How GUTT Works
Organizational memory that connects to your tools, captures context automatically, and gives every AI agent the knowledge they need.
What is GUTT?
GUTT captures decisions from your meetings, Slack, GitHub, and Jira—then surfaces them to Claude Code, Cursor, and Copilot via MCP. No manual documentation. No re-explaining your codebase every time you start a new chat.
When an AI agent starts a task, it queries GUTT first. It already knows your architecture, your conventions, and what was tried before. The result: code that follows your patterns, right the first time.
From Scattered Data to Shared Understanding
Your organization's knowledge is scattered across dozens of tools. GUTT collects it, connects it, and makes it queryable by both humans and AI agents.
Left: Data sources (meetings, Slack, GitHub, Jira) → Middle: Knowledge graph → Right: Shared understanding
On the left: Your data sources—meeting transcripts, Slack conversations, GitHub PRs, Jira tickets, Confluence docs. All disconnected, scattered, hard to search.
In the middle: GUTT ingests this data and builds a knowledge graph. Not just storing documents—understanding relationships. Who made which decisions? Why? What lessons were learned? Who knows what?
On the right: Shared understanding. Your AI agents and team members query the same brain. They get context before they act. No more re-explaining. No more repeated mistakes.
How Development Teams Use It
Every role in your development organization—from product to engineering to leadership—both queries and contributes to the same organizational memory. See use cases.
All roles query and contribute: PM research → Developer implementation → AI context → Analysis insights → Leadership visibility
Product Manager researches a feature using Claude Desktop. Their notes, requirements, and stakeholder feedback are captured in GUTT—automatically available to developers who pick up the work later.
Developer starts implementation using Claude Code. Before writing code, the agent queries GUTT: "What patterns have we used for this? What mistakes should I avoid? Who's the expert on this system?" The answers come from your organization's actual history.
AI Agents implement with full context. They know your conventions, your architecture decisions, and the lessons from past projects. When they're corrected, that correction becomes a lesson for next time.
Scheduled Analysis runs overnight, looking for patterns across your work—repeated questions, emerging best practices, knowledge gaps. Insights surface before you think to ask for them.
Leadership stays informed without sitting in every meeting. They see trends, blockers, and team health through the knowledge that flows through GUTT naturally.
Why It Gets Smarter Over Time
Every query retrieves context. Every correction captures a lesson. Every decision adds to the graph.
GUTT isn't a static database—it's a living memory that learns from your team's work. The more you use it, the more valuable it becomes. Context compounds instead of decays.
No manual documentation. No wikis that rot. The memory builds itself.
Ready to give your AI agents context?
Watch AI generate code that already knows your standards—not hallucinated patterns.
Book a Demo