantage
Disclaimer

Public project, not financial advice.

This page should be ambitious about the product and conservative about claims.

ZenInvest is not financial advice. It is an educational, research, and product experimentation project. Human oversight remains essential, and any live use should be approached cautiously.

Next milestones

Where the project page can go next.

The current site presents a sharp public brief now and leaves space for deeper case-study material later.

Case study

Detailed pipeline walkthrough

Expand this page into a richer system narrative once the product and screenshots are ready for publication.

Governance

Show the safety model clearly

Document the role of deterministic risk rules, operator controls, and auditability more deeply over time.

Writing

Turn the build into essays and learning

Use ZenInvest as a source of public writing on multi-LLM systems, product design, and decision support.