Persistent, searchable memory for autonomous AI agents. Semantic retrieval replaces brute-force context loading — so your agent scales without burning tokens.
// HOW IT WORKS
From connection to comprehension in minutes — not days.
Point your agent at our API with a single config line. Works with OpenClaw, custom agents, and any LLM framework.
Your agent stores observations, facts, and session notes automatically. We extract structured data and generate embeddings at full resolution.
Three-tier retrieval — handoff notes, recency-boosted recall, and deep semantic search — surfaces exactly what matters for the current context.
Browse, search, and edit your agent's memories through a visual UI. Human-readable, human-editable, always in sync.
Agent Graph Explorer
Every task, skill, document, and preference your agent has learned — visualized as an interactive knowledge graph.
Getting Started
No coding required. Hand your agent a prompt and it connects itself. Developers can also use the API directly.
Create a free account. During onboarding, StateLayer generates a connection package — a set of instructions tailored to your agent platform.
Copy the connection package and paste it into your agent's chat, drop it as a file, or text it — however you normally communicate.
From that point on, your agent writes memories after each session and recalls them at the start of the next. Context carries forward.
Memory Storage
Browse episodes, facts, decisions, and handoff notes. Search across all memories instantly. Your agent's complete knowledge base at a glance.
// FEATURES
Built for developers who want their agents to learn, retain, and recall — without managing infrastructure.
No databases to provision, no embeddings to manage. Connect your agent and it just works. We handle storage, indexing, and retrieval.
Every memory is stored as plain text you can read, understand, and edit. No opaque vector blobs — just clean, structured knowledge.
A visual interface to browse, search, and manage your agent's memories. See what your agent knows, edit what it remembers, delete what it shouldn't.
One account, multiple agents, fully isolated memory per agent. Scale from a single assistant to an entire fleet without cross-contamination.
Handoff notes for session continuity, recency-boosted search for recent context, and deep semantic recall for long-term knowledge. The right memory at the right time.
When a session ends, your agent writes a structured summary of where things stand. The next session picks up exactly where it left off — no context lost.
Our LLM pipeline extracts structured facts, preferences, and decisions from raw conversation. Your agent builds knowledge without manual curation.
// PRICING
All memories stored at full resolution. Memory Explorer included on every plan. Upgrade and search quality improves instantly — zero re-processing.
Get started with persistent memory at no cost.
High-resolution search and more agents for growing projects.
For teams running multi-agent systems at scale.
OPENCLAW + NEMOCLAW INTEGRATION
Our installer scans your OpenClaw workspace, uploads existing memories, configures semantic search as a tool, and sets up automatic memory sync. Your agent gains persistent, searchable memory without changing how it works.
Works with the tools you already use
OpenClaw Integration
Memory like a lobster — it never forgets
StateLayer was built for the OpenClaw ecosystem. The installer hooks directly into your workspace — scanning your files, configuring HEARTBEAT.md for scheduled syncs, and adding a memory-search tool so your agent can query its own history. No manual config. No YAML files. Just run the command and go.