{"slug": "recallmeet-remember-the-past-prepare-for-whats-next", "title": "RecallMeet: Remember the Past, Prepare for What’s Next", "summary": "A developer built RecallMeet, a personal AI meeting-memory and preparation agent that ingests meeting transcripts, links them by project, tracks commitments and unresolved issues, and generates a \"Prepare Me\" briefing for upcoming meetings. The system pairs a Next.js frontend with a FastAPI backend, using PostgreSQL for structured data, an LLM for summarization and reasoning, and a long-term memory layer called Hindsight for project context and prep feedback. Each user's meeting history is kept private and isolated from other users.", "body_md": "Meetings contain important information such as decisions, commitments, project discussions, and unresolved issues. As the number of meetings increases, remembering all this information becomes difficult.\n\n**RecallMeet** is a personal AI meeting-memory and preparation agent that remembers a user's previous meetings, connects them through projects, tracks commitments, and prepares the user for upcoming meetings.\n\nThe core idea is:\n\n**Remember → Prepare → Feedback → Learn → Prepare better.**\n\nEach user's meetings and memory remain private and isolated from other users.\n\nImportant information is often scattered across multiple meetings of the same project. Users may have to search through old transcripts to remember decisions, commitments, and unresolved issues before a new meeting.\n\nA traditional workflow is:\n\n**Meeting → Transcript → Summary**\n\nRecallMeet extends this into:\n\n**Meeting → Project Context → Long-Term Memory → Future Preparation**\n\nInstead of only answering *“What happened in this meeting?”*, RecallMeet focuses on:\n\n**“What do I need to know before my next meeting?”**\n\nUsers upload meeting transcripts containing the project, date, participants, and conversation.\n\nThe system extracts:\n\nMeetings from the same project are connected within the user's private history.\n\n```\nApollo Meeting 1\n       ↓\nRequirements + Security\n       ↓\nApollo Meeting 2\n       ↓\nAPI + Commitment\n       ↓\nApollo Meeting 3\n       ↓\nDeployment + Unresolved Issue\n       ↓\nApollo Meeting 4\n       ↓\nClient Concerns\n       ↓\nProject Memory\n       ↓\n\"Prepare Me\"\n       ↓\nPersonalized Preparation\n```\n\nThe **“Prepare Me”** feature uses this project history to generate previous discussions, pending commitments, unresolved issues, important context, and recommended discussion points.\n\nRecallMeet separates structured data, AI reasoning, and long-term memory.\n\nThe **Next.js frontend** manages the user interface, while the **FastAPI backend** handles application logic.\n\nThe application database stores users, meetings, projects, commitments, due dates, and statuses. The **LLM** handles summarization, information extraction, reasoning, and preparation generation.\n\n**Hindsight** provides long-term contextual memory, storing meaningful experiences, project context, and preparation feedback.\n\n```\n                         ┌──────────────────────┐\n                         │         USER         │\n                         │  Login / Dashboard   │\n                         └──────────┬───────────┘\n                                    │\n                                    ▼\n                         ┌──────────────────────┐\n                         │     NEXT.JS UI       │\n                         │                      │\n                         │ • Meeting Upload     │\n                         │ • Projects           │\n                         │ • Commitments        │\n                         │ • Prepare Me         │\n                         │ • Prep Feedback      │\n                         └──────────┬───────────┘\n                                    │\n                                    ▼\n                         ┌──────────────────────┐\n                         │    FASTAPI BACKEND   │\n                         │                      │\n                         │ • Authentication     │\n                         │ • Meeting Management │\n                         │ • Project Management │\n                         │ • Preparation Engine │\n                         └──────────┬───────────┘\n                                    │\n              ┌─────────────────────┼─────────────────────┐\n              │                     │                     │\n              ▼                     ▼                     ▼\n      ┌───────────────┐     ┌───────────────┐     ┌────────────────┐\n      │  PostgreSQL   │     │   LLM ENGINE  │     │    HINDSIGHT   │\n      │               │     │               │     │    MEMORY      │\n      │ Users         │     │ Summarization │     │ Experiences    │\n      │ Meetings      │     │ Extraction    │     │ Project Context│\n      │ Projects      │     │ Reasoning     │     │ Feedback       │\n      │ Commitments   │     │ Preparation   │     │ Learning       │\n      └───────────────┘     └───────┬───────┘     └───────┬────────┘\n                                    │                     │\n                                    └──────────┬──────────┘\n                                               ▼\n                                    ┌──────────────────────┐\n                                    │ PREPARATION ENGINE   │\n                                    │                      │\n                                    │ Project History      │\n                                    │ + Commitments        │\n                                    │ + Issues             │\n                                    │ + Feedback           │\n                                    └──────────┬───────────┘\n                                               │\n                                               ▼\n                                    ┌──────────────────────┐\n                                    │ PERSONALIZED MEETING │\n                                    │      BRIEFING        │\n                                    └──────────┬───────────┘\n                                               │\n                                               ▼\n                                    ┌──────────────────────┐\n                                    │    PREP FEEDBACK     │\n                                    └──────────┬───────────┘\n                                               │\n                                               ▼\n                                    ┌──────────────────────┐\n                                    │ HINDSIGHT LONG-TERM  │\n                                    │       LEARNING       │\n                                    └──────────────────────┘\n```\n\nThe workflow begins when a user uploads a meeting transcript. RecallMeet analyzes it and extracts useful information such as decisions, commitments, and unresolved issues.