Meeting and work coordination portal

For

Engineering and delivery teams that run recurring meetings and track work across several tools

Solves

Meeting notes, decisions and task follow-ups live in separate tools, so teams re-explain context and reported progress drifts from actual tool activity.

Delivers

Reviewed meeting records, action items and standup drafts linked to their sources

Built in

about 4 weeks of creation time, MVP in 4 days

Investment

$14,000 for the MVP, $47,500 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce coordination overhead while keeping decisions and task follow-ups traceable.

1. Transcribe permitted meeting audio into text.
2. Generate concise summaries of key points and decisions.
3. Extract action items with owners and due dates.
4. Store notes, transcripts and summaries in one searchable repository.
5. Support note-taking and summaries in multiple languages.
6. Connect calendars to schedule and list meetings.
7. Join scheduled meetings automatically with participant notice.
8. Provide a chat assistant over meeting content.
9. Prepare agendas and briefs before meetings.
10. Send follow-up reminders to task owners.
11. Notify users about colleagues' office presence where permitted.
12. Read activity from Jira, GitHub and Slack.
13. Draft standup updates from actual work activity.
14. Flag discrepancies between reported work and tool activity.
15. Store agent work and results locally for persistence.
16. Inject relevant prior work into new sessions without summarization.
17. Verify provenance preservation with formal checks.
18. Generate written content such as articles and internal posts.
19. Automate repetitive coordination workflows.
20. Provide real-time data analysis over captured work data.

Everything these tools do, in one app

• Meeting transcription Automatically converts spoken meeting discussions into written text.Found in Fellow.app, MeetMinutes
• Meeting summaries Generates concise summaries of key points and decisions from meetings.Found in Fellow.app, MeetMinutes, On-It
• Action item capture Extracts and tracks tasks and follow-ups from meetings.Found in Fellow.app, MeetMinutes
• Centralized notes repository Stores all meeting notes, transcripts, and summaries in one accessible place.Found in Fellow.app, MeetMinutes
• Multilingual support Allows note-taking and summaries in multiple languages.Found in Spinach AI, MeetMinutes
• Calendar integration Connects with calendar applications to manage events and schedule meetings.Found in Fellow.app, On-It
• Automated meeting joining Joins meetings on behalf of the user to capture discussions.Found in Fellow.app
• AI meeting assistant Provides a chatbot to interact with meeting content and retrieve information.Found in Fellow.app, MeetMinutes
• Pre-meeting preparation Helps users prepare with agendas and briefs before meetings.Found in Fellow.app
• Follow-up reminders Sends reminders to team members to complete tasks or share updates.Found in On-It
• Office presence awareness Notifies users about colleagues' arrivals and presence in the office.Found in On-It
• Work activity reading Reads activity from tools like Jira, GitHub, and Slack to track work progress.Found in Troopr AI Scrum Master
• Standup update drafting Automatically drafts standup updates based on actual work activity.Found in Troopr AI Scrum Master
• Inconsistency flagging Flags discrepancies between reported work and actual tool activity.Found in Troopr AI Scrum Master
• Local memory storage Stores AI agent work and results locally for persistence across sessions.Found in Eggshell
• Context injection Injects relevant prior work into new chat sessions without LLM summarization.Found in Eggshell
• Formal verification Uses formal methods to verify properties like provenance preservation.Found in Eggshell
• Content generation Generates written content such as articles, blogs, and marketing copy.Found in Spinach AI, Falcon AI
• Workflow automation Automates repetitive tasks through customizable workflows.Found in Falcon AI
• Data analysis Provides real-time data analysis tools for informed decision-making.Found in Falcon AI

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted meeting audio, calendar events, participant lists, existing notes, and read-only work-tool activity from Jira, GitHub and Slack

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted meeting audio

4. 3

   Calendar events

5. 4

   Notes and work-tool activity

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed meeting records, action items and standup drafts linked to their sources

AI does the heavy lifting, people stay in charge

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, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Meeting recording requires participant consent and local rules; final decisions and task assignments remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Meeting capture and consent, Editable meeting record, Action and follow-up board, Work activity and standup view, Client or stakeholder summary. Use a list of meetings and work items, a large central editing canvas, and a right-hand panel for sources, participants, decisions and comments. Let users compare transcript, summary and prior version side by side. Display draft, changes requested and approved states. Provide a shareable summary link with comments anchored to the relevant decision or action item. Make the task-specific outcome reviewed meeting records, action items and standup drafts linked to their sources visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, meeting and participant records, consent states, source connections, approval states, retention limits, export history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions such as posting summaries or updating work tools.

