Assisted workday coordination portal

For

Marketing and operations teams coordinating assisted work across several tools

Solves

Assisted work is spread across separate subscriptions for writing, analytics, focus control and weather planning, so coordination and data ownership suffer.

Delivers

Reviewed work items, generated drafts, dashboard views and scheduled alerts

Built in

about 5 weeks of creation time, MVP in 5 days

Investment

$13,500 for the MVP, $46,000 for the full product

Run it

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

Reduce tool sprawl while keeping assisted work in one owned portal.

1. Accept everyday-language commands and content tasks.
2. Generate articles, reports and summaries.
3. Analyze data and produce insights or visual representations.
4. Arrange analytics in adjustable dashboards.
5. Automate repetitive tasks and workflows.
6. Block distracting page content by context and intent.
7. Adjust behavior for work, learning or side-project profiles.
8. Show current conditions as they change.
9. Send alerts from user-defined preferences.
10. Provide hourly and weekly forecasts for planning.
11. Display patterns and alerts on an explorable map.
12. Offer adaptable pre-made project templates.
13. Let several users work on one project at once.
14. Connect with other applications and platforms.
15. Keep data on the user's device where privacy matters.
16. Intervene at the moment impulsive clicks would lead to distraction.
17. Protect data privacy and integrity.
18. Keep the interface usable with minimal technical expertise.

Everything these tools do, in one app

• Natural language processing Lets users interact with the tool using everyday language for commands and content tasks.Found in Gondolin, BrainGate.io
• Content generation Creates written material such as articles, reports, and summaries.Found in Gondolin
• Data analysis Examines data and provides insights or visual representations.Found in Gondolin, BrainGate.io
• Customizable dashboards Displays analytics in a layout that users can adjust to their needs.Found in BrainGate.io
• Intelligent automation Automates repetitive tasks and workflows to reduce manual effort.Found in BrainGate.io
• Context-aware blocking Blocks distracting web content based on page content and user intent instead of whole sites.Found in Task Sentry
• Task-based profiles Adjusts tool behavior for different activities like work, learning, or side projects.Found in Task Sentry
• Real-time updates Provides current information as it changes, such as weather conditions.Found in Tiempo
• Customizable notifications Sends alerts based on user-defined preferences.Found in Tiempo
• Detailed forecasts Offers hourly and weekly predictions for planning.Found in Tiempo
• Interactive maps Displays patterns and alerts on a map that users can explore.Found in Tiempo
• Customizable templates Provides pre-made formats that can be adapted for different projects.Found in Gondolin
• Collaboration features Allows multiple users to work on the same project at the same time.Found in Gondolin
• Third-party integrations Connects with other popular applications and platforms.Found in Gondolin, Tiempo, BrainGate.io
• Local AI processing Keeps data on the user's device for privacy.Found in Task Sentry
• Proactive protection Intervenes at the moment impulsive clicks would lead to distraction.Found in Task Sentry
• Security measures Protects data privacy and integrity.Found in BrainGate.io
• User-friendly interface Makes the tool easy to use with minimal technical expertise.Found in Gondolin, Tiempo, BrainGate.io

What goes in, what comes out

The workflow

1. In
   Start with

   Team tasks, content briefs, analytics sources, focus rules and planning inputs

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect team tasks

4. 3

   Content briefs

5. 4

   Analytics sources

6. 5

   Focus rules and planning inputs

7. 6

   Then follow this sequence: 1

8. Out
   Finish with

   Reviewed work items, generated drafts, dashboard views and scheduled alerts

AI does the heavy lifting, people stay in charge

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. One fixed team workspace and approved data sources; final editorial, analytical and scheduling decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Work intake and briefs, Editable production preview, Client proof and delivery. Use a thumbnail gallery for projects, a large central editing canvas, and a right-hand panel for references, constraints and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant asset. Make the task-specific outcome reviewed work items, generated drafts, dashboard views and scheduled alerts visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, asset versions, client comments, approval states, usage allowances, revision limits, download 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-owned documents, authorized analytics sources and permitted planning feeds. Cloud asset storage, design-file import/export and publishing destinations. 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

   5 days

   One buyer segment, one recurring use case; first modules: accept everyday-language commands and content tasks; generate articles, reports and summaries. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

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

4. 4

   Full product

   2 weeks

   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 marketing and operations teams coordinating assisted work across several tools use it to solve "assisted work is spread across separate subscriptions for writing, analytics, focus control and weather planning, so coordination and data ownership suffer"?
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: Reviewed work items completed per team hour and rework after approval.
4. Measure, then decide. Track reviewed work items completed per team hour and rework after approval; 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 team workspace and approved data sources; final editorial, analytical and scheduling decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: accept everyday-language commands and content tasks; generate articles, reports and summaries. Support the third module with operator review: analyze data and produce insights or visual representations. 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 work items, generated drafts, dashboard views and scheduled alerts. Retain the explicit scope boundary: One fixed team workspace and approved data sources; final editorial, analytical and scheduling decisions remain human.

What the build depends on. Asset upload and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist creative QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One fixed team workspace and approved data sources; final editorial, analytical and scheduling 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 workspace package. Offer a monthly production allowance after repeat demand. Quote complex integrations or specialist analytics separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed work items, generated drafts, dashboard views and scheduled alerts. 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 tool sprawl while keeping assisted work in one owned portal. Demonstrate a concrete reviewed work items, generated drafts, dashboard views and scheduled alerts using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Marketing and operations teams coordinating assisted work across several tools professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed work items, generated drafts, dashboard views and scheduled alerts from a small authorized input set, with a transparent calculation of reviewed work items completed per team hour and rework after approval and no promised savings.

The first 30 days

1. Week 1: interview five marketing and operations teams coordinating assisted work across several tools and inspect a recent example of assisted work spread across separate subscriptions for writing, analytics, focus control and weather planning.
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 reviewed work items completed per team hour and rework after approval, 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: Reviewed work items completed per team hour and rework after approval. 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

Reviewed work items completed per team hour and rework after approval; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewed work items, generated drafts, dashboard views and scheduled alerts. 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 templates, workspace settings and review examples, together with reliable delivery for a narrow operations niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for marketing and operations teams coordinating assisted work across several tools. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Gondolin, Task Sentry, Tiempo and BrainGate.io, plus freelancers and generic generation tools. Compare this product with the buyer's present method on reviewed work items completed per team hour and rework after approval. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, data processing, storage, reviewer hours, client revision rounds and licensed source assets. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewed work items, generated drafts, dashboard views and scheduled alerts. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve team voice, source attribution, quotation accuracy and usage permissions. Named owners approve substantive changes and publication scope. One fixed team workspace and approved data sources; final editorial, analytical and scheduling decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.