Connect your agents.
OpenClaw, custom LangChain setups, or raw API calls — d33pmemory integrates effortlessly as your central memory layer.
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Every conversation becomes structured knowledge.
How it works
Clear Architecture
Always Evolving
Clear Architecture
Always Evolving
d33pmemory's proprietary extraction pipeline transforms raw dialogue into a multi-layered knowledge architecture. Our confidence-scored model distinguishes between verified facts and probabilistic inferences — creating an ever-evolving cognitive profile that gets smarter with every interaction.
Extract structured memories.
Our engine normalizes every conversation, identifying facts, relationships, and preferences, resolving conflicts automatically.
Retrieve and compile context.
Pull exactly what your agent needs to know right before answering, minimizing tokens while maximizing context.
Extraction pipeline
Raw dialogue passes through our extraction engine that distills conversations into structured knowledge — facts, relationships, events, preferences, and behavioral patterns.
Step 01
Entity resolution
Disambiguate identities and concepts across fragmented conversations using multi-vector similarity.
Step 02
Knowledge extraction
Identify facts, relationships, events, preferences, and patterns. Each tagged as stated or inferred.
Step 03
Confidence scoring
Every memory gets a certainty score (0.0–1.0) with full provenance — which interaction, when, what was said.
Step 04
Context compilation
When an agent needs context, assemble the exact memories that matter — packed into a token budget.
Memory object payload
{
"type": "fact",
"content": "User follows a gluten-free diet",
"source": "stated",
"confidence": 0.95,
"category": "health/dietary",
"tags": ["gluten-free", "dietary"],
"scope": "shared",
"contributed_by": "slack-bot"
}Five types of knowledge
Our extraction engine categorizes every piece of knowledge, each with confidence and provenance.
Type 01Fact
"User follows a gluten-free diet"
Conf0.95
Sourcestated
Type 02Relationship
"Emma is a frequent dining companion"
Conf0.88
Sourceinferred
Type 03Event
"Dinner booked at Trattoria for Feb 15"
Conf0.92
Sourcestated
Type 04Preference
"Prefers Italian restaurants"
Conf0.74
Sourceinferred
Type 05Pattern
"Books restaurants for 2 on weekends"
Conf0.68
Sourceinferred
Core capabilities
Multi-layer Model
Cognitive Engine
Episodic, semantic, and procedural memory layers — mirroring how humans actually organize knowledge.
Confidence Engine
Scoring System
Every memory has a certainty score (0.0–1.0) that evolves as evidence accumulates. Stated vs inferred is always clear.
Auto-Consolidation
Memory Graph
Corroborated memories strengthen. Stale ones decay. Contradictions resolve through our consolidation engine.
Semantic Recall
Retrieval API
Search by meaning, not keywords. Describe what you need and get the most relevant memories ranked by similarity.
Context Compiler
Prompt Optimizer
Don't dump old messages. Compile the exact memories that matter — 142 tokens replacing 15,000.
Evidence Chains
Provenance Tracker
Every fact has a provenance trail — which interaction, when, and whether it was stated or inferred.
Beyond vector search
Standard RAG systems fall apart when managing real user profiles.
Standard RAG
Linear token growth
Ephemeral retention
No contradiction handling
Context = message dump
No confidence or provenance
Current
d33pmemory
99% context compression
Persistent evolving memory
Auto conflict resolution
Compiled context payloads
Confidence + evidence chains
Trusted by top AI engineering teams.
Don't just take our word for it.
"We cut our agent's context window usage by 94%. d33pmemory just works — two API calls and our assistant remembers everything."
Marcus T.
AI Engineer
"Replaced our entire RAG pipeline in an afternoon. The confidence scoring alone is worth it — we finally know what the agent is sure about vs guessing."
Priya S.
Backend Lead
"The conflict detection is the killer feature. When a user updates their preferences, old memories get flagged. No more stale data poisoning responses."
Lena K.
ML Researcher