AI app for it and development · no coding needed
Shared work context coordination portal
Keep one permissioned, current picture of work that people and AI tools can act on.
Made for: Engineering and operations teams coordinating people and AI tools across shared work
What it does for you
The problem
Work context lives in separate tools, so people and AI agents act on stale or partial information.
What it gives you
A shared, permission-scoped context store with live activity and change summaries
What you give it
Connected tool activitymeeting recordsdecisionstask state
Build your own version of Sense, Hoop and more
One app with what these 4 AI tools do, yours to keep and change: Sense, Hoop, Compendium, In Parallel MCP.
Everything these tools do, in one app
- Shared context layer Keeps one up-to-date store of knowledge, decisions, and context that both people and AI tools can use.Found in Compendium, In Parallel MCP
- Automatic task capture Pulls tasks from meetings, emails, and chat without manual entry.Found in Hoop
- Interactive dashboards Shows data in real-time visual dashboards for easier interpretation.Found in Sense
- Automated data cleaning Prepares and cleans data automatically before analysis.Found in Sense
- Customizable reporting templates Lets users create reports from templates they can adjust.Found in Sense
- Meeting transcripts and summaries Provides transcripts, summaries, and context alongside captured tasks.Found in Hoop
- Calendar integration Connects to the calendar to prompt users before meetings.Found in Hoop
- Multiplayer AI sessions Lets multiple teammates drive one AI interaction together in real time.Found in Compendium
- Live activity view Shows what every teammate and agent is working on right now.Found in Compendium
- Change summaries Summarizes what changed while you were away.Found in Compendium
- MCP server access Exposes the shared context to AI tools through an MCP server.Found in Compendium, In Parallel MCP
- Model-agnostic access Works with multiple AI tools rather than locking users into one model provider.Found in Compendium, In Parallel MCP
- Passive integrations Ingests information from connected tools automatically without manual writing.Found in Compendium, In Parallel MCP
- Permission-scoped sharing Lets users control what context is shared and with whom.Found in In Parallel MCP
- Graph-based context model Stores context as events and relationships so updates reflect changes without last-write-wins logic.Found in In Parallel MCP
- Collaborative team access Allows team members to access and give feedback together.Found in Sense
- Enterprise security compliance Meets strict security and data residency requirements with certifications and policies.Found in In Parallel MCP
- Unlimited data storage Stores unlimited data with a capped file size per context document.Found in Compendium
How it works, step by step
- Maintain one shared store of knowledge, decisions and context for people and AI tools
- Capture tasks automatically from meetings, email and chat
- Show real-time visual dashboards of work state
- Clean and prepare incoming data before analysis
- Build reports from adjustable templates
- Produce meeting transcripts, summaries and linked tasks
- Connect calendars and prompt users before meetings
- Let several teammates drive one AI session together
- Show what every teammate and agent is working on now
- Summarize what changed while a user was away
- Expose shared context to AI tools through an MCP server
- Work with multiple AI tools rather than one model provider
- Ingest information from connected tools without manual writing
- Scope what context is shared and with whom
- Store context as events and relationships instead of last-write-wins fields
- Give team members shared access and feedback
- Meet enterprise security and data residency requirements
- Store unlimited data with a capped file size per context document
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned shared, permission-scoped context store with source references and unresolved questions
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 Shared work context coordination portal 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 Shared work context coordination portal 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 Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data198 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
Keep one permissioned, current picture of work that people and AI tools can act on. For engineering and operations teams coordinating people and AI tools across shared work, convert connected tool activity, meeting records, decisions and task state into a shared, permission-scoped context store with live activity and change summaries. The benefit is a testable hypothesis, measured through coordination errors per week and time to reconstruct current work state; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect connected tool activity, meeting records, decisions and task state, then follow this sequence: 1. Maintain one shared store of knowledge, decisions and context for people and AI tools. 2. Capture tasks automatically from meetings, email and chat. 3. Show real-time visual dashboards of work state. 4. Clean and prepare incoming data before analysis. 5. Build reports from adjustable templates. 6. Produce meeting transcripts, summaries and linked tasks. 7. Connect calendars and prompt users before meetings. 8. Let several teammates drive one AI session together. 9. Show what every teammate and agent is working on now. 10. Summarize what changed while a user was away. 11. Expose shared context to AI tools through an MCP server. 12. Work with multiple AI tools rather than one model provider. 13. Ingest information from connected tools without manual writing. 14. Scope what context is shared and with whom. 15. Store context as events and relationships instead of last-write-wins fields. 16. Give team members shared access and feedback. 17. Meet enterprise security and data residency requirements. 18. Store unlimited data with a capped file size per context document. Resolve uncertain cases with qualified reviewers, approve a shared, permission-scoped context store with live activity and change summaries, and measure coordination errors per week and time to reconstruct current work state against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, permission checks and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final decisions on task ownership, priority and external sharing remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, permission boundaries, data residency and usage rights. Named owners approve task changes and external sharing. One team, one connected tool set and one approved AI tool; final task ownership and external sharing decisions remain human. 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 team, one connected tool set and one approved AI tool; final task ownership and external sharing decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: maintain one shared store of knowledge, decisions and context for people and AI tools; capture tasks automatically from meetings, email and chat. Support the remaining modules with operator review. Include source references, corrections, basic organization 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
Connected calendars, email, chat, meeting recorders and project trackers. Cloud storage, identity providers, AI tool endpoints and MCP clients. 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: Connections and permissions, Shared context and live activity, Reports and change summaries. Use a workspace list, a central context timeline with linked tasks and decisions, and a right-hand panel for permissions, sources and comments. Let users compare current state against a previous snapshot. Display draft, in review and approved states. Provide a scoped share link for external collaborators. Make the task-specific outcome a shared, permission-scoped context store with live activity and change summaries visible beside its evidence, review state and value baseline.
