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Agent memory that persists, structures, and connects

Working memory, semantic memory, episodic memory, procedural memory, preference memory, and shared memory - all structured, all queryable, all in one transactional system.

MEMORY TYPES

Six types of memory for agents

Human cognition uses multiple memory systems. Agents benefit from the same separation. Spectron maps each to structured storage with graph relationships and temporal awareness: working memory for active session context, semantic memory for facts and knowledge graphs, episodic memory for past interactions and outcomes, procedural memory for learned patterns and workflows, preference memory for user personalisation, and shared memory for multi-agent coordination.

AUTONOMOUS UNDERSTANDING

Memory that keeps thinking

Most memory systems are passive. They store what agents tell them and retrieve what agents ask for. Spectron's memory is active - background processes autonomously discover connections between entities, consolidate fragmented knowledge, and infer relationships that no single conversation could reveal.

Connection discovery

Relationships between entities mentioned in separate conversations are discovered automatically as context accumulates.

Knowledge consolidation

Fragmented facts from dozens of interactions merge into coherent entity profiles. Understanding becomes structured over time.

Implicit inference

New facts are derived from the graph without being explicitly stated. The knowledge graph grows richer than the sum of its inputs.

THE PROBLEM

The fragmented memory tax

Memory middleware like Mem0 layers a memory API on top of external databases - a vector store here, a key-value store there, maybe a graph database for relationships. Every layer adds latency, failure modes, and consistency gaps.

Consistency gaps

Memory in one store, state in another. No unified transactions means no guarantees that memory and data stay in sync.

Latency compounds

Each system adds a network hop. Memory retrieval that should take milliseconds takes tens of milliseconds across systems.

Operational burden

Three to five systems to deploy, monitor, back up, and secure. Each one is a potential failure point.

No unified permissions

Different permission models for memory, vectors, and structured data. Security policies cannot be applied consistently.

THE SOLUTION

Atomic context with Spectron

Spectron runs on SurrealDB. Memory, knowledge graphs, vectors, and structured data share the same ACID transaction boundary. No middleware, no glue code, no consistency gaps.

One transaction

Memory writes and data updates happen in the same ACID transaction. Partial writes are impossible.

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One permission model

RBAC and record-level permissions apply to memory and data identically. One security policy, consistently enforced.

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One query language

SurrealQL queries memory, graphs, vectors, and structured data together. No stitching results from multiple systems.

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One deployment

Deploy SurrealDB + Spectron as a single system. Self-hosted, embedded, or fully managed in the cloud.

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FREQUENTLY ASKED QUESTIONS

Agent memory

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Give your agents memory

Structured memory for AI agents - working, semantic, episodic, procedural, preference, and shared memory types.

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The context layer for AI agents.

Documents, graphs, vectors, time-series, and memory - in one transaction, one query, one deployment.

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