Ablo
Ablo provides multiplayer infrastructure that enables AI agents and people to collaborate on the same Postgres data. The platform coordinates concurrent writes, record claiming, and change attribution through a typed TypeScript SDK, CLI, and hosted Model Context Protocol servers. It uses logical replication to read from existing databases and writes back through a scoped role, keeping the system of record in the customer's database.
- Developer Tools
- Artificial Intelligence
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
AI agents typically operate in isolation, making it difficult for multiple agents to collaborate on shared data without conflicts or data integrity issues. Teams building multi-agent systems lack infrastructure to coordinate concurrent writes, track changes, and ensure agents work from current data, limiting the scalability and reliability of agent-based workflows.
Solution
Ablo provides multiplayer infrastructure that enables AI agents to work together collaboratively on the same data. The platform connects to existing Postgres databases, allowing agents and people to work in parallel, reserve records when they need to take turns, and see what changed. Agents can verify that the data behind their decisions is still current before saving updates, and every accepted change is recorded with attribution. The engine ships as a typed TypeScript SDK, a command line for schema setup and evolution, and hosted Model Context Protocol servers that expose the same surface to coding assistants. A Python client and REST API cover additional runtimes, while the coordination service manages the transaction log without moving the system of record.
Target Audience
Primary customers are engineering teams building multi-agent AI systems that need coordinated access to shared data, particularly those already using Postgres and seeking to integrate agent workflows with human operations.
Features
- Postgres-native integration via logical replication streaming, with writes landing back in the same database through a scoped role
- Record claiming mechanism that lets agents reserve rows to coordinate turn-taking and prevent conflicts
- Typed TypeScript SDK, CLI for schema management, and hosted Model Context Protocol servers for coding assistant integration
- Python client and plain REST API for runtimes beyond the SDK
- Full audit trail recording every accepted change and who made it, with 1 GiB to 50 GiB audit storage depending on plan
- Apache License 2.0 client libraries with readable source code before commitment