Twelve signals. One model. Complete memory intelligence.
Rabbit handles the entire memory lifecycle for your organization. From understanding what you're asking, to extracting structured facts, to detecting contradictions across months of data, to giving you cited answers grounded in what actually happened.
Every signal runs on the same architecture. No chaining multiple APIs. No sending data to different providers. One model, trained for one purpose, running on infrastructure you control.
Everything an organization needs to remember
Each signal is a specialized capability trained into the same model. One API call, one architecture, twelve different ways to process organizational knowledge.
Understand
Classifies natural language queries into precise intents so every question gets the right retrieval strategy. Factual, temporal, synthesis, entity, aggregation, actions, or history.
[INTENT]Extract
Pulls people, organizations, decisions, action items, dates, and topics from any text. Meetings, emails, Slack threads, notes. Structured JSON output every time.
[EXTRACT]Organize
Auto-triages incoming information into types (meeting, decision, task, insight) with summaries and tags. The first layer of turning noise into knowledge.
[TRIAGE]Link
Detects relationships between memories across 7 types: follows up, contradicts, supports, expands, references, supersedes, and relates to. Builds the knowledge graph automatically.
[LINK]Reason
Multi-hop reasoning across thousands of memories. Chains lookups, resolves references, and connects dots that span different conversations, people, and timeframes.
[EXPAND]Compile
Builds and maintains living knowledge pages for entities and topics. When new information arrives, existing pages update automatically. Knowledge compounds over time.
[COMPILE]Recall
Conversational answers grounded in your actual data, with numbered source citations. Not hallucinations. Verified facts from your organization's real history.
[ANSWER]Ambient
Surfaces forgotten commitments, contradictions, and stale information without being asked. Proactive intelligence that catches what humans miss.
[AMBIENT]Multi-turn
Maintains conversation context across follow-up questions. "Tell me more about that" and "what about the budget?" work naturally without repeating context.
[MULTITURN]Summarize
Generates concise summaries of long content while preserving every decision, name, and action item. No lossy compression. Every important detail survives.
[SUMMARIZE]Sentiment
Detects emotional tone in organizational communications. Understands whether a meeting was tense, a decision was contentious, or feedback was positive.
[SENTIMENT]Graceful Uncertainty
When the answer is not in the data, Rabbit says so clearly instead of making something up. Trained explicitly to distinguish "I found nothing" from "I'm guessing."
[DONTKNOW]From scattered information to structured knowledge
One pipeline. No external dependencies. Your data stays inside your infrastructure from input to output.
Raw Input
Meetings, emails, Slack, notes
Rabbit
Extract, classify, link, compile
Knowledge Graph
Entities, relationships, timelines
Instant Recall
Cited answers from real data
See Rabbit in action
Paste any text and watch Rabbit extract structured knowledge in real time.
Simple. Powerful. OpenAI-compatible.
Standard REST API with streaming support. Drop in as your memory layer.
{
"text": "Met with Sarah from Acme on Tuesday.
Budget confirmed at $45,000."
}
// Response
{
"people": ["Sarah"],
"organizations": ["Acme"],
"decisions": [
"Budget confirmed at $45,000"
],
"action_items": [{
"owner": "Sarah",
"task": "Send contract"
}]
}
{
"question": "What did we decide about
the Q2 launch?",
"context": [...memories]
}
// Response
{
"answer": "The Q2 launch was confirmed
for April 22 with a $45,000 budget
from Acme [1]. Sarah Chen is
sending the signed contract [1].",
"sources": [1],
"confidence": 0.96
}
General-purpose AI vs. memory intelligence
| Capability | Rabbit | General LLMs (GPT, Claude) | RAG Systems |
|---|---|---|---|
| Entity extraction from org data | Specialized, 92% F1 | Generic, lower precision | Not included |
| Relationship detection | 7 link types, automatic | Not available | Not available |
| Contradiction detection | Built-in signal | Not available | Not available |
| Knowledge compilation | Auto-updating pages | Re-derives every query | Re-derives every query |
| On-premise deployment | Full support | API only | Depends on stack |
| Per-token cost | $0 (fixed infra) | $0.15-15 per 1M tokens | Depends on LLM used |
| Data sovereignty | Your infrastructure | Third-party servers | Depends on LLM used |
Ready to give your organization a memory?
Get API access or talk to us about on-premise deployment.