AI app for it and development · no coding needed
Local work memory and recall console
Reduce time spent reconstructing past work while keeping captured data on the user's own device.
Made for: Knowledge workers and small technical teams who need a searchable record of their own work activity
What it does for you
The problem
Work activity is scattered across screens, tabs, chats, email and meetings, so people cannot find what they did earlier or answer questions about it.
What it gives you
A searchable, user-approved work history with reminders and agent-accessible context
What you give it
Permitted local activity captureon-device transcriptionuser notes
Build your own version of Remind AI, LUCI Desktop and more
One app with what these 5 AI tools do, yours to keep and change: Remind AI, LUCI Desktop, Hansel, ShogunAI, Memno.
Everything these tools do, in one app
- Automatic activity capture Records your work activity without manual logging, covering screens, tabs, chats, email, and meetings.Found in LUCI Desktop, Hansel, ShogunAI
- Local-first storage Keeps captured data on your own device rather than in a vendor cloud account.Found in LUCI Desktop, Hansel, ShogunAI
- Searchable work history Makes past screens, transcripts, and activity searchable so you can find what you did earlier.Found in LUCI Desktop, Hansel, ShogunAI
- AI Q&A over history Lets you ask natural language questions about your past work and get answers.Found in Hansel
- Agent-accessible context Exposes your captured context to AI agents through MCP or a command-line interface so they can query it.Found in LUCI Desktop, ShogunAI
- On-device transcription Converts meeting speech to searchable text without sending audio to cloud servers.Found in LUCI Desktop
- Automatic daily summaries Generates summaries of your captured activity each day.Found in LUCI Desktop
- Configurable retention rules Lets you auto-delete history after set periods like 7, 30, or 90 days, or keep it indefinitely.Found in LUCI Desktop
- Encrypted local data Encrypts stored data with keys kept in your device's keychain so it can't be read without them.Found in Hansel
- Zero-data-retention AI Sends AI requests only to providers that do not retain your data.Found in Hansel
- Approval-gated sending Stops anything addressed to another person and waits for your explicit approval before sending.Found in ShogunAI
- Model-agnostic memory Works as a memory layer regardless of which AI model you use.Found in ShogunAI
- Reminder scheduling Schedules reminders with flexible time intervals and sends timely notifications.Found in Remind AI
- Automated follow-up notifications Sends follow-up alerts to reduce missed tasks and deadlines.Found in Remind AI
- Multi-device synchronization Keeps reminders consistent across your different devices.Found in Remind AI
- Calendar and app integration Connects with popular calendars and communication apps.Found in Remind AI
- Multi-format input processing Analyzes notes, voice memos, photos, emails, and documents using transcription, OCR, and parsing.Found in Memno
- Email thread participation Lets you CC the assistant on email threads so it can participate with full context.Found in Memno
- Scheduling and calls Makes phone calls and handles scheduling or rescheduling tasks with human oversight.Found in Memno
- Mobile quick capture Captures content quickly from mobile features like the lock screen camera and other apps.Found in Memno
How it works, step by step
- Capture work activity across screens, tabs, chats, email and meetings without manual logging
- Store captured data locally on the user's device
- Transcribe meeting speech on-device
- Index past screens, transcripts and activity for search
- Answer natural language questions over the user's history
- Expose captured context to AI agents through MCP or a command-line interface
- Generate automatic daily summaries
- Apply configurable retention rules such as 7, 30 or 90 days or indefinite
- Encrypt stored data with keys held in the device keychain
- Restrict AI requests to providers that do not retain data
- Hold anything addressed to another person for explicit user approval before sending
- Work as a model-agnostic memory layer
- Schedule reminders with flexible intervals and timely notifications
- Send automated follow-up alerts for missed tasks and deadlines
- Synchronize reminders across the user's devices
- Connect to calendars and communication apps
- Process notes, voice memos, photos, emails and documents using transcription, OCR and parsing
- Let the user CC the assistant on email threads so it participates with full context
- Make calls and handle scheduling or rescheduling with human oversight
- Capture content quickly from mobile features such as the lock-screen camera
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Local work memory and recall console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Local work memory and recall console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce time spent reconstructing past work while keeping captured data on the user's own device. For knowledge workers and small technical teams who need a searchable record of their own work activity, convert permitted local activity capture, on-device transcription and user notes into a searchable, user-approved work history with reminders and agent-accessible context. The benefit is a testable hypothesis, measured through time to retrieve a past work item and user-confirmed recall accuracy; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted local activity capture, on-device transcription and user notes, then follow this sequence: 1. Capture work activity across screens, tabs, chats, email and meetings without manual logging. 2. Store captured data locally on the user's device. 3. Index past screens, transcripts and activity for search. Resolve uncertain cases with the user, approve a searchable, user-approved work history with reminders and agent-accessible context, and measure time to retrieve a past work item and user-confirmed recall accuracy against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Capture scope, retention and agent access remain user-controlled; sending to other people and scheduling calls remain user-approved. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve user privacy, source attribution, quotation accuracy and usage permissions. Users approve substantive changes and external sending scope. One operating system and one user device; capture scope, retention and agent access remain user-controlled. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One operating system and one user device; capture scope, retention and agent access remain user-controlled. Implement one approved input format, a bounded representative case set and the first two task modules: capture work activity across screens, tabs, chats, email and meetings without manual logging; store captured data locally on the user's device. Support the third module with user review: index past screens, transcripts and activity for search. Include source references, corrections, basic device access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
User-owned devices, authorized calendars and permitted communication apps. Local storage, design-file import/export and agent interfaces. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Capture and permissions, Searchable history, Review and reminders. Use a timeline and filter bar for captured activity, a large central search and answer panel, and a right-hand panel for retention rules, encryption status and agent access. Let users compare a question with its cited source items. Display captured, reviewed and approved states. Provide an export and deletion view with a full audit trail. Make the task-specific outcome a searchable, user-approved work history with reminders and agent-accessible context visible beside its evidence, review state and value baseline.
