Product

We use it first. Then you can too

Every product's first customer is our own company. 5 AI units run on it daily — not a demo, our actual operating system

OOMeta OS

Enterprise AI Operating System

Encode industry expertise, judgment, and workflows into continuously running systems. Built-in signal ingestion, decision engine, action queue, and heartbeat monitoring — not a tool, not a report, your business's own intelligent operating system

—Signal layer — auto-collect market, customer, operational data

—Decision engine — turn strategic judgment into runnable logic

—Action queue — auto-assign, execute, and track tasks

—Heartbeat monitoring — real-time visibility into every unit

Architecture ▾

Technical Specifications ▾

Runtime	Python 3.13+ / Hermes Agent
Data Layer	SQLite + FTS5 (structured) / Filesystem (unstructured)
Decision Latency	< 500ms per judgment (LLM) / < 10ms (rules)
Uptime	99.5% (self-hosted on VPS)
Integration	Webhook, API, CLI, Discord, WeChat

Use Cases ▾

A trading unit that scans 100+ market signals daily, makes buy/sell decisions, and executes trades without human intervention

A research unit that monitors 30+ competitive intelligence sources, generates reports, and alerts product teams to shifts

An operations unit that runs 50+ cron jobs, detects failures, and auto-remediates common issues before they escalate

vs. Alternatives ▾

Feature	OOMeta	Alternative
Signal ingestion	Multi-source auto-collection	Manual or single-source
Decision execution	LLM + rules hybrid	Rules-only or human-in-loop
Action tracking	Built-in AQ with priority queue	External ticketing system
Monitoring	Heartbeat per unit, real-time	Dashboard with manual refresh
Self-healing	Auto-remediation on failure	Alert-only, human fixes

OOMeta Guard

AI Agent Governance Platform

Cross-vendor, cross-regulatory AI Agent governance layer. From discovery to control to optimization — one platform covering the full lifecycle of Agent governance. Two independent studies confirm: 88.4% of organizations had AI agent security incidents (AvePoint 2026, n=750) and 88% of enterprises already have confirmed incidents (Gravitee 2026, n=919). 89.5% have systemic governance gaps. Only 14.4% of agents have security approval.

—Agent discovery — scan every deployed AI system

—Access audit — what data each Agent can reach

—Compliance engine — maps to FINRA, Colorado AI Act, Great American AI Act, EU AI Act

—Cost analysis — full visibility from tokens to infrastructure

Architecture ▾

Technical Specifications ▾

Decision Architecture	Dual-layer: deterministic rules (ms) + LLM reasoning (s)
Compliance Standards	EU AI Act, AIUC-1, FINRA, Colorado AI Act, Great American AI Act, NIST NCCoE Referenced Standard
Integration	Hermes Plugin, MCP Protocol, REST API
Audit Trail	Immutable SQLite + FTS5, every decision logged
Budget Control	Per-agent, per-model, rolling 24h/7d/30d windows

Use Cases ▾

A CISO discovers 47 unapproved AI agents running across 3 cloud providers, audits their data access, and enforces a zero-trust policy in 2 hours

A FinOps manager detects a cost anomaly — one agent spent $12,000 in 4 hours on a misconfigured loop — and auto-blocks the model before the bill hits

A compliance officer generates an EU AI Act compliance report for 15 agents with one command, mapping each to specific articles and risk categories

vs. Alternatives ▾

Feature	OOMeta	Alternative
Governance layer	Behavior + cost + compliance	Consumption or access only
Execution timing	Pre-execution (before call)	Post-action (after the fact)
Decision method	LLM reasoning + deterministic rules	Deterministic rules only
Learning	Learns from historical decisions	Static rules, no learning
Coverage	Cross-platform (Hermes → MCP → API)	Single platform/ecosystem

OOMeta Signal

Intelligent Intelligence System

24/7 automatic scanning of market signals, competitive dynamics, and regulatory changes — compressing noise into actionable intelligence

—Multi-source ingestion — news, regulatory, social, industry reports

—Smart classification — AI prioritizes signals automatically

—Action triggers — high-priority signals enter the action queue

—Trend analysis — detect structural shifts from signals

Architecture ▾

Technical Specifications ▾

Sources	30+ continuous feeds (news, regulatory, social, industry)
Classification	LLM-based 4-tier priority (P0-P3) with confidence scoring
Ingestion Cadence	Every 30 min (P0) / 2h (P1) / 6h (P2) / daily (P3)
Action Integration	Auto-creates AQ tasks for P0 signals
Output Formats	Daily digest, real-time alerts, trend reports

Use Cases ▾

A product team is alerted within 30 minutes of a competitor launching a new feature, with a full analysis of what it means for their roadmap

A regulatory team catches an EU AI Act amendment on the day of publication and has a compliance impact assessment before the close of business

An investment team receives a daily signal digest that surfaces 3 structural shifts in their sector, each with supporting evidence and recommended actions

vs. Alternatives ▾

Feature	OOMeta	Alternative
Source coverage	30+ continuous feeds	5-10 manual or single-source
Priority classification	LLM-based, 4 tiers, confidence scored	Keyword-based or manual
Action integration	Auto-creates tasks for P0 signals	Email alert, manual triage
Trend detection	Structural shift analysis with pattern recognition	Basic keyword trending
Cadence	30min to daily, per-priority configurable	Daily batch only

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