Integrations and data access

Calendar providers, meeting platforms, Jira, GitHub, Slack and file storage. Start with file exchange and read-only connections, and validate current provider access, usage rights and schema behavior before promising a connector. Validate destination specifications before promising direct posting or work-tool updates.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   4 days

   One buyer segment, one recurring use case; first modules: transcribe permitted meeting audio into text; generate concise summaries of key points and decisions; extract action items with owners and due dates. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   5 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   10 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will engineering and delivery teams that run recurring meetings and track work across several tools use it to solve "meeting notes, decisions and task follow-ups live in separate tools, so teams re-explain context and reported progress drifts from actual tool activity"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted action items per meeting hour and follow-ups completed before the next meeting.
4. Measure, then decide. Track accepted action items per meeting hour and follow-ups completed before the next meeting; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One team, one calendar provider and read-only connections to one work tool; recording requires participant consent and final decisions remain human. Implement one approved input format, a bounded representative case set and the first three task modules: transcribe permitted meeting audio into text; generate concise summaries of key points and decisions; extract action items with owners and due dates. Support the remaining modules with operator review: read activity from Jira, GitHub and Slack; draft standup updates from actual work activity; flag discrepancies between reported work and tool activity. 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.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewed meeting records, action items and standup drafts linked to their sources. Retain the explicit scope boundary: One team, one calendar provider and read-only connections to one work tool; recording requires participant consent and final decisions remain human.

What the build depends on. Audio upload and playback, asynchronous transcription jobs, editable version history, reviewer access and tested export formats. High-fidelity coordination requires participant consent and local recording rules. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One team, one calendar provider and read-only connections to one work tool; recording requires participant consent and final decisions remain human.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined team and meeting set. Offer a monthly coordination allowance after repeat demand. Quote complex enterprise integrations or specialist compliance work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed meeting records, action items and standup drafts linked to their sources. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce coordination overhead while keeping decisions and task follow-ups traceable. Demonstrate a concrete reviewed meeting records, action items and standup drafts linked to their sources using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Engineering and delivery team communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant practitioner events.

Lead magnet

A reviewed sample reviewed meeting records, action items and standup drafts linked to their sources from a small authorized input set, with a transparent calculation of accepted action items per meeting hour and follow-ups completed before the next meeting and no promised savings.

The first 30 days

1. Week 1: interview five engineering and delivery teams that run recurring meetings and track work across several tools and inspect a recent example of meeting notes, decisions and task follow-ups live in separate tools, so teams re-explain context and reported progress drifts from actual tool activity.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure accepted action items per meeting hour and follow-ups completed before the next meeting, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted action items per meeting hour and follow-ups completed before the next meeting. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if consent cannot be obtained, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted action items per meeting hour and follow-ups completed before the next meeting; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed meeting records, action items and standup drafts linked to their sources. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved meeting formats, decision patterns and review examples, together with reliable delivery for a narrow coordination niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for engineering and delivery teams that run recurring meetings and track work across several tools. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Spinach AI, Fellow.app, MeetMinutes, Falcon AI, On-It, Troopr AI Scrum Master and Eggshell, plus manual notes and generic chat tools. Compare this product with the buyer's present method on accepted action items per meeting hour and follow-ups completed before the next meeting. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Transcription and model usage, storage, reviewer hours, integration maintenance, consent handling and client revision rounds. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed meeting records, action items and standup drafts linked to their sources. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve participant consent, source attribution, quotation accuracy and usage permissions. Named owners approve decisions, task assignments and any external posting. One team, one calendar provider and read-only connections to one work tool; recording requires participant consent and final decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.