Medical inventory planning tool
Small-clinic planning combines consumption with expiry and storage constraints.
- For
- Clinic operations managers buying routine supplies
- Solves
- Ordering decisions overlook usage patterns and expiry dates.
- Delivers
- Reviewed replenishment suggestions
- Built in
- about 6 weeks of creation time, MVP in 7 days
- Investment
- $11,500 for the MVP, $46,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For clinic operations managers buying routine supplies, turn supply usage, stock counts and supplier lead times into reviewed replenishment suggestions.
- Normalize supply items.
- Flag expiring stock.
- Model usage.
- Account for lead times.
- Suggest order quantities.
- Record staff approval.
What goes in, what comes out
- Supply usage
- Stock counts
- Supplier lead times
AI drafts, people review. Assumption-driven planning and decision workspace.
- Reviewed replenishment suggestions
How it works
The workflow
- InStart with
Supply usage, stock counts and supplier lead times
- 1
Validate baseline inputs
- 2
Confirm definitions and constraints
- 3
Select editable assumptions
- 4
Calculate feasible alternatives
- 5
Inspect sensitivities
- 6
Let the responsible person approve a plan
- 7
Compare later actuals with the recorded assumptions
- OutFinish with
Reviewed replenishment suggestions
AI does the heavy lifting, people stay in charge
Extract input context and explain scenario differences. Use deterministic calculations or explicit optimization for quantities, compatibility, dates and prices. Show uncertain assumptions. Never let generated prose silently change the calculation rules.
What your team sees
Key screens: Stock dashboard, expiry view, order scenarios. 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. In this product, the first view is stock dashboard, followed by expiry view and order scenarios.
Accounts and administration
Scenario versions, baseline reconciliation, constraint checks, assumption ownership, reviewer approvals, plan exports and actual-versus-plan tracking.
Integrations and data access
Clinic-approved content and administrative exports. Clinical integrations require separate assessment. Read-only operational exports, calendars and finance or inventory records as relevant. Start with plan exports and retain human approval for execution. These are candidate integration categories, not verified supported connectors.
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: normalize supply items; flag expiring stock. 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 weeksRemaining modules: account for lead times; suggest order quantities; record staff approval. Self-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 clinic operations managers buying routine supplies use it to solve "ordering decisions overlook usage patterns and expiry dates"?
- 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. Reproduce a known historical plan, test missing inputs and boundary constraints, then run a new scenario.
- Measure, then decide. Track stockouts and expired stock value. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Begin with clinic operations managers buying routine supplies and one recurring use case. Build the first two modules: normalize supply items; flag expiring stock. Provide operator assistance for the third module: model usage. Deliver reviewed replenishment suggestions through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
After the MVP. After paid pilots establish value, automate the remaining modules: account for lead times; suggest order quantities; record staff approval. Add one validated source integration, reusable customer configuration and recurring delivery. Expand to additional teams, document formats or languages only after testing the new scope.
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.
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: normalize supply items; flag expiring stock. 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
Remaining modules: account for lead times; suggest order quantities; record staff approval. Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$46,500about 6 weeks of creation time · start with the MVP from $11,500
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 | $50–$100 | $50–