Product Requirements Document (PRD): EchoMind AI

Project Name: EchoMind: AI Voice-to-Graph Brain
Version: 1.0 (2026 Internal Release)
Status: Draft
Author: Senior Product Manager

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1. Executive Summary

EchoMind is a "Second Brain" mobile application designed to bridge the gap between spontaneous verbal thought and structured knowledge management. By leveraging high-fidelity background recording, on-device AI transcription, and a GPU-accelerated dynamic knowledge graph, EchoMind allows users to capture ideas hands-free and automatically see how they connect to their existing web of knowledge.

2. Problem Statement

Knowledge workers, researchers, and creatives often have their best ideas while away from a keyboard (e.g., driving, walking). Traditional voice memo apps create "audio graveyards"—siloed, untranscribed files that are difficult to search and impossible to connect to other notes. This leads to "insight leakage" and the cognitive overhead of manually transcribing and filing notes later.

3. Goals & Success Metrics

• Goal: Reduce the "Capture-to-Connection" time from hours (manual) to seconds (automated).
• Metrics:
  • Insight Discovery Rate: Percentage of new notes that are linked to existing nodes within 24 hours.
  • User Retention (Wk 4): Target 35% for power users (Researchers/Creators).
  • Capture Velocity: Average number of voice memos recorded per user per week (Target: 5+).
  • Search Latency: P95 response time for semantic search results < 200ms.

4. User Personas

1. Dr. Aris (The Researcher): Needs to record observations in the field. Values privacy, offline capability, and complex bi-directional linking.
2. Sarah (The Content Creator): Records "shower thoughts" and script ideas. Needs integration with Notion and Obsidian to turn notes into published content.
3. James (The Executive): Uses voice to capture action items and meeting summaries. Needs high-fidelity recording and automated task extraction.

5. User Stories

• As a researcher, I want to record thoughts in areas with no signal so that my ideas are transcribed locally without needing a cloud connection.
• As a creative, I want to see a visual map of my notes so that I can identify non-obvious patterns and connections between different projects.
• As a busy professional, I want the app to automatically tag my recordings based on content so that I don't have to manually organize them.
• As a privacy-conscious user, I want my audio files encrypted end-to-end so that only I can access my intellectual property.

6. Functional Requirements

6.1 Audio Capture & Processing

• High-Fidelity Recording: Support 48kHz, 16-bit Mono WAV capture via expo-audio-studio.
• Background Operation: Must support "Orange Dot" recording on iOS 19+ and Foreground Service notifications on Android 16.
• On-Device Transcription: Utilize react-native-executorch with the Moonshine model for <100ms latency English transcription.

6.2 Knowledge Graph & Visualization

• GPU Rendering: Use @shopify/react-native-skia for 60fps graph navigation.
• Dynamic Layout: Implement d3-force within a Reanimated Worklet for smooth node positioning.
• Semantic Linking: Automated "Suggested Links" based on vector similarity scores > 0.85.

6.3 Search & Organization

• Semantic Search: Natural language querying (e.g., "What did I say about AI ethics last month?") powered by pgvector.
• Smart Tagging: LLM-driven keyword extraction (FastAPI/Pydantic-AI backend).

7. Technical Requirements

7.1 Tech Stack (2026 Standards)

• Frontend: React Native 0.83 (New Architecture), Expo SDK 55.
• Local Inference: ExecuTorch (Moonshine/Distil-Whisper-Turbo).
• Styling: NativeWind (Tailwind for React Native).
• Backend: Node.js 24 (LTS), FastAPI (AI Microservices).
• Databases:
  • PostgreSQL 17 + pgvector + pgvectorscale (System of Record).
  • Neo4j (Knowledge Graph Read-Model).
• Auth: Clerk (with Organizations 2.0).
• Encryption: Nitro Modules (AES-256-GCM via react-native-quick-crypto).

7.2 Integrations

• Obsidian: Bi-directional sync via Local REST API + Cloudflare Tunnel.
• Notion: Page/Block property sync using the Notion API.
• Vector DB: Pinecone Serverless for multi-region scalability.

8. Data Model

Entities

1. User: id, clerk_id, email, settings_json.
2. VoiceNote: id, user_id, s3_url_encrypted, transcript, summary, embedding_vector.
3. KnowledgeNode (Neo4j): node_id, label, type (Concept/Person/Event).
4. KnowledgeEdge (Neo4j): source_id, target_id, weight, relationship_type (e.g., "MENTIONS", "RELATED_TO").

9. API Specification (FastAPI)

• POST /v1/process-audio:
  • Input: Encrypted Audio Blob, UserID.
  • Process: Transcribe $\rightarrow$ Summarize $\rightarrow$ Vectorize $\rightarrow$ Map to Graph.
  • Response: TaskID (SSE Stream for progress).
• GET /v1/graph/connections:
  • Input: node_id, depth.
  • Response: JSON of nodes and edges for Skia rendering.

10. UI/UX Requirements

• Recording Indicator: Integrated with iOS Dynamic Island.
• Graph View: Pinch-to-zoom, drag-to-rearrange. Color-coded nodes based on "Node Type."
• Theme: Modern Dark Mode (OLED Optimized) to minimize battery drain during recording.

11. Non-Functional Requirements

• Performance: 60fps UI performance during graph heavy-loading.
• Privacy: No raw audio stored on servers in unencrypted format.
• Battery: Background recording should consume < 5% battery per hour.
• Availability: Offline-first mode for transcription.

12. Out of Scope

• Real-time multi-user collaborative graph editing (V2).
• Desktop application (Browser-based dashboard only for V1).
• Video-to-Note conversion.

13. Risks & Mitigations

• Risk: AI Hallucinations in transcripts.
  • Mitigation: Use Silero VAD to prune silence and provide "Confidence Scores" for words.
• Risk: Neo4j/Postgres out-of-sync.
  • Mitigation: Implement the Transactional Outbox Pattern with Debezium.

14. Implementation Tasks

Phase 1: Project Setup

• [ ] Initialize project with React Native 0.83 and Expo SDK 55
• [ ] Set up NativeWind for styling
• [ ] Configure ESLint/Prettier with New Architecture rules
• [ ] Initialize Clerk Auth with clerk-expo

Phase 2: High-Fidelity Capture & Local AI

• [ ] Implement expo-audio-studio for 48kHz WAV recording
• [ ] Configure iOS UIBackgroundModes and Android foregroundServiceType="microphone"
• [ ] Integrate react-native-executorch with Moonshine model weights
• [ ] Build encryption Nitro Module using react-native-quick-crypto

Phase 3: Backend & Data Pipeline

• [ ] Deploy FastAPI service on AWS Lambda (Response Streaming enabled)
• [ ] Set up PostgreSQL 17 with pgvectorscale
• [ ] Provision Neo4j instance and write Transactional Outbox worker
• [ ] Implement S3 Client-Side Encryption (CSE) upload flow

Phase 4: Graph Visualization

• [ ] Build @shopify/react-native-skia canvas component
• [ ] Implement d3-force simulation inside a UI-thread worklet
• [ ] Create semantic search bar with Pinecone/pgvector filtering
• [ ] Build Obsidian/Notion sync toggle settings

Phase 5: Launch & QA

• [ ] Conduct SOC2 data handling audit
• [ ] Perform battery stress test on Android 16 and iOS 19
• [ ] Finalize "First Time User Experience" (FTUE) walkthrough
• [ ] Deploy to TestFlight and Google Play Console (Closed Testing)