Industry · Software & SaaS
Each agent carries with it what the team already decided.
Architecture decisions, support feedback, and onboarding that starts from accumulated context, delivered to Claude Code, Cursor, Codex, and Devin via MCP.
Scenario
How context circulates when ValorBrain is in the flow.
- 01
Claude Code closes the architecture discussion and the decision-extractor records the decision with its source (ADR, PR) and owner.
- 02
The next day, Cursor receives the current standard via context-surfacing, right at question time.
- 03
Nobody re-explains: the new endpoint already ships in line with the ADR, consistent across agents.
- 04
Support records the exception granted to the customer, with source and who approved it.
- 05
In the roadmap discussion, the agent retrieves the cases behind the request, not just the request.
- 06
The decision to prioritize (or not) gets recorded, and the next discussion starts from it.
- 07
The engineer joining, or the new agent, receives what changed since the last session.
- 08
The handoff-generator routes pending work with the permissions inherited from whoever opened the task.
- 09
The team's accumulated context becomes a starting point, not archaeology material.
Related departments
Frequently asked questions
We already store ADRs in the repository.
Good: they become source, not archive. ValorBrain cross-references the ADR with the sessions that produced it and the PRs that applied it, and delivers the current version when an agent asks.
Isn't this just RAG?
RAG answers a question. ValorBrain maintains decision, permission, version, and handoff between agents, and flags when an answer has aged because the rule changed.
What if the memory goes stale?
Every unit has validity (as_of) and supersession. The current rule arrives before the old one; conflict and drift become flags for human review. We don't promise infallibility; we promise traceability.
What proof is there that retrieval works?
Internal benchmarks: LoCoMo R@10 of 96.58% (1986 questions, +2.1 points over the published open-source leader) and an average of 75.5% (binary 80.8%) on BEAM-100K, with reader, judge, and effort stated in the methodology. These are internal retrieval benchmarks; not peer-reviewed and not end-to-end QA. The everyday proof is simpler: a cited source in every answer and an auditable read.
Next step
Less starting over. More continuity
Bring a real project. In one conversation we map where context gets lost between the people and agents on your team, and where to start.