Purpose-Built Memory Database
Agent memory, built in.
Not bolted on.

Areev is a purpose-built memory database. Importance scoring, temporal reasoning, biological decay, and cryptographic erasure are native to the engine — not assembled from separate systems. Memory that compounds.

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Native to the Engine

Five primitives. One engine.

These capabilities don't exist in any existing database. Areev was built around them — not on top of them.

Importance Scoring

Vector DBs rank by similarity. Caches don't rank at all. Neither understands that some memories matter more than others.

→ Not in Pinecone, Weaviate, Redis

Temporal Reasoning

When something happened changes what it means. No existing database can answer "what did the user believe about X, as of Tuesday?"

→ Not in Postgres, Elasticsearch, Qdrant

Biological Decay

Memories that aren't reinforced should fade. No database has a native forgetting curve — you'd need background jobs scanning every store.

→ Not in any existing database

Cryptographic Erasure

"Delete user X" means scanning five systems and hoping you got everything. Or rotate one key and it's gone. O(1).

→ Not in any existing database

Atomic Transactions

A memory write needs to store the fact, its embedding, its timestamp, and its importance score atomically. With assembled parts, any can fail independently.

→ Impossible across 5 separate systems

From raw logs to durable knowledge.

Three stages transform noisy agent interactions into structured, searchable, deletable memory grains.

Stage 01 — Ingestion

Observe

Raw events — tool calls, LLM outputs, user messages — enter the observation buffer. Nothing is stored permanently yet.

Stage 02 — Synthesis

Distil

The importance scorer evaluates signal density. High-value observations are synthesized into typed grains. Low-signal events decay.

Stage 03 — Recall

Retrieve

Agents query by semantic similarity (HNSW), keyword (BM25), or graph (Hexastore). RRF fusion combines all three.

The atoms of agent knowledge.

Instead of replaying raw transcripts, Areev stores semantic grains — the compressed, typed residue of every meaningful interaction. 10 grain types cover the full cognitive surface.

BeliefWhat the agent knows as true
0x01
EventTime-stamped occurrences
0x02
StateSession and entity snapshots
0x03
WorkflowMulti-step procedural memory
0x04
ActionCompleted operations and tool calls
0x05
ObservationRaw sensory inputs
0x06
GoalObjectives and pursuit targets
0x07
ReasoningChain-of-thought traces
0x08
ConsensusMulti-agent shared beliefs
0x09
ConsentUser permission records
0x0A
Cryptographic Erasure O(1)

Forgetting is a feature.

When a deletion request arrives, Areev rotates the cryptographic key that wraps the target grain. The data becomes permanently unreadable in O(1) time — no scans, no scrubs, no latency. 90+ automated compliance checks across 7 regulations.

GDPR HIPAA EU AI Act SOC 2 CCPA
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Build agents that think with clarity.

The human mind, as a primitive. Starting now.

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