Redundant knowledge, brittle handoffs
Everyone is quietly building a personal KB with the same meeting transcripts. Sharing between agents turns into export → copy → paste → Slack. The seams between teammates are where AI value leaks out.
If you're already running serious personal AI workflows, you can feel exactly where the team layer breaks — we want to build this with you.
You have a personal setup that actually works — custom prompts, agents, maybe a few tools wired together. But when your output lands in shared spaces, something is lost. Context doesn't carry. Decisions don't stick. You find yourself re-explaining things that should already be known.You've probably tried to fix this with Notion, Slack, a shared knowledge base. None of it held.
If that sounds familiar, we built Heddle for you.
Everyone is quietly building a personal KB with the same meeting transcripts. Sharing between agents turns into export → copy → paste → Slack. The seams between teammates are where AI value leaks out.
A decision gets made, and now the PM has to schedule four meetings so everyone actually hears it. Engineers execute against stale intent docs. Yesterday's tasks don't match today's product direction.
Systems of record capture what happened. Copilots retrieve fragments. Neither preserves the why. As agents start acting on behalf of people, stale or low-authority context becomes a system-level reliability problem.
These aren't tool problems. They're structural — and no copilot or knowledge base was built to solve them. That's what Heddle is for.
Heddle sits underneath the tools your team already uses. When decisions get made — in meetings, in Slack, in 1:1s — Heddle structures them, links them to their source, and keeps them live. Agents read from it. Teammates read from it. When something changes, that change is made everywhere, without losing context.
You don't migrate to Heddle. It integrates into Linear, Notion, Slack, Figma, GitHub. The tools stay. The disagreements between them stop.
Heddle gives your team’s AI a shared memory, so decisions, context, and intent don’t disappear between tools.
New material lands in your Studio vault. The agent scans it, classifies what's a new decision versus a status change versus supersession, and stages candidates — each linked back to the exact source with deep-link evidence.
A weekly review packet goes to a human. You approve, hold, or keep it project-local. Only then does it merge into the canonical log. Durable memory, preserved evidence, no autonomous drift.