Echo Memory / 回声记忆

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A Personal Memory OS for AI-native work. Echo Memory turns conversations, documents, decisions, and changing ideas into a traceable personal memory layer that can be reused by different AI agents.

AI knows more about the world every day, but it still does not truly know you. Echo Memory gives your AI a memory of what you experienced, why you decided, and how your thinking changed.

The current macOS Alpha is the first working slice of this direction. It is not yet a complete personal digital twin, but it already closes the loop from source material to evidence-backed retrieval and agent access.

Why it exists

People generate valuable context continuously: meetings, calls, customer feedback, voice notes, documents, AI conversations, decisions, and follow-up results. That context is usually scattered across tools and quickly loses its connection to time, evidence, and later outcomes.

Traditional tools mainly preserve files or produce one-off summaries. Echo Memory is designed around a longer loop:

Capture -> Understand -> Connect -> Evolve -> Retrieve -> Feedback

The goal is not to save more notes. It is to preserve a person's experiences and reasoning as a durable, user-controlled context layer for future AI.

Product position

Echo Memory is not defined by transcription or meeting summaries. Those are input and processing capabilities.

The long-term product has four connected layers:

1. Personal Memory Layer: shared, permissioned context so every AI does not need to learn the user from zero.
2. Cognitive Database: evidence-backed records of knowledge, decisions, open questions, and how beliefs change.
3. Personal Memory OS: one system for capture, understanding, organization, retrieval, and feedback.
4. Digital Twin Database: a long-term, correctable model of what a person experienced, knows, values, and how they make decisions.

The digital-twin direction is a product vision, not a claim that the current Alpha can fully model a person.

What the current Alpha does

• Imports MP3, M4A, and WAV audio with duplicate detection.
• Imports Markdown, TXT, and DOCX documents into the same searchable library.
• Transcribes audio locally with embedded Whisper or a local whisper.cpp command.
• Uses local Ollama models for summaries, key points, decisions, action items, and open questions.
• Preserves timestamped transcript evidence and lets users return from a conclusion to its source.
• Organizes records into project knowledge libraries with local full-text and vector retrieval.
• Answers questions across indexed audio and documents with openable citations.
• Shows a day-based growth timeline across projects and records.
• Generates versioned cognitive-evolution snapshots with reviewable evidence and feedback.
• Exposes an opt-in, local, read-only MCP server for authorized AI tools.

What makes it different

Time is the backbone

Memory is not a folder tree. Events, projects, people, questions, and decisions develop in parallel. Echo Memory keeps when something happened and how later information relates to it.

Evidence is more important than a summary

Important conclusions should return to original transcript segments, timestamps, or document sources. AI inference is marked and reviewable instead of being presented as user-authored fact.

Memory keeps its history

A changed opinion is not a database error. Versioned memory preserves what was believed before, what changed, and which evidence caused the change.

Memory is callable

With user authorization, different AI tools can retrieve the context needed for a task through MCP without forcing the user to repeat the same background in every chat.

Current interface

The screenshots use synthetic demonstration data.

Evidence-backed knowledge chat

Growth timeline

Cognitive evolution

Local-first and user-controlled

Audio, the SQLite library, local transcription, local analysis, retrieval, and MCP remain on the Mac by default.

External AI is disabled by default. If a user enables it and explicitly confirms a generation, Echo Memory sends only the selected scope's text and existing structured analysis to the configured OpenAI-compatible service. Original audio is never uploaded by this feature. API keys are stored in macOS Keychain.

Generated cross-record memory is versioned, linked to sources, and can be confirmed or rejected. It does not overwrite original recordings, transcripts, or single-record analysis.

MCP: one memory layer for many agents

The current MCP server is local stdio, disabled by default, and read-only. It can search records, retrieve bounded transcript ranges, list projects, return project context, and list action items. It does not open a public port or modify the library.

See the MCP reference for tools and development configuration.

Product principles

• The user owns the memory: data should remain exportable, correctable, deletable, and revocable.
• Original evidence outranks AI summaries: important claims must remain traceable.
• Time and versions are preserved: new conclusions do not erase old reasoning.
• High-impact automation is confirmable: inferred relationships and changes must be reviewable.
• Agent access follows least privilege: tools receive only the context required for the task.
• The system assists decisions, not replaces the user: uncertainty and conflicting evidence should remain visible.

Current boundary and direction

The Alpha focuses on a single-user, single-device workflow. It does not currently provide real-time recording, automatic meeting joining, mobile or Windows apps, cloud sync, team collaboration, public APIs, or MCP writes.

The longer-term direction is to expand from traceable conversation memory into a personal memory infrastructure that can connect events, people, projects, questions, knowledge, decisions, and outcomes across time. That direction still requires product, privacy, and user-trust validation.

Requirements

• macOS on Apple Silicon
• Node.js 18+, Rust stable, Cargo, and Xcode Command Line Tools
• CMake for the first embedded Whisper build
• A local Whisper ggml-*.bin model for transcription
• Optional local whisper-cli / WHISPER_CPP_BIN
• Optional local Ollama service and model for analysis

Run locally

cd app
npm install
bash scripts/check-env.sh
npm run tauri dev

The default library is stored at ~/Library/Application Support/回声记忆. Use ECHO_LIBRARY_ROOT for an isolated development or test library.

Verify

cd app
npm run typecheck
npm run build
npm run test:growth
cd src-tauri
cargo fmt --check
cargo test --features mcp-bin

Project status

Echo Memory is Alpha software. Source builds are supported. A notarized macOS installer is not currently published in GitHub Releases.

Contributions are welcome. Read CONTRIBUTING.md before opening an issue or pull request, and never attach real audio, transcripts, databases, credentials, or private customer material to a public issue. Security reports should follow SECURITY.md.

Support

Echo Memory is free and open source. Support helps fund maintenance, compatibility testing, and documentation.

License

Apache-2.0. See LICENSE.