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Spectron: AI agent memory that actually works

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The context layer
for AI agents

The database where storage, context, and memory are one transaction.

01 |THE PROBLEM → THE FIX

Agents fail due to context. Not models.

Your model can reason. It just has nothing reliable to reason over. Each failure below has a structural fix - built into the engine.

Context that leaks at every seam

Data flows between six systems. Relationships, history, and metadata fragment at every boundary, silently.

App state

User session

Vector DB

Embeddings

Graph DB

Relations

Doc store

Documents

Auth

Identity

Data fragments at every system boundary

Writes that half-succeed

Memory updates in one system, state fails in another. Without unified transactions, partial writes corrupt context.

Single transaction

Vector DB

Write embedding

Graph DB

Write relation

committed

inconsistent state

rolled back

Latency that compounds

Every system adds a network hop. Round trips stack under load until agents miss their response window.

Agent

Vector DB

Graph DB

Doc store

Auth

Total

Cumulative latency

Six systems to keep alive

Six failure modes, six monitoring setups, six sets of credentials. The glue code becomes the product.

Vector DB

Similarity search

auth

config

monitor

Graph DB

Relationship store

auth

config

monitor

Doc store

Raw document index

auth

config

monitor

Auth service

Identity & tokens

auth

config

monitor

Cache layer

Hot key store

auth

config

monitor

Five systems. Five auth configs. Five things to scale, secure, and keep alive.

02 |THE PLATFORM

Build and run agents on the context layer

Object storage to agent memory. One transaction boundary. One permission model. One deployment.

SPECTRON

Memory

Your agents remember users, accumulate preferences, and reason over history - no separate memory layer needed.

Explore Spectron

Spectron: persistent agent memory built on SurrealDB

SURREALDB

Context

The multi-model database where documents, graphs, vectors, time-series, full-text, and relational live in one ACID transaction. One query gives the agent everything it needs to reason.

Explore SurrealDB

SurrealDB: multi-model database for documents, graphs, vectors, and time-series

SURREALDS

SurrealDS

Distributed database storage with quorum consensus. Compute-storage separation, object storage, and elastic scale beneath the context layer.

Explore SurrealDS

Distributed storage with quorum consensus, the foundation of the SurrealDB platform

03 |MULTI-MODEL

Six databases become one

Put an end to stitching databases together. SurrealDB unifies your entire context layer in a single multi-model engine - one query language, one transaction, one deployment.

Before - Multiple databases

Client
0ms
Your application
6 SDKs · 6 drivers · 6 connection pools

Vector
database

Proprietary API

Full-text search
database

Search DSL

Time-series
database

InfluxQL / Flux

Document
database

SQL / MQL

Graph
database

Cypher / Gremlin

Relational
database

SQL

Eventual consistency only

After - SurrealDB

Client
0ms
Your application
1 SDK · 1 driver · 1 connection pool
SurrealDB
SurrealDB

SurrealQL

Vectors
Full-text
Time-series
Documents
Graphs
Relational
Single ACID transactionStrong consistency

THE ARCHITECTURE

One stack. Four layers. Every layer under one roof.

Spectron gives agents persistent memory. SurrealDB unifies every data model in one ACID transaction. The storage engine separates compute from storage on commodity object storage.

Applications
Spectron
Spectron
Memory
Entity extraction
Knowledge graph
Temporal facts
Hybrid retrieval
SurrealDB
SurrealDB
Context
Documents
Graphs
Vectors
Time-series
Auth
APIs
SurrealDS
Storage
Storage
Quorum consensus
Compute-storage sep.
Scale to zero
Object storage (S3 / GCS / Azure Blob)

04 |HOW IT WORKS

The read-think-write loop

Every agent turn resolves in one ACID transaction. No stale reads, no partial writes, no glue code.

READ

Graph traversal, vector search, and temporal facts - one SurrealQL statement, one round trip.

SurrealQL

Multi-model query

Graph

Vector

Temporal

Unified result set

THINK

Documents, relationships, embeddings, and history arrive together. The agent reasons over complete context.

Result set

Multi-model query output

Documents

Relations

Vectors

History

Complete context

WRITE

Persist decisions, update entities, trigger events - one ACID transaction, no partial writes.

BEGIN TRANSACTION

ACID transaction boundary

Update

Create

Trigger

COMMITTED

SURREALQL

One query. Every model.

