Governed Autonomy
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Demos

See governed agents working through real operating workflows

These are descriptions of what you will see in a live walkthrough — not screenshots, not invented metrics. Each demo traces the same governed path: Problem → Input → Agent workflow → Evidence → Human gate → Output → Audit trail. The point is not a flashy output; it is that every step is shown, gated, and replayable.

What these are. Demos are scoped to your data and use case during a live session. We do not publish fabricated screenshots, customer names, or performance numbers. Finance demos run as a capability and governance demonstration on paper trading — no trading-return, alpha, or performance claims.
Demo library
What a live walkthrough shows you

Pick the workflow closest to your work. In a session we run it on representative inputs and show every rung of the governed-autonomy ladder along the way.

VC Deal Intelligence Venture Capital

  • Problem A lean team needs to evaluate more inbound deals than it can read.
  • Input A pitch deck, a data-room link, or a company name and URL.
  • Agent workflow Sourcing and triage personas extract the thesis, market, and team, then a Strategy Council deliberates.
  • Evidence Each claim links back to the source document or external signal it came from.
  • Human gate The partner reviews and decides whether to advance, pass, or request more.
  • Output A structured deal brief with strengths, risks, and open questions.
  • Audit trail Every signal and step is logged and replayable. See the VC solution.
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AI Due-Diligence Memo Adversarial DD

  • Problem Diligence memos take days and tend to confirm the thesis rather than stress it.
  • Input A target company plus available materials — deck, data room, public filings.
  • Agent workflow An adversarial persona argues the bear case while others build the bull case, then the Council reconciles.
  • Evidence Claims are cited to their underlying documents and sources; gaps are flagged, not papered over.
  • Human gate The reviewer accepts, rejects, or sends sections back before anything is finalized.
  • Output A balanced memo with an explicit risk register and confidence on each claim.
  • Audit trail Hash-chained logs let you reconstruct how every conclusion was reached.
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Founder OS Operator automation

  • Problem A founder loses hours to GTM prep, fundraising materials, and competitive research.
  • Input Company context, target audience, and the task at hand.
  • Agent workflow Operator personas draft GTM, fundraising prep, and competitive intel as a coordinated workflow.
  • Evidence Outputs cite the research and inputs behind each recommendation.
  • Human gate The founder edits and approves before anything goes out.
  • Output Drafted materials and a prioritized action list.
  • Audit trail Each step is logged and replayable. See the Entrepreneur solution.
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Executive Briefing Decision-support

  • Problem Leaders need a synthesized, trustworthy view across scattered sources before a decision.
  • Input A question or decision plus the relevant documents and data.
  • Agent workflow Personas gather, summarize, and reconcile inputs, surfacing disagreements rather than averaging them away.
  • Evidence Every point in the brief traces to its source, with calibrated confidence attached.
  • Human gate The executive reviews, probes, and decides — the agent does not act on its own.
  • Output A concise briefing with options, trade-offs, and confidence levels.
  • Audit trail The full reasoning path is logged and replayable for later review.
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AI Ops Workflow Declarative automation

  • Problem Recurring operational reporting and routing eats team time and drifts out of date.
  • Input A declarative workflow definition — schedule, steps, and data sources.
  • Agent workflow Scheduled and on-demand steps run in sequence or parallel, passing data between them.
  • Evidence Each step records its inputs and outputs so results are explainable.
  • Human gate Consequential steps wait for approval; routine steps run within their granted scope.
  • Output Delivered reports and notifications through your chosen channels.
  • Audit trail Runs are logged and replayable, with watchdog supervision over the running system.
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Knowledge / Second-Brain SecondBrain

  • Problem Organizational knowledge is scattered and answers are hard to trust.
  • Input A question against your captured documents and knowledge base.
  • Agent workflow Retrieval personas find relevant material and synthesize an answer with graded recall.
  • Evidence Each answer is traceable to the source passages behind it — degrade, don't block, by design.
  • Human gate The user can drill into sources and correct or confirm before relying on an answer.
  • Output A cited answer with its supporting evidence attached.
  • Audit trail Queries and sources are logged for later review and reuse.
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Governed-Autonomy Replay The differentiator

  • Problem You need to verify, not assume, that an agent decision can be explained after the fact.
  • Input Any prior decision the platform has logged.
  • Agent workflow The replay reconstructs the decision: the evidence gathered, confidence scored, and gates passed.
  • Evidence The hash-chained log shows the inputs, reasoning, and calibration behind the decision.
  • Human gate A reviewer can confirm the gate that fired and what authority the agent had.
  • Output A step-by-step replay of the decision, end to end.
  • Audit trail This is the audit trail — see the Trust Center and Architecture.
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Finance & trading demos. Where a demo touches markets or trading — including the investment-research workflows on the Investment Research OS — it runs strictly as a capability and governance demonstration on paper trading. Meta3Agents makes no trading-return, alpha, or performance claims anywhere on this site. Outputs are decision-support, not financial advice.
See it on your data

We will run the workflow closest to your work on representative inputs and show every rung of the ladder. See also Architecture and the Trust Center.

Request a live walkthrough →