Launched this week
Airbyte Agents
The context layer for production-grade AI agent
45 followers
The context layer for production-grade AI agent
45 followers
The context layer for production-grade AI agents. Connect Salesforce, Stripe, Zendesk +50 more into a queryable Context Store, so your agent reasons across systems without stitching APIs at runtime. UI, MCP, or SDK. 40% fewer tool calls, up to 80% fewer tokens.
Connector Builder by Airbyte
The "context layer" framing is exactly what's missing in most production agents — the value isn't "call this API", it's "reason across systems without rebuilding the join at runtime." 80% fewer tokens is a serious unlock when you're deploying agents on noisy, time-sensitive data streams. We hit a parallel problem on the financial side: agents watching prediction markets and trading flows produce signal soup unless you give them a unified context of positions, baselines, and event history. That's basically what we built into PolyMind for Polymarket alerts. Curious how Airbyte's Context Store handles temporal data — do you snapshot events with timestamps so an agent can reason about "what changed since 9am" without re-pulling raw API history?
@samir_asadov Hi Samir, Henry from airbyte here. The Airbyte Context Store maintains a search-optimized index of your data so agents can instantly query "what changed since 9AM" without the lag of raw API loops. We use a hybrid approach to keep things efficient: agents use the Context Store for sub-second discovery, then perform a direct call to the API to verify the latest state right before they execute a task.
I feel like a lot of these products are solving for invented solutions.
I had limited coding experience before starting to build my own enterprise apps + websites in Feb, and I have honestly not come up against I problem I have not been able to solve on my own.
By the time I knew N8n existed, I had already automated all of the ops in one of my projects.
I feel like having something of our the box for connectors could be useful but also as a discovery exercise, maybe part of your service could be to introduce new endpoints that customers previously had not considered (i.e. why not use X instead of Y).