Governed runtime for AI-written apps
AI writes the app.
ObjectOS keeps it governable.
Point your coding agent at ObjectStack. It writes models, UI, workflows, permissions, and tools as compact metadata, not a full codebase. In many CRUD/workflow apps, code moves toward 1%, iteration toward 100x, and people review small governed diffs.
- Open protocol
- Apache 2.0, self-hostable
- ~1% code surface
- Metadata instead of app code
- ~100x iteration
- Small diffs, governed runtime
For AI-written enterprise software
Keep the systems that work.
Add a governed runtime for agents.
Enterprise AI does not need another rebuild project or another pile of generated code. It needs a compact target format agents can write, humans can review, and a runtime that keeps each change governed across legacy systems, new applications, and AI agents.
Platform capabilities
Start with the business model,
not a blank codebase
- 01
Give agents a business model
Model customers, orders, equipment, cases, and approvals as objects agents can read, relate, and act on.
- 02
Extend systems without replacing them
Add APIs, permissions, workflows, and intelligence on top of databases, ERP, CRM, and custom systems.
- 03
Generate metadata, not app code
For typical CRUD and workflow software, agents write the compact ObjectStack definition while ObjectOS supplies tables, APIs, UI, tools, permissions, and audit. Less code to generate, less code to review.
- 04
Enforce governance at runtime
Reuse enterprise identity, permissions, approval queues, and audit logs so every agent action has a defined boundary.
AI build and agent operations
Let agents create the software.
Keep people in the review loop.
ObjectOS turns objects, fields, workflows, permissions, and actions into declarative metadata that agents can read and update through governed tools. In the open-source edition, you bring your own AI: a coding agent writes metadata as source files, often a tiny fraction of a generated app codebase; you review the diff, and any MCP client can query your data. For CRUD and workflow surfaces, the runtime supplies the repeated 99%, so metadata-only changes can move at two-orders-of-magnitude iteration speed. The in-app Build and Ask assistants run on Cloud and Enterprise.
View the AI security model →AI Builder
Cloud & Enterprise: describe a change in natural language. The in-app Builder generates objects, fields, views, and workflows, then routes structural changes for approval. In open source, your coding agent writes the same compact metadata diff instead of a full app codebase.
AI Ask
Cloud & Enterprise: ask questions inside the product, analyze business context, and trigger approved actions within the signed-in user’s permissions. In open source, query the same objects through MCP with your own AI.
Tools / MCP
All editions: @objectstack/mcp exposes objects, queries, and actions as policy-aware tools for Claude, Cursor, any MCP client, or a local model.
How it works
Turn business operations into
a structure agents can use
ObjectOS describes objects, relationships, permissions, workflows, and actions in unified metadata. Agents change a compact definition layer instead of regenerating application code, so business iterations stay fast, reviewable, and governed.
Security and governance
Keep data in your network.
Let AI work inside permissions.
ObjectOS runs as a self-hosted runtime on your infrastructure. Business records, identities, audit logs, and files stay under your control; AI agents access objects through governed tools and inherit the signed-in user’s permissions.
Explore security and governance →Data residency
Connect your databases and storage. Unless you configure an external service, ObjectOS does not send telemetry, contact a license server, or transmit data back to ObjectStack.
User-scoped AI
Agents act as signed-in users and obey object, record, and field permissions, so they cannot see data the user cannot see.
Approval and audit
Structural changes go through a human approval queue. Reads, writes, tool calls, and permission changes can be written to audit logs.
Offline ready
Run in a VPC, on local servers, or in air-gapped networks with local models, internal identity, and your own secrets management.
Application templates
Start with working templates,
not a blank canvas
Helpdesk template
An AI-first customer support template for tickets, SLA, summaries, suggested replies, and knowledge retrieval.
View template source →Contracts template
Manage the contract lifecycle with metadata extraction, approval, renewal reminders, and audit trails.
View template source →Procurement template
Run purchase requests, suppliers, POs, receiving, and three-way matching as a governed application.
View template source →How it compares
Different from
the tools you know
vs Airtable
A real database with server-side logic and runtime governance — not a spreadsheet-style workspace.
Read the comparison →vs Retool
Business logic is reviewable metadata — not JavaScript scattered across screens.
Read the comparison →vs Lovable & Bolt
Agents generate governed metadata with schema and permissions — not a one-off codebase.
Read the comparison →Latest insights
Practical thinking on AI-native software
When an AI Agent Deletes Production Data: Runtime Guardrails Beat Prompts
The Replit database incident shows a structural lesson: an agent's blast radius must be controlled by runtime permissions, approvals, and audit logs, not only by a prompt.
Retool vs. Governed AI App Platforms: Can You Review Business Authority?
Retool has strong access governance, including RBAC, audit logs, SSO, and self-hosting. The harder question is whether business authority is declared as a reviewable fact.
Power Platform Lock-In: Dataverse, Azure, and the Self-Host Tradeoff
Power Platform is already inside the Microsoft tenant, but self-hosting, Dataverse export, AI usage pricing, and sovereignty requirements matter for long-running systems.
Next step
Start with the business data you know best.
Connect one existing system, define its key business objects, and let your agent ship the first governed AI-written application as a small metadata diff.
Learn how to connect existing systems →