
Plain-language multi-app automation delivery workspace
Reduce the technical effort to turn a described task into a running multi-step automation across apps.
- 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
What it does
Reduce the technical effort to turn a described task into a running multi-step automation across apps.
- Capture the automation in plain language.
- Refine the prompt before generation.
- 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.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned reviewed, running automation the team owns with source references and unresolved questions.
Everything these tools do, in one app
- Plain-language workflow creation Lets users describe the automation they want in everyday language instead of building it manually.Found in Hipocap, Lutra, TaskWand
- AI workflow generation Uses AI to turn the user's description into a complete automation workflow.Found in Hipocap, Lutra, TaskWand
- Multi-step automation Creates workflows that run several steps in sequence to complete a task.Found in Hipocap, TaskWand
- App integrations Connects with other applications so the automation can work across platforms.Found in Hipocap, Lutra
- Automatic task execution Runs the generated workflow automatically once it has been created.Found in Hipocap
- Custom API services Allows users to add their own API-based services to extend what can be automated.Found in Hipocap
- Ready-made workflows Provides pre-built automations that users can deploy quickly for common tasks.Found in Lutra
- Workflow scheduling Lets users schedule automations to run automatically at set times.Found in Lutra
- n8n workflow generation Produces ready-to-run n8n workflows from a text description.Found in TaskWand
- Conditions and loops Supports workflow logic such as conditional branches and repeated steps.Found in TaskWand
- Error handling Includes error handling in generated workflows so failures can be managed.Found in TaskWand
- Prompt improvement Refines the user's prompt to help produce more accurate workflow results.Found in TaskWand
- Workflow explanations Explains the generated workflow so users can understand what it does.Found in TaskWand
- Free trial tokens Gives free tokens on signup so users can try the service immediately.Found in TaskWand
What goes in, what comes out
- Plain-language descriptions
- App credentials
- Approved service access
AI drafts, people review. Technical delivery workspace with managed implementation.
- A reviewed
- Running automation the team owns
How it works
The workflow
- InStart with
Plain-language descriptions, app credentials and approved service access
- 1
Confirm the buyer's problem and scope
- 2
Collect plain-language descriptions
- 3
App credentials and approved service access
- 4
Then follow this sequence: 1
- OutFinish 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.
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
Scoping call
Day 1Thirty 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
MVP
7 daysOne 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
Paid pilot
8 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
3 weeksSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe 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.
- 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"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- 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.
- 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.
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- 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.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
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.
| Stage | Hosting and infrastructure | AI usage | Total 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 |
Run it or resell it
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.
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
- 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.
- Week 2: prepare a consented or synthetic demonstration of the three task modules.
- Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
- 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.
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.