Team conversation and writing coordination portal

For

Team leads and knowledge workers coordinating conversations, meetings and writing across chat, calendar and documents

Solves

Context is scattered across chat threads, meetings and documents, so decisions, owners and next steps are missed and writing work is repeated.

Delivers

Reviewed daily brief with decisions, owners and next steps

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 missed follow-ups and repeated context gathering while keeping a human-approved record of decisions.

1. Connect chat, calendar, meeting and document sources.
2. Summarize threads, messages and notifications.
3. Generate meeting agendas and briefings.
4. Extract insights from shared files and reports.
5. Route tasks and trigger routine follow-ups.
6. Pull context from connected apps and agents.
7. Produce daily or on-demand catch-up briefs.
8. Sync calendar and message history at onboarding.
9. Provide a mobile-responsive daily overview.
10. Record, index and search past conversations.
11. Scan meetings and connected tools for important updates.
12. Produce daily or weekly digests and exports.
13. Apply enterprise security and compliance controls.
14. Draft text and develop ideas from scratch.
15. Suggest grammar and style changes.
16. Adjust tone for different purposes.
17. Give real-time writing feedback.
18. Learn user preferences for proactive support.
19. Support text, voice and email interaction.
20. Send personalized meeting reminders and briefings.

Everything these tools do, in one app

• In-chat AI assistant Lets users ask for help directly inside their team chat environment.Found in Slackbot
• Conversation summarization Turns threads, messages, and notifications into concise summaries.Found in Slackbot, Attrove AI, Rumi.ai
• Meeting preparation Generates agendas and briefings ahead of meetings.Found in Slackbot, Martin
• File and report analysis Extracts insights from documents and files shared in channels or threads.Found in Slackbot
• Task routing and follow-ups Automates routine follow-up actions and routes tasks based on chat requests.Found in Slackbot
• App and agent integrations Connects to other apps and agents to pull context from multiple sources.Found in Slackbot, Attrove AI, Rumi.ai and 2 more
• Daily catch-up briefs Provides daily or on-demand briefs that surface decisions, owners, and recent changes.Found in Attrove AI
• Quick onboarding Connects apps and syncs calendar and message history in a few minutes.Found in Attrove AI
• Mobile-responsive interface Offers a mobile-friendly design with a dedicated daily overview.Found in Attrove AI
• Meeting memory Records, indexes, and makes past conversations searchable and shareable.Found in Rumi.ai
• Continuous context scanning Continuously scans meetings and connected tools to surface important updates automatically.Found in Rumi.ai
• Automated digests and exports Produces daily or weekly digests and lets users export or share summaries with stakeholders.Found in Rumi.ai
• Enterprise security compliance Meets enterprise-grade security and compliance standards such as SOC 2 Type II.Found in Rumi.ai
• AI content generation Assists with idea development and creates text from scratch.Found in Sonnet
• Grammar and style suggestions Improves readability and polish by suggesting grammar and style changes.Found in Sonnet
• Customizable tone settings Adjusts the tone of writing to match different purposes.Found in Sonnet
• Real-time writing feedback Refines text during the writing process with immediate feedback.Found in Sonnet
• Proactive personalized assistance Learns user preferences and routines over time to offer proactive support.Found in Martin
• Multi-modal communication Allows interaction through text, voice, and email.Found in Martin
• Personalized reminders Sends meeting briefings and reminders tailored to the user.Found in Martin

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted chat threads, meeting records, shared files and calendar events

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted chat threads

4. 3

   Meeting records

5. 4

   Shared files and calendar events

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed daily brief with decisions, owners and next steps

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate summaries, briefs and writing suggestions 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. One fixed workspace and permitted source set; final decisions, task assignments and published writing remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Connection and sync setup, Daily brief and catch-up, Thread and meeting summary, Writing workspace, Admin and controls. Use a left navigation for sources and briefs, a central feed of summaries and next steps, and a right-hand panel for owners, due dates and comments. Let users compare a summary against its source thread or transcript. Display draft, changes requested and approved states. Provide a shareable digest link with comments anchored to the relevant item. Make the task-specific outcome a reviewed daily brief with decisions, owners and next steps visible beside its evidence, review state and value baseline.

Accounts and administration

Workspace ownership, source connections, member roles, approval states, usage allowances, 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.

Integrations and data access

Team chat, calendar, meeting recording, document storage and email. 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.

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: connect chat, calendar, meeting and document sources; summarize threads, messages and notifications. 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 team leads and knowledge workers coordinating conversations, meetings and writing across chat, calendar and documents use it to solve "context is scattered across chat threads, meetings and documents, so decisions, owners and next steps are missed and writing work is repeated"?
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: Follow-ups completed on time and reviewer correction time.
4. Measure, then decide. Track follow-ups completed on time and reviewer correction time; 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 fixed workspace and permitted source set; final decisions, task assignments and published writing remain human. Implement one approved source format, a bounded representative case set and the first two task modules: connect chat, calendar, meeting and document sources; summarize threads, messages and notifications. Support the remaining modules with operator review: generate meeting agendas and briefings; extract insights from shared files and reports; route tasks and trigger routine follow-ups; pull context from connected apps and agents; produce daily or on-demand catch-up briefs. 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 a reviewed daily brief with decisions, owners and next steps. Retain the explicit scope boundary: One fixed workspace and permitted source set; final decisions, task assignments and published writing remain human.

What the build depends on. Source connection and sync, asynchronous summarization jobs, editable version history, reviewer access and tested export formats. High-fidelity coordination requires qualified review. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed workspace and permitted source set; final decisions, task assignments and published writing 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 workspace package. Offer a monthly production allowance after repeat demand. Quote complex integrations or specialist writing support separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed daily brief with decisions, owners and next steps. 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 missed follow-ups and repeated context gathering while keeping a human-approved record of decisions. Demonstrate a concrete reviewed daily brief with decisions, owners and next steps using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Team leads and knowledge workers coordinating conversations, meetings and writing professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample daily brief with decisions, owners and next steps from a small authorized input set, with a transparent calculation of follow-ups completed on time and reviewer correction time and no promised savings.

The first 30 days

1. Week 1: interview five team leads and knowledge workers coordinating conversations, meetings and writing and inspect a recent example of context scattered across chat threads, meetings and documents, so decisions, owners and next steps are missed and writing work is repeated.
2. Week 2: prepare a consented or synthetic demonstration of the task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure follow-ups completed on time and reviewer correction time, 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: Follow-ups completed on time and reviewer correction time. 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 access is unavailable, 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

Follow-ups completed on time and reviewer correction time; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs a reviewed daily brief with decisions, owners and next steps. 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 summary formats, routing rules 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 team leads and knowledge workers coordinating conversations, meetings and writing. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Slackbot, Attrove AI, Rumi.ai, Sonnet and Martin, plus manual note-taking and generic chat assistants. Compare this product with the buyer's present method on follow-ups completed on time and reviewer correction time. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, meeting transcription and storage, reviewer hours, client revision rounds and licensed source connectors. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of a reviewed daily brief with decisions, owners and next steps. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, quotation accuracy and usage permissions. Named owners approve substantive changes, task assignments and publication scope. One fixed workspace and permitted source set; final decisions, task assignments and published writing remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.