AI INTEGRATION SPECIALISTS
Agent Memory Systems

Agents That Actually Remember

Persistent context across every session — recalled when it matters

An agent that forgets between sessions feels broken. We build memory that persists the right facts, preferences and context — then surfaces them at the right moment, without bloating the window or letting stale data linger.

PersistentAcross Sessions
RelevantRecall, Not Dump
GovernedDecay & Privacy
OwnedOn Your Infra
The Problem

Stateless Agents Feel Broken

Without memory, every conversation starts from zero. But naive memory is worse — dumping everything into the prompt is slow, expensive, and quietly poisons answers with stale context.

⚠️ The two failure modes

  • No memory — users repeat themselves and preferences never stick
  • Everything in the prompt — slow, costly, and full of irrelevant noise
  • Stale facts never expire, so the agent acts on outdated truth
  • No structure — memories can't be edited, audited, or deleted on request

✦ A real memory architecture

  • Durable store for facts, preferences and history — survives every session
  • Relevance-ranked recall that surfaces only what this turn needs
  • Decay and confidence so old or weak memories fade instead of misleading
  • Editable, auditable, deletable — governance built in from day one
Capabilities

What We Build

A complete memory layer — storage, retrieval and governance — wired into your existing agents.

🧠

Long-Term Memory

Durable storage of facts, preferences and outcomes that persists across sessions, users and devices — the agent's lasting knowledge, not a transcript it forgets.

VectorsStructuredPer-userDurablePortable
🎯

Relevant Recall

Semantic and structured retrieval that surfaces only the memories this turn actually needs — never the whole history.

Decay & Confidence

Scoring, aging and consolidation so fresh, reinforced facts win and stale, low-confidence ones fade out.

🗃️

Working Memory

In-session scratchpad and summarization that keeps long conversations coherent without blowing the context window.

🔐

Governance & Privacy

Per-user isolation, audit trails and the ability to view, edit or delete any memory — built for compliance.

🔌

Integration

Wired into your stack via MCP or a clean API, so existing agents gain memory without a rewrite.

The Build

From Forgetful to Persistent

We design the memory model around what your agent actually needs to remember — then build, tune and hand it over.

1

Model

Define what's worth remembering, for how long, and at what scope.

2

Store

Stand up the durable store and schema — vectors plus structured data.

3

Recall

Build relevance-ranked retrieval that injects only what each turn needs.

4

Govern

Add decay, confidence, isolation and the edit/delete controls.

5

Tune

Measure recall quality against real sessions and hand it over.

Tooling

The Stack

Open, portable building blocks — no proprietary memory black box you can't inspect or move.

PostgreSQLpgvectorRedisEmbeddingsQdrantSemanticClaudeMCPDecayConfidenceDockerAPIs PostgreSQLpgvectorRedisEmbeddingsQdrantSemanticClaudeMCPDecayConfidenceDockerAPIs

Storage

PostgreSQLpgvectorRedisSQLite

Vectors

EmbeddingsQdrantRe-ranking

Retrieval

SemanticStructuredHybrid

Agents

ClaudeMCPTool use

Governance

DecayConfidenceIsolationAudit

Infra

DockerAPIsYour cloud
🗄️

Your Memory, On Your Infrastructure

Memory is some of the most sensitive data your agents touch. We build it on open, portable components in your own database and cloud — no proprietary memory service holding your users' context hostage. Per-user isolation, full audit trails, and one-call deletion are part of the design, not an upsell.

Give Your Agents a Memory

Tell us what your agents keep forgetting. We'll design a memory layer that remembers the right things — and forgets the ones it should.