The Memory and Control Layer for AI Agents
OpenSink records agent activity, manages human approvals, and provides a real-time timeline of execution — without locking you into any framework.
Works with all major AI frameworks and providers.
Sessions: durable, resumable agent execution
Every agent run is a Session. Sessions track state, handle human approvals, and let agents pause and resume without losing context.
invoice-processor-47Resumable
Agents can stop, crash, or wait — then resume without losing context
Human-in-the-Loop
Pause for approvals or input, continue exactly where you left off
Full Visibility
Inspect, debug, and audit every agent execution in detail
Durable State
Store execution variables that survive restarts and crashes
OpenSink stores session state — your agent code decides what happens next.
A control layer that stores what matters.
OpenSink gives you visibility into agent execution and a durable place to store the outputs that matter — sessions, decisions, and results.
After OpenSink
OpenSink becomes your control plane for agent execution and outputs.
Running agents in production is hard to control.
Agents produce
Without a control layer
- No visibility into execution state
- No way to pause for human approval
- Outputs scattered or lost
- Hard to debug or audit
Before OpenSink
Fragmented. Hard to access. Easy to lose.
Built around simple, explicit primitives
Sessions
Durable execution records with state, human-in-the-loop, and resumability
Sinks
Named containers for durable agent outputs
Items
Structured records agents write to Sinks
Jobs
Scheduled HTTP triggers for periodic agent runs
Boring by design — reliable in production.
Control how agents operate — anywhere
OpenSink doesn't replace your agents. It gives you a central place to configure and control their behavior.
Agent configurations
Define how agents behave, without hardcoding logic.
Stored, versioned, and inspectable.
Sessions & state
Durable execution records that survive crashes and restarts.
Agents store state, pause for human input, and resume exactly where they left off.
This is not observability.
Observability tools
- Logs & traces
- Debugging-focused
- High volume
- Disposable
OpenSink
- Structured data
- System-of-record
- Intentional
- Persistent
OpenSink stores outputs your system depends on — not telemetry.
Designed for agents. Loved by developers.
import { OpenSink } from "@opensink/sdk";
const sink = new OpenSink({
apiKey: process.env.OPENSINK_API_KEY
});
// Write an item to your sink
await sink.items.create("finance-news", {
title: "AAPL dropped 3%",
data: { ticker: "AAPL", change: -3 }
});
// Query items back
const items = await sink.items.list("finance-news");Agents can discover, read, and write data reliably — without custom glue code.
Available at launch
Memory and derived context are coming next — built on the same primitives.
Who OpenSink is for
Built for you if
- You're running AI agents in production
- Agent outputs matter beyond a single run
- You need reliability, not demos
Probably not for you if
- You only need logs or tracing
- You want a no-code agent builder
- You don't control your backend