Let agents run in parallelwithout stepping on each other.

A drop-in coordination layer that keeps shared state correct when many agents read and write at once.

Quick install

Up and running in seconds

Scroll to see the installation

Finder
9:41
Finder
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Terminal
Notes
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The problem

When agents collide

01

Lost updates

Two agents read the same state, both modify it. The second write silently erases the first.

02

Duplicate task claims

No exclusive claim on a shared queue — two agents grab the same task and burn compute redoing it.

03

Contradictory decisions

One agent picks Postgres, another picks DynamoDB. Nothing enforces that only one answer wins.

04

Irreversible mistakes

The email sends, the trade executes, the record deletes — before anyone gets a chance to say no.

Live demo

See it in action

Watch agents coordinate on a shared task queue. No duplicates, no conflicts.

ZeroLock Playground

Agents

Alphaidle
Betaidle
Gammaidle

Task Queue

Analyze dataset
pending
Generate report
pending
Send notifications
pending
Update dashboard
pending

Event Log

Click "Run Demo" to start...

Watch how Beta's duplicate claim gets blocked — only one agent processes each task.

Integrations

Works with your stack

LangGraph
CrewAI
Vercel AI SDK
OpenAI
Anthropic

Drop ZeroLock into any agent framework. No rewrites required.

Three calls. Zero races.

Claim, work, commit

The SDK wraps the write-wait-reread protocol so an agent never has to hand-roll its own locking. If the claim loses, it just tries the next task.

1import { ZeroLockClient, claimTask, completeTask } from '@zlock/sdk-ts';
2
3const client = new ZeroLockClient({
4 gateway: 'http://localhost:8080',
5 agentId: 'worker-1',
6});
7
8// 1. Claim: exactly one agent wins each task
9const claim = await claimTask(client, 'task-queue', taskId, 'worker-1');
10
11if (claim.claimed) {
12 // 2. Work: nobody else is doing this
13 await processTask(taskId);
14
15 // 3. Commit: mark it done
16 await completeTask(client, 'task-queue', taskId, 'worker-1');
17}

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