Meet Orbia
Stop losing product context.
See how Orbia connects customer evidence, product decisions, and engineering execution in one workflow.
Works with the tools you already use.
Turn company knowledge into product decisions.
Lost context
Customer calls, product usage data, support tickets, engineering decisions, and product strategies stay in separate silos; decisions are made with incomplete context because the relationships between them aren't established.
From evidence to decision
All this scattered data is automatically clustered; it turns into prioritized opportunities and decisions approved by PMs.
No decision memory
Teams can't find why a decision made three months ago was made. The same discussion repeats with the same mistakes.
From decision to implementation
The same memory carries the "why is this needed" context to coding agents in a technical format, completely.
AI agents need context
You need to give coding agents not just what to do, but the context of "why is this needed, what has been tried before."
From outcome to learning
Every decision shipped to production is compared with actual results. The system learns which decisions worked.
Solution
Orbia generates an implementation-ready spec from validated evidence and product decisions. Each spec includes objectives, scope, acceptance criteria, historical technical decisions, and implementation context. Missing scenarios are highlighted with a readiness score, allowing PMs to review and approve before sending it directly to Claude Code or Cursor via MCP.
Closed-Loop
Evidence Flow
Slack, support, and call signals are automatically clustered and gathered into one flow — nothing gets lost.
Approval Screen
The LLM suggests a relationship, you approve with one click — the approved relationship is permanently written to memory.
Memory Explorer
Ask "Why did we make this decision?" — it comes with the source Slack thread, PR, and reasoning chain.
Prioritization
A prioritized list backed by RICE score and source evidence count.
Spec Approval
Highlights missing scenarios with a readiness score; approved specs are sent directly to the agent.
Outcome Tracking
Predicted impact is compared with actual results; learnings are fed back into memory.
The Orbia Difference
Cursor and Claude Code can now connect — to Slack, GitHub, Jira. But they ask from scratch every time. Orbia doesn't ask; it remembers.
Coding Agents
Temporary memory, shallow context
Agents work with momentary context windows. They scan data temporarily but can't build a permanent structure; when the session ends, the context is lost.
Orbia
Enterprise memory that never forgets
Every validated relationship is written into a permanent knowledge graph. You never have to explain the same context to AI again.
Bring everything into one Orbit
Orbia Platform
Agent-ready Artifacts
Dev-ready spec
Go from idea to implementation in minutes. Scope, user stories, acceptance criteria, edge cases, dependencies, and success metrics—generated from real product context.
Engineering ticket
A ticket that's ready to assign. Priority, labels, acceptance criteria, linked evidence, and implementation context. Import directly into Linear.
Decision record
What was decided, what was considered, and why. Keeps the team aligned as the product and context grow.
FAQ
Stop losing product context.
See how Orbia connects customer evidence, product decisions, and engineering execution in one workflow.
Get a Live Demo