Screenshot of the Plain-language multi-app automation delivery workspace interactive demo
Screenshot of the interactive demo, on sample data

Plain-language multi-app automation delivery workspace

Reduce the technical effort to turn a described task into a running multi-step automation across apps.

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For
Operations and IT teams who need multi-step automations across the apps they already use
Solves
Building multi-step automations across several apps needs technical work, and the tools that generate them are rented separately.
Delivers
A reviewed, running automation the team owns
Built in
about 6 weeks of creation time, MVP in 7 days
Investment
$12,500 for the MVP, $42,500 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Reduce the technical effort to turn a described task into a running multi-step automation across apps.

  1. Capture the automation in plain language.
  2. Refine the prompt before generation.
  3. Generate a complete multi-step workflow.
  4. Produce a ready-to-run n8n workflow.
  5. Add conditions and loops.
  6. Include error handling in generated steps.
  7. Explain the generated workflow in plain terms.
  8. Connect the apps the workflow must work across.
  9. Add custom API-based services.
  10. Offer ready-made workflows for common tasks.
  11. Schedule automations to run at set times.
  12. Execute the workflow automatically once approved.
  13. Compare the reviewed result with the recorded baseline and value assumptions.
  14. Capture corrections and named-owner approval before consequential use.
  15. Export a versioned reviewed, running automation the team owns with source references and unresolved questions.

Everything these tools do, in one app

What goes in, what comes out

What the customer puts in
  • Plain-language descriptions
  • App credentials
  • Approved service access

AI drafts, people review. Technical delivery workspace with managed implementation.

What the customer gets
  • A reviewed
  • Running automation the team owns
02

How it works

The workflow

  1. In
    Start with

    Plain-language descriptions, app credentials and approved service access

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect plain-language descriptions

  4. 3

    App credentials and approved service access

  5. 4

    Then follow this sequence: 1

  6. Out
    Finish with

    A reviewed, running automation the team owns

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate workflows 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 approved app set and one workflow runtime; final connection permissions and production runs remain under team control. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Description and app access, Editable workflow preview, Run history and delivery. Use a list of automations, a central step-by-step workflow canvas, and a right-hand panel for connections, conditions and errors. Let users compare generated versions side by side. Display draft, changes requested and approved states. Provide a run log with each step's input, output and failure reason. Make the task-specific outcome a reviewed, running automation the team owns visible beside its evidence, review state and value baseline.

Accounts and administration

Workspace ownership, connection versions, run logs, approval states, usage allowances, execution limits, download history and a rights record for supplied credentials. 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 app accounts, approved API credentials and permitted service endpoints. Cloud workflow storage, app connectors and execution destinations. Start with file exchange and validate destination specifications before promising direct execution. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

03

How we build it

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

    7 days

    One buyer segment, one recurring use case; first modules: capture the automation in plain language; refine the prompt before generation. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    8 days

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

  4. 4

    Full product

    3 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 operations and IT teams who need multi-step automations across the apps they already use use it to solve "building multi-step automations across several apps needs technical work, and the tools that generate them are rented separately"?
  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 automations per delivery hour and manual steps removed per workflow.
  4. Measure, then decide. Track accepted automations per delivery hour and manual steps removed per workflow; 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 approved app set and one workflow runtime; final connection permissions and production runs remain under team control. Implement one approved input format, a bounded representative case set and the first two task modules: capture the automation in plain language; refine the prompt before generation. Support the remaining modules with operator review: generate a complete multi-step workflow; produce a ready-to-run n8n workflow; add conditions and loops; include error handling in generated steps; explain the generated workflow in plain terms; connect the apps the workflow must work across; add custom API-based services; offer ready-made workflows for common tasks; schedule automations to run at set times; execute the workflow automatically once approved. 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 app integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around a reviewed, running automation the team owns. Retain the explicit scope boundary: One approved app set and one workflow runtime; final connection permissions and production runs remain under team control.

What the build depends on. Description capture and preview, asynchronous generation jobs, editable version history, reviewer access and tested export formats. High-fidelity production requires specialist integration QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One approved app set and one workflow runtime; final connection permissions and production runs remain under team control.

04

Investment

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

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: capture the automation in plain language; refine the prompt before generation. Manual review in the loop.

    $12,500 · about 7 days of creation time

  2. Phase 2

    Paid pilot

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

    $12,500 · about 8 days of creation time

  3. Phase 3

    Full product

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

    $17,500 · about 3 weeks of creation time

Indicative total, MVP to full product$42,500about 6 weeks of creation time · start with the MVP from $12,500

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.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$30–$60$60–$120$90–$180
Full productabout 50 customers$110–$210$530–$1,050$640–$1,260
05

Run it or resell it

Internally

For your own team

Operations and IT teams who need multi-step automations across the apps they already use run it inside the business: plain-language descriptions, app credentials and approved service access in, a reviewed, running automation the team owns out, reviewed by your people.

For your clients

As part of your offer

Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.

Your brand, or this one

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

  • primary#278891
  • accent#c95466
  • surface#e4f0f1
  • ink#22201e
Headings
Space Grotesk
Text
Inter
Voice
Technical, direct, no hype
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 automation package. Offer a monthly production allowance after repeat demand. Quote complex multi-app or custom API work separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed, running automation the team owns. 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 the technical effort to turn a described task into a running multi-step automation across apps. Demonstrate a concrete reviewed, running automation the team owns using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Operations and IT teams who need multi-step automations across the apps they already use professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed, running automation the team owns from a small authorized input set, with a transparent calculation of accepted automations per delivery hour and manual steps removed per workflow and no promised savings.

The first 30 days

  1. Week 1: interview five operations and IT teams who need multi-step automations across the apps they already use and inspect a recent example of building multi-step automations across several apps needs technical work, and the tools that generate them are rented separately.
  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 automations per delivery hour and manual steps removed per workflow, 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 automations per delivery hour and manual steps removed per workflow. 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

Accepted automations per delivery hour and manual steps removed per workflow; 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, running automation the team owns. 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 app connections, workflow patterns 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 operations and IT teams who need multi-step automations across the apps they already use. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Hipocap, Lutra, TaskWand, freelance automation developers and manual in-app configuration. Compare this product with the buyer's present method on accepted automations per delivery hour and manual steps removed per workflow. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Generation attempts, workflow execution runs, storage, reviewer hours, client revision rounds and licensed app access. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of a reviewed, running automation the team owns. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Preserve app permissions, source attribution, credential handling and usage permissions. The team approves substantive changes and production scope. One approved app set and one workflow runtime; final connection permissions and production runs remain under team control. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

Get this solution built

Built for you by our AI software factory, MVP in about 7 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

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