Trusted AI systems for decision-heavy organizations.
Our first product is Decision Memory — a workspace that helps people preserve the context behind important decisions: what was decided, why it was decided, what evidence supported it, who owned it, what actions followed, and how the decision changed over time.
Important decisions rarely live in one place.
They start in meetings, continue in Slack or Teams, move into Jira, Notion, Confluence, Google Docs, email threads, and architecture reviews. Months later, people remember that something was decided — but not the rationale, evidence, owner, tradeoffs, or later changes.
That is the gap AuzzurA is focused on: helping organizations preserve trusted decision context before it disappears into fragmented knowledge.
Decision Memory
Decision Memory is not a meeting summarizer, task board, or generic AI chatbot.
Meetings, chats, tickets, and documents are evidence. The durable object is the approved decision record — with rationale, evidence, ownership, follow-through, outcomes, and lineage.
AI helps surface candidate decisions from selected evidence. Humans review and approve what becomes trusted memory. Approved decisions can then be searched, revisited, compared with later decisions, and recalled through Ask DM.
Decision memory should be trusted, useful, and human.
Human-approved
AI can propose, but important organizational memory should not be created silently.
Evidence-backed
A decision should stay connected to the context that made it trustworthy.
Policy-aware
Sensitive evidence, access boundaries, and workspace context matter.
Useful for people and AI tools
As work becomes more AI-assisted, organizations need trusted decision context that people, copilots, and future AI systems can safely reuse.
Focused on the why, not only the what
A task tells you what to do. A transcript tells you what was said. Decision Memory preserves what was decided and why.
Decision Memory is in private pilot.
We are looking for design partners who regularly lose decision context across meetings, documents, tickets, chats, and stakeholder groups — especially in product, engineering, architecture, platform, AI, and cross-functional decision workflows.
If this problem is familiar, we would be happy to compare notes.