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Founder building governed AI systems: fail-closed execution, audit-grade receipts, agent infrastructure, and reliable automation.
Terraform plan, but for agent actions: every risky tool-call runs first in a disposable Daytona sandbox, gets measured, and is cleared to run for real only if it passes a fail-closed policy gate.
The context lie detector for your DataHub catalog
QA for non-deterministic AI agents: Proctor learns each automation's behavioral contract, catches silent model/prompt regressions, and escalates real failures to a human — all governed by UiPath.
Noise-aware eVTOL corridors: route flight by who hears it
Evidence-bound audits for Codex runs: support, contradict, or admit the evidence cannot decide.
A memory engine for AI agents: typed memories, budget-bounded recall, timelyforgetting, and contradiction adjudication. Built on Qwen Cloud.
AI that reads the fine print for you: paste any dense document and get it in plain words, the parts that affect you, and the questions to ask before you sign.
Decisions vanish in Slack threads. Quorum detects them, drafts a record, gets one-click approval, files it to a Canvas, and answers 'what did we decide about X?' with cited sources.
What does changing this break? Blast-radius analysis on the GitLab Orbit knowledge graph — every definition, file & test that depends on a symbol, with a risk score and the tests to re-run.
Gemini 3 reads your AI agent's own traces, catches runtime regressions CI can't, and blocks the release. A human approves or overrides, every decision recorded for audit.
A governed AI agent that fact-checks any claim against the live web, shows every source it admits or rejects in real time, and ships a cryptographically signed receipt you can verify.