\n\nThis information is connected to the relevant project. Hindsight maintains meaningful long-term context, while structured information such as commitments and statuses is maintained by the application database.\n\nWhen the user selects **“Prepare Me,”** relevant project history is retrieved and used to generate a personalized briefing.\n\nExample:\n\n**Previous Discussions:** API integration, security, deployment\n\n**Pending Commitments:** Send API documentation\n\n**Unresolved Issues:** Client budget concern\n\n**Recommended Focus:** Follow up on commitments and unresolved concerns.\n\nThe most important feature of RecallMeet is its ability to use **Prep Feedback** to improve future preparation.\n\nFor example:\n\n**User Feedback:**\n\n*“You missed the client's budget concern. Focus more on unresolved client concerns next time.”*\n\nThis feedback becomes part of the user's long-term memory and can influence the next preparation.\n\n```\n                 ┌─────────────────────┐\n                 │   MEETING UPLOAD    │\n                 └──────────┬──────────┘\n                            ↓\n                 ┌─────────────────────┐\n                 │   AI UNDERSTANDS    │\n                 │     MEETING         │\n                 └──────────┬──────────┘\n                            ↓\n              ┌─────────────────────────────┐\n              │ PROJECT + DECISIONS         │\n              │ COMMITMENTS + ISSUES        │\n              └──────────────┬──────────────┘\n                             ↓\n                   ┌──────────────────┐\n                   │ HINDSIGHT MEMORY │\n                   └────────┬─────────┘\n                            ↓\n                   ┌──────────────────┐\n                   │   \"PREPARE ME\"   │\n                   └────────┬─────────┘\n                            ↓\n                ┌────────────────────────┐\n                │ PERSONALIZED PREP      │\n                │ Context + Commitments  │\n                │ Issues + Focus         │\n                └───────────┬────────────┘\n                            ↓\n                   ┌──────────────────┐\n                   │   PREP FEEDBACK  │\n                   └────────┬─────────┘\n                            ↓\n                   ┌──────────────────┐\n                   │ HINDSIGHT LEARNS │\n                   └────────┬─────────┘\n                            ↓\n                ┌────────────────────────┐\n                │ NEXT PREPARATION       │\n                │ Uses Previous Feedback │\n                └───────────┬────────────┘\n                            ↓\n                   ┌──────────────────┐\n                   │ BETTER FOCUS     │\n                   └──────────────────┘\n```\n\nThe key learning behavior is:\n\n**First Preparation → Feedback → Hindsight Memory → Second Preparation → Improved Focus**\n\nThe user logs into RecallMeet, uploads meeting transcripts, and organizes them by project. The system builds project memory as more meetings are added.\n\nBefore an upcoming meeting, the user selects **“Prepare Me”** to receive a personalized briefing.\n\n```\nLOGIN\n  ↓\nUPLOAD MEETING\n  ↓\nANALYZE TRANSCRIPT\n  ↓\nEXTRACT INFORMATION\n  ↓\nPROJECT MEMORY\n  ↓\n\"PREPARE ME\"\n  ↓\nPERSONALIZED PREPARATION\n  ↓\nPREP FEEDBACK\n  ↓\nHINDSIGHT LEARNS\n  ↓\nBETTER FUTURE PREPARATION\n```\n\nThe MVP focuses on authentication, meeting uploads, project organization, information extraction, commitment tracking, Hindsight memory, personalized preparation, and Prep Feedback. Features such as real-time transcription, meeting-platform integrations, mobile apps, and cross-user memory are outside the initial MVP.\n\nRecallMeet transforms meeting information into a continuously useful personal memory system.\n\nInstead of treating meetings as isolated conversations, it connects them through project context, remembers important information, tracks commitments, and prepares users for future discussions.\n\nIts central learning loop is:\n\nRecallMeet is therefore more than a meeting summarizer—it is a **private, project-aware AI memory that turns past meetings and preparation feedback into progressively better preparation for the user's next meeting.**\n\n**Project Deliverables & Links**\n\nGitHub Repository: [https://github.com/Ho436-art/RecallMeet](https://github.com/Ho436-art/RecallMeet)\n\nDemo Video: [https://youtu.be/xuQOZrfyWJU](https://youtu.be/xuQOZrfyWJU)", "url": "https://wpnews.pro/news/recallmeet-remember-the-past-prepare-for-whats-next", "canonical_source": "https://dev.to/raghasree_chowdary_1/recallmeet-remember-the-past-prepare-for-whats-next-52i8", "published_at": "2026-09-28 14:07:15+00:00", "updated_at": "2026-09-28 14:20:03.102953+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-agents", "ai-tools", "ai-products"], "entities": ["RecallMeet", "Next.js", "FastAPI", "PostgreSQL", "Hindsight"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/recallmeet-remember-the-past-prepare-for-whats-next", "markdown": "https://wpnews.pro/news/recallmeet-remember-the-past-prepare-for-whats-next.md", "text": "https://wpnews.pro/news/recallmeet-remember-the-past-prepare-for-whats-next.txt", "jsonld": "https://wpnews.pro/news/recallmeet-remember-the-past-prepare-for-whats-next.jsonld"}}