# AIORG — Make Your Organization AI-Native

> AIORG is where you give AI a real place in your organization — structure to work in, knowledge to work from, rules to work by — so you hand it goals and get back finished, verified work. Everything it learns is shared, everything it does is visible, and all of it is on the record.

## The Organization (the picture on our front page, in words)

Everything below is one governed Organization:

- **Workforce (product)** — AI departments that plan, coordinate, and deliver real work. Strategic leadership: a Product Owner owns the WHAT (vision, requirements, acceptance criteria) and routes through a Project Manager who owns the HOW (decomposition, scheduling, coordination). Six example departments — Engineering, QA, Security, DevOps, SRE, Marketing — each run a Director (directs), managers (control), and workers (do), with defined skills (Python, Go, React, Selenium, Kubernetes, Terraform, …) and real tool integrations (GitLab, GitHub, Jira, ArgoCD, Docker, Grafana, PagerDuty, HubSpot). Runtime: any LLM provider (OpenAI, Anthropic, Google, custom), validation gates (evidence bundles, quality review, crypto audit), results (deliverables, artifacts, reports).
- **Connect (product)** — the bridge from developers' laptops. Claude Code, GitHub Copilot, Grok CLI enroll as governed members; every tool call is policy-checked (each enrolled tool carries the Governance shield) and the agents take real seats in the departments beside the org's own AI workers.
- **Knowledge (product)** — one curated knowledge base for every agent: everything your org knows in one place, curated and kept current, served to every agent.
- **Context (product)** — see what every agent sees, live: what each agent is working on, the full history of every session, early warnings before things drift.
- **Governance (product)** — the boundary around everything: one gate for every agent action. Policy Gateway, access policies, identity isolation, audit ledger, proof of every action, cost controls; data filtering strips PII before anything reaches external APIs; egress control blocks unauthorized calls; every allowed and denied action is logged immutably.

## How organizations go AI-Native

1. **Expand your organization** — add departments in minutes; each is a new capability.
2. **Hire AI that knows the job** — staff departments with directors, managers, and workers; give them skills, job descriptions, and your existing tools and LLM providers.
3. **Ship work, not prompts** — submit requests and get back real deliverables with built-in quality gates.

## Built for enterprise AI adoption

- **Scale without hiring** — deploy whole departments in minutes, with the skills and tooling they need.
- **Compliance by default** — every action passes the Policy Gateway; every decision is cryptographically logged.
- **Evidence-based delivery** — deliverables include evidence bundles, validation results, and a chain of custody from request to artifact.
- **Model agnostic** — OpenAI, Anthropic, Google, or your own fine-tuned models, swappable per department, role, or task.

## Deploy your way

- **Cloud** — fully managed, live in minutes. Early access is invitation-only ([get started](/get-started)).
- **Self-hosted** — your Kubernetes, your data, air-gapped capable (contact sales@aiorg.io).
- **Hybrid** — cloud control plane, on-prem execution (contact sales@aiorg.io).

More: [products](/llms.txt) · [journal](/journal.md) · [pricing](/pricing.md)