Selected system / S1
TeamOS
A context-management and retrieval system that turns operational noise into the right intelligence at the right moment.
Turns meetings, artifacts, decisions, tasks, blockers, and dependencies into structured operational memory that can be retrieved, reasoned over, and acted on.
Ingestion, work-record synthesis, triple-store persistence, reconciliation, SuperFlow-style context retrieval, and a Galaxy map interface.
IngestNormalizePersistReconcileRetrieve
Architecture
- Schema-bound work-record generation from raw operational artifacts.
- Firestore as source of truth plus OpenAI and Gemini vector stores.
- LLM arbitration for entity, task, scope, ownership, and duplicate resolution.
- Context-management and retrieval flows that assemble the right operational picture for each user turn.
- Galaxy UI for visual context and FullStar chat for grounded retrieval.
Breakthroughs
- Designed an adaptive reconciliation layer for messy operational reality.
- Separated flashy map visuals from the deeper memory pipeline underneath.
- Designed retrieval as a context operating layer, not a search box bolted onto records.
- Built around traceability, source grounding, and retryable background work.
AI layer
Multi-model synthesis, arbitration, dual retrieval, citation validation, and context assembly.
What it proves
Systems architecture, product judgment, backend orchestration, and human-in-the-loop AI governance.