The system of record that makes agent-produced documents trustworthy, versioned, and human-editable. Git-native version control, built for the speed AI writes at.
Production velocity creates a new problem: version control, lost context, and human discretion become a nightmare.
An agent rewrites 40% of a document. Was it reviewed? Can a human undo just that section — without touching the rest?
Three different agent runs each propose a rewrite. Where did the other two go? Is there a decision record, or just noise?
A human wants to strike a paragraph, reorder two sections, and route the rest back to an agent — without losing the audit trail.
Six months later, that question needs a real, retrievable answer — not a regenerated approximation that renders differently today.
Two producers, one source of truth. Agents commit at volume. Humans make targeted edits in a web studio. Both write to the same git history.
Triggered from a Slack prompt via OpenClaw, connected to arbitrary data sources, committing directly to the repository humans use.
Split-pane markdown editor with live preview, section-level strike/reorder, inline AI-rewrite requests with diff-before-commit.
Every write carries the blob SHA it was based on. Stale writes are rejected, not silently overwritten.
Rewrapping a paragraph reports zero changes. A changed key figure reports the specific before/after value. Blocks are tracked by identity, not position.
Every PDF is keyed to the exact commit that produced it. "What did we send in March" always has a real answer.
Draft → review → approved → released → superseded, with sign-off captured as commit trailers that survive clone/mirror/export.
If an author — human or agent — needs raw HTML to get an outcome, the vocabulary is missing a term. The validator hard-rejects the escape hatch. This is what keeps diffs readable and the design system enforceable at any production volume.
Get in touch to see Docgentic in action.