A tamper-evident, on-chain history for AI memory — while the memory itself never leaves your machine.
Local-first · Open source · No login required · Cloud optional
A complete cognitive architecture built to transform raw fragmented inputs into structured, intelligent context.
Granular control over AI behavior, coding styles, and specific project constraints tailored to your exact needs.
Networked memory representation where entities, files, and abstract concepts are interconnected for deep reasoning.
Multi-engine search combining precise FTS5 text matching with intelligent pgvector semantic similarity.
Automated pipelines that ingest scattered chat logs and convert them into structured, valuable memory nodes.
Seamless integration to funnel data straight from Claude Code, Cursor, Feishu, and GitHub into your central brain.
Memory is not just storage, it connects. Related decisions, projects, and people are automatically linked. You only need to ask one point, and AI will understand the full context.
Start with local mode — one command, no account. All data stays on your machine as Markdown files. Cloud is your choice, not ours.
One command: npx @awareness.market/setup. No email, no credit card, no account creation. Start in 30 seconds.
All data stored as Markdown files locally. Works fully offline. Nothing leaves your computer without your explicit consent.
The SDK is open source on GitHub. Read the code, audit it yourself, or fork it. No black boxes.
Upgrade for team sync, semantic search, and multi-device access. No lock-in — upgrade only when you're ready.
See It in Action — your AI remembers, recalls, and syncs context automatically.
AI tools are powerful — but they forget everything after each session. Other tools store memories. Awareness teaches your agent to think with them.
Unify your fragmented toolchain
Seamlessly stream data from Claude Code, Cursor, GitHub, and Slack into a single centralized memory cloud.
Distill meaning from raw logs
Automatically extract key entities, decisions, and action items from chat histories using intelligent NLP pipelines.
Networked context, not just vectors
Information is woven into a robust directed graph, giving your agent complex reasoning capabilities beyond flat similarity.
Instant contextual recall
Using multi-way hybrid search, Awareness brings back exactly the right context in milliseconds when you need it.
96.0% on the ICLR 2025 long-term memory benchmark — 500 human-curated questions, reproducible scripts included.
Hybrid BM25 + vector + knowledge-graph recall runs on pure database compute. Zero LLM calls, zero latency tax, zero data leaves your machine.
Copy one config, paste it into your AI tool, and you're connected. That's it.
Awareness is the shared memory layer for AI agents: coding assistants, MCP tools, LangChain workers, and collaborative agent workspaces can recall the same decisions, preferences, and project context.
Give Claude Code, Cursor, Windsurf, and Copilot a persistent memory that survives new chats, project switches, and long refactors. The setup writes MCP config plus workflow rules so the agent knows when to recall and record.
Search intent: memory for Claude Code, Claude Code memory, memory for Cursor, Cursor AI memory.
Awareness connects to Cursor, Windsurf IDE, Trae AI, Zed Editor, VS Code Agent Mode, GitHub Copilot Extensions, PyCharm AI Assistant, and OpenClaw installation flows through MCP, SDKs, and local setup rules.
Search intent: Cursor, Windsurf IDE, Trae AI, Zed Editor, VS Code Agent Mode, GitHub Copilot Extensions, PyCharm AI Assistant, OpenClaw installation.
Research agents, coding agents, review agents, and automation workers can coordinate through one durable memory graph instead of passing brittle summaries between sessions. Built for Agentic Workflow, Open Memory Protocol (OMP), and LangChain memory issues.
Search intent: multi-agent memory, Multi-Agent Collaboration, Agentic Workflow, Open Memory Protocol (OMP), LangChain memory issues.
Awareness behaves like a coworker who keeps up with decisions, tradeoffs, risks, and handoffs. It helps agents continue AI Task Automation and office workflows without asking you to re-explain context every morning.
Search intent: agent cowork, AI cowork, AI Task Automation, persistent memory for AI agents, 自动办公智能体.
Four core capabilities that turn passive memory into active cognition.
Awareness injects workflow rules into your agent's config — so it automatically loads context at session start, recalls before work, and records after every change. No manual triggers needed.
Your AI auto-extracts 13 types of structured knowledge — decisions, solutions, risks, skills, preferences — and tags them for instant recall. It learns your patterns so you never repeat yourself.
Memories aren't just stored — they're connected. Related decisions, projects, and people are linked. Ask about one thing, your AI understands the full picture.
Auth system uses JWT with 15-min access tokens and 7-day refresh tokens. Token refresh endpoint is /api/auth/refresh.
Knowledge isn't static — it grows, updates, and self-corrects. Contradictions are flagged, outdated facts superseded, and new insights emerge as your agent works.
Multi-user memory, role-based access, cross-team recall, and contradiction detection — all built in.
Connect your existing tools via SDK or MCP, and give every team member an AI that remembers the full picture.
Data sources -> Memory workspace -> Workflow outputs
Awareness
Enterprise
Client conversations, requirement changes, and key commitments are automatically captured with user_id and agent_role tagging. When the team changes, the next owner recalls the full client context instantly via cross-role memory.
â What did the client mention in our last review meeting?
In the Mar 4 review: "This engine project must clear technical due diligence by Q3." Requested a POC proposal for the investment committee.
SOPs and operational context are automatically extracted into 6 engineering knowledge types — decisions, workflows, pitfalls, key_points, insights, and problem_solutions. Contradiction detection flags outdated procedures before they cause mistakes.
检测到：项目里程碑临近 · 待更新风险清单
Key people leave — knowledge stays. New hires connect to the shared memory workspace with role-based access. Cross-role recall means they can query any team's accumulated knowledge from day one.
新成员入职 · 第 5 天
↑ Traditional onboarding avg. 6 months
Why enterprises can't afford to ignore this
When a key employee leaves, they take 3 years of customer relationships with them. The next rep inherits an empty inbox and starts from zero — every single time.
73% of decisions made in meetings never get properly followed up. Context breaks between the meeting room and execution. Teams repeat the same mistakes quarter after quarter.
Who knew what, when, and why? Without stronger knowledge attribution and audit visibility, you can't answer regulators, resolve disputes, or learn from past decisions effectively.
When a client states a hard requirement in a meeting, the knowledge base shouldn't need a human to file it. Memory should actively capture it — flag the change, link the record, and surface it in the next recall.
The longer your team uses Awareness, the deeper the institutional memory grows. Every client interaction, every engineering decision, every operational insight compounds into a knowledge asset your competitors simply cannot replicate. The switching cost isn't a lock-in — it's a competitive advantage you've earned.
Awareness Enterprise gives your team multi-user memory with role-based access, cross-team recall, and 13 auto-categorized knowledge types. Connect via SDK or MCP — your existing AI tools gain shared institutional memory from day one.
One config file gets many MCP-compatible tools connected quickly. Deeper workflows can be added incrementally through the SDK when needed.
Create your first memory in under a minute. Connect any AI tool and start building assistants that actually remember.