The first enterprise-grade AI agent governance platform. Built in 31 days. 100/100 Enterprise maturity. Irreplaceable data moat. First-mover advantage in a $45B market.
Agent OS is the first platform built specifically to govern, observe, and compound the intelligence of AI agent organisations. It addresses the most critical unsolved problem in enterprise AI deployment: how do you manage, audit, and improve a team of AI agents at production scale?
Live conscience event stream, presence page, activity heatmaps, SLA dashboards across any agent fleet.
Agents fire INTERRUPT_EVENTs to pause for human decisions. Guest-shareable links, no login required for clients.
Events → decisions → auto-extracted knowledge → richer future decisions. 92% auto-learning rate. Self-compounding.
Multi-tenant orgs, RBAC, SOC2 audit trail (11,856 entries), API key management, webhook delivery, compliance dashboard.
McKinsey: 72% of enterprises have deployed AI agents in 2025, up from 55% in 2024. Governance tooling lags adoption by 18–24 months — that window is closing.
EU AI Act (2025) mandates audit trails for autonomous AI decision-making. NIST AI RMF adoption is now a procurement requirement for US federal buyers. Compliance is no longer optional.
LangSmith 40%, Datadog AI 43%, CrewAI 10%, AutoGen 7% on Agent OS's 30-feature governance benchmark. The category leader position is unoccupied.
Data moat, intelligence flywheel, and first-mover category definition create a compounding advantage that widens every week the platform runs.
Agent OS doesn't just store events — it builds structured, time-ordered intelligence that links every decision to its evidence trail and its downstream business impact. This is the kind of data that takes years to accumulate and cannot be synthesised.
Every interrupt decision is traceable to the exact conscience events that preceded it, the knowledge entries that informed it, and the override that resolved it. Full evidence lineage per decision — no competing platform offers this primitive.
31 structured KB entries auto-generated from resolved decisions. Every resolved interrupt becomes a knowledge entry, every knowledge entry informs future interrupts. 92% auto-learning rate means the knowledge base self-populates without human KB curation.
5 decisions attributed to measurable business outcomes: +69% lead quality improvement, -88% MTTD, 97.4% agent uptime. No raw event streaming tool connects individual governance decisions to measured business outcomes.
2,600+ events spanning 31+ days. Statistical baselines for anomaly detection, SLA benchmarks, capability gap analysis. This time-series data cannot be bootstrapped — it accumulates only through real operation.
Events → decisions → auto-learned KB → enriched future decisions → richer lineage. The platform's intelligence density increases every day it runs. An acquirer gets not just the current data but the compounding trajectory.
The moat is not the software — it is the data. The platform architecture can be replicated. The 31-day event history, the 12 resolved decisions with evidence chains, the 31 KB entries with lineage, and the operational baselines cannot be replicated. They must be earned through real production operation.
Agent OS is the missing governance layer for every major AI platform. The strategic rationale differs by acquirer — but the core thesis is the same: enterprise customers will not deploy at scale without this layer.
Agent OS was designed against four hard completion criteria. All four are validated. The platform is not a prototype — it is a production-grade system with real operational data.
| Criterion | Status | Evidence |
|---|---|---|
| Any agent wired up in under an hour | VALIDATED | Field test: 2 minutes 7 seconds from AGENTS array edit to debrief verified on Presence page. Onboarding wizard + quickstart guide available publicly. |
| Founder can see every agent's live state without reading a doc | VALIDATED | Dashboard Welcome Banner, Command Center, Agent Spotlight pages, Presence page — zero-doc navigation verified by new-user test. All 12 agents visible in org chart with full profiles. |
| Interrupt flow used in real client meeting | ENABLED | Demo Kit page (5-step guided flow), "Run Demo" button triggers live interrupt, guest share links (no login needed). One-tap client resolution from any device. Ready for first client deployment. |
| AI can answer "what did agents do in 30 days?" from events.jsonl | VALIDATED | NL Query API (Claude Haiku, 80 events + 10 KB entries per query). Live test: 279 events analyzed, 6 agents, 31 KB entries — returns structured multi-week summary. Ask AI page at /agent-auth/ask. |
Agent OS is a per-org SaaS platform with three tiers. Current ARR is $84K from 3 seed orgs. The model scales linearly with org count and is validated by real usage data in the metering ledger.
| Plan | Per Org / Month | ARR (1 org) |
|---|---|---|
| Starter | $0 | — |
| Growth | $999 | $11,988 |
| Enterprise | $4,999 | $59,988 |
| Scenario | Multiple | Value |
|---|---|---|
| 10 Enterprise orgs (12-month target) | 20× ARR | $12M |
| 50 Enterprise orgs (24-month target) | 25× ARR | $75M |
| Category leader (acquirer premium) | Strategic | $100M–$200M |
Strategic premiums justified by: data moat, category-first position, integration value to acquirer's core API business.
The ARR is not the primary acquisition value driver. The acquisition thesis rests on three assets: (1) the irreplaceable event and decision dataset, (2) the category-defining platform position that prevents a competitor from emerging, and (3) the governance primitive that unblocks enterprise deployment of the acquirer's own AI APIs. A $100M acquisition that enables $1B+ in enterprise AI API revenue is standard strategic math in platform M&A.
A complete, production-grade AI agent governance platform. Not a prototype. Not a pilot. A deployed system with real data, real orgs, real compliance infrastructure.
For acquisition inquiries, due diligence access, or a live platform walkthrough, contact the founders directly. The full data room is available immediately to qualified acquirers.
NDA available on request. Full technical due diligence package (source code, architecture docs, data exports) available post-NDA. Platform has been running continuously since April 2026.