Graph traversals, vector search, transactions, and access control in one expressive language. Explore real-world query patterns across search, graphs, agents, and more.

Multi-model query

ACID transactions

Built-in auth

Hybrid RAG

Graph RAG

Context expansion

Knowledge graphs

Agent memory

Conversational memory

Live queries

Recommendations

Geospatial queries

Event-driven automation

Multi-model query

Graph, vector, and temporal data in one round trip

-- Combine graph traversal, vector similarity, and temporal
-- filtering into a single round trip. No ORMs, no joins,
-- no glue code between datastores.

LET $vec = fn::embed("running shoes");

SELECT
->purchased->product AS history,
->reviewed->product[WHERE
vector::similarity::cosine(
embedding, $vec
) > 0.8
] AS relevant,
->prefs[WHERE valid_at <= time::now()] AS prefs
FROM ONLY $user;

SPECTRON

Memory in the database, not above it

Spectron is the first agent memory system with ACID transactions across all data models. Entity extraction, knowledge graphs, temporal facts, and hybrid retrieval, built into SurrealDB, not bolted on top.

SPECTRON

Memory in the database, not above it

Spectron is the first agent memory system with ACID transactions across all data models. Entity extraction, knowledge graphs, temporal facts, and hybrid retrieval, built into SurrealDB, not bolted on top.

PROVEN IN PRODUCTION

In production at
Samsung, Verizon,
Tencent & PolyAI.

Teams are building on the context layer across industries. Here's what they've shipped.

TRUSTED BY THE BEST

The SurrealDB integration was seamless and delivered performance on par with our internal stack. It proves that enterprises can bring their own knowledge base without sacrificing speed, quality, or control.

Colman Yau

VP of Engineering, PolyAI

SurrealDB is enabling the next phase of our product. It gives us the flexibility and graph-native capabilities we need to keep innovating for customers at every size and industry.

Or Weis

CEO & Co-founder, Permit.io

We replaced 5 backend tools with SurrealDB and scaled to 700,000 users in 8 hours.

Lucy Egan

Aspire

SurrealDB fast tracked our progress with all its features. Graph links + Record links + Full text search + Vector embeddings and Vector search + Surreal WASM for offline-ability... just name it!

Sigismond

Community developer

I'm certainly enjoying that I can replace hundreds of lines of Postgres trigger and function code with a dozen characters in a DEFINE statement in SurrealDB.

Trevor Parscal

Community developer

SurrealDB has allowed our team to focus more on product and iteration without worrying about database constraints. We can do literally everything we need in SurrealDB.

Albert Marashi

Community developer

So much easier to write advanced queries compared to SQL. Queries are actually readable! Community on Discord is also very helpful and includes SurrealDB developers.

@BeniaminDudek

Community developer

USE CASES

From agents to real-time apps

Context-aware agents, persistent memory, knowledge graphs, and real-time collaboration - see what teams are building on the context layer.

AI AGENTS

Unified context, memory, and knowledge graphs for agents that reason - not just retrieve.

AGENT MEMORY

Persistent, structured memory - working, semantic, episodic, and procedural - for agents that remember.

KNOWLEDGE GRAPHS

Model rich relationships and dependencies. Traverse connections, rank entities, and retrieve structured context - one query, one round trip.

REAL-TIME APPLICATIONS

Live queries push changes to subscribers as they commit. No polling, no message broker, no stale reads.

FREQUENTLY ASKED QUESTIONS

Learn more about the context layer

THE COMMUNITY

Building the future together

Join a growing community of developers, engineers, and teams building the next generation of intelligent applications on SurrealDB.

Stay in the loop

Product announcements, technical deep dives, AI agent recipes, and event invites - in your inbox every two weeks.

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Verizon IndyCar racing teamTencent headquarters buildingSamsung headquarters building
Apple retail store
BYD headquarters building
Verizon IndyCar racing teamTencent headquarters buildingSamsung headquarters building
Apple retail store
BYD headquarters building
Verizon IndyCar racing teamTencent headquarters buildingSamsung headquarters building
Apple retail store
BYD headquarters building

GET STARTED

Start building with
the context layer

Object storage to agent memory. A single stack, a single transaction, zero glue code.

SurrealDB

The context layer for AI agents.

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

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