Product service bundle configurator
Test sustainable service additions to existing products.
- For
- Manufacturers adding digital services
- Solves
- Service bundles are priced without understanding delivery workload.
- Delivers
- Product-lead-reviewed service bundle options
- Built in
- about 3 weeks of creation time, MVP in 4 days
- Investment
- $22,000 for the MVP, $50,000 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
Test sustainable service additions to existing products.
- Compose permissible bundles.
- Model usage and support costs.
- Compare contribution scenarios.
- Compare the reviewed result with the recorded baseline and value assumptions.
- Capture corrections and named-owner approval before consequential use.
- Export a versioned product-lead-reviewed service bundle options with source references and unresolved questions.
What goes in, what comes out
- Approved product capabilities
- Service cost assumptions
AI drafts, people review. Assumption-driven planning and decision workspace.
- Product-lead-reviewed service bundle options
How it works
The workflow
- InStart with
Approved product capabilities and service cost assumptions
- 1
Confirm the buyer's problem and scope
- 2
Collect approved product capabilities and service cost assumptions
- 3
Then follow this sequence: 1
- OutFinish with
Product-lead-reviewed service bundle options
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. No unverified capability promises or automatic commercial offers. A model suggestion is never a verified fact, professional decision or authorization to act.
What your team sees
Primary screens: Constraint and input setup, Scenario comparison, Decision and pilot tracker. Place editable drivers and constraints beside a clearly labeled scenario output. Include a baseline view, comparison chart or schedule, and an assumptions history. Let users trace a proposed quantity or date back to its inputs. Keep forecasts distinct from actual results. Make the task-specific outcome product-lead-reviewed service bundle options visible beside its evidence, review state and value baseline.
Accounts and administration
Scenario versions, baseline reconciliation, constraint checks, assumption ownership, reviewer approvals, plan exports and actual-versus-plan tracking. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.
Integrations and data access
Product feedback, authorized interviews, usage exports and requirement records. Read-only operational exports, calendars and finance or inventory records as relevant. Start with plan exports and retain human approval for 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
4 daysOne buyer segment, one recurring use case; first modules: compose permissible bundles; model usage and support costs. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
5 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
8 daysSelf-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 manufacturers adding digital services use it to solve "service bundles are priced without understanding delivery workload"?
- 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: Observed bundle contribution minus support and delivery cost.
- Measure, then decide. Track observed bundle contribution minus support and delivery cost; 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: No unverified capability promises or automatic commercial offers. Implement one approved input format, a bounded representative case set and the first two task modules: compose permissible bundles; model usage and support costs. Support the third module with operator review: compare contribution scenarios. 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 product-lead-reviewed service bundle options. Retain the explicit scope boundary: No unverified capability promises or automatic commercial offers.
What the build depends on. A defensible calculation model, explicit units, constraint validation and representative boundary tests. Advanced forecasting or optimization needs adequate historical data. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: No unverified capability promises or automatic commercial offers.
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: compose permissible bundles; model usage and support costs. 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$50,000about 3 weeks of creation time · start with the MVP from $22,000
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 | $50–$100 | $80–$160 |
| Full productabout 50 customers | $110–$210 | $350–$700 | $460–$910 |
Run it or resell it
For your own team
Manufacturers adding digital services run it inside the business: approved product capabilities and service cost assumptions in, product-lead-reviewed service bundle options 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
#782791 - accent
#8dc954 - surface
#eee4f1 - ink
#22201e
- Headings
- DM Serif Display
- Text
- DM Sans
- Voice
- Curious, rigorous, user-led
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 750-3,000 for a scoped planning setup and review, then USD 200-900 monthly for refreshes within agreed complexity. Data integration and optimization are separately scoped. All ranges are hypotheses. Package the initial sale as one bounded product-lead-reviewed service bundle options. 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
Test sustainable service additions to existing products. Demonstrate a concrete product-lead-reviewed service bundle options using the buyer's approved example and show the baseline, corrections and actual delivery effort.
Where to find buyers
Manufacturers adding digital services professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.
Lead magnet
A reviewed sample product-lead-reviewed service bundle options from a small authorized input set, with a transparent calculation of observed bundle contribution minus support and delivery cost and no promised savings.
The first 30 days
- Week 1: interview five manufacturers adding digital services and inspect a recent example of service bundles are priced without understanding delivery workload.
- 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 observed bundle contribution minus support and delivery cost, 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: Observed bundle contribution minus support and delivery cost. 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
Observed bundle contribution minus support and delivery cost; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.
Retention and expansion
Repeat the workflow when the buyer again needs product-lead-reviewed service bundle options. 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 validated domain model, customer-approved constraints and forecast or decision history that improves practical planning. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for manufacturers adding digital services. Repeatable delivery and useful integrations matter more than access to a base model.
Alternatives and positioning
Spreadsheets, planners, specialist forecasting tools and existing scheduling or configuration software. Compare this product with the buyer's present method on observed bundle contribution minus support and delivery cost. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.
Main delivery costs
Data preparation, domain modeling, validation, scenario computation, reviewer support and ongoing assumption maintenance. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of product-lead-reviewed service bundle options. Track cost per accepted output, including correction work, unsuccessful cases and support.
Safeguards
Use consented research and preserve contradictory evidence. Separate observed user behavior, proposed explanations and untested product assumptions. No unverified capability promises or automatic commercial offers. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.