Rumi handles
the hustle.
Your organization is constantly producing new information. Agents discover things. Documents change. Projects evolve. Decisions are made. APIs send updates. People correct earlier assumptions. Rumi works through that incoming stream and helps turn it into organized, reusable memory.
See Rumi in ActionSix steps from
noise to knowledge
Rumi is not a general purpose chatbot. Rumi's responsibility is to help process incoming information into usable memory. Each step is deterministic, auditable, and configurable.
Understand
Rumi examines incoming information and identifies what it is about. Entity extraction, topic classification, and intent recognition happen at ingest time.
Summarize
Important context can be condensed into useful memory without losing the original source. Configurable summary lengths preserve fidelity for critical details.
Categorize
Rumi helps organize knowledge into meaningful categories and metadata. Automatic tagging, namespace assignment, and taxonomy alignment.
Connect
Related memories can be associated so future Recall is not limited to exact words. Semantic similarity, entity co-occurrence, and temporal proximity create graph edges.
Prepare
Information is prepared for semantic retrieval and future use by connected systems. Embedding generation, index updates, and cache warming happen automatically.
Organize
The Stash becomes more than stored content. It becomes an organized memory layer with lifecycle governance, decay scheduling, and audit trails.
Rumi works in the background so your people and AI systems do not have to become memory librarians.
Rumi does not replace your AI tools. Rumi helps them remember.
Multi-probe validation
at every write
Every memory entering Recall Racoon passes through Rumi's probe pipeline. Probes are configurable per namespace and can be extended with custom validators.
🔍Format Probe
Validates structure against expected schemas. JSON, Markdown, YAML, and custom formats. Rejects malformed input before it enters the pipeline.
🔍Citation Probe
Verifies source attribution. Every claim must reference a document, ticket, commit, or API response. Configurable minimum citation count per namespace.
🔍Semantic Probe
Checks for semantic coherence. Detects hallucinations, contradictions, and low-confidence extractions using local embedding comparison.
🔍Contradiction Probe
Compares new claims against existing Stash. Semantic similarity threshold (default 0.85) triggers conflict detection. 5-tier auto-resolution: supersede, merge, flag, archive, or reject.
🔍Decay Probe
Time-based confidence decay. Configurable half-life per namespace. Stale claims (confidence < 0.80, age > 90 days) flagged for review or auto-archive.
Claim lifecycle
governance
Every memory is a lifecycle-managed claim. State transitions are explicit, auditable, and governed by policy—not probabilistic drift.
| State | Description | Transition Triggers | Recall Eligible |
|---|---|---|---|
| candidate | Newly ingested, awaiting probe validation | Ingestion complete | No |
| confirmed | Passed all probes, active in Stash | All probes pass | Yes |
| stale | Confidence decayed below threshold | Decay probe, age > 90d | Flagged |
| superseded | Replaced by higher-confidence claim | New evidence, contradiction resolution | No (ref only) |
| conflicted | Semantic contradiction detected | Contradiction probe, similarity > 0.85 | No |
| archived | Retained for audit, excluded from Recall | Manual, policy, or age-based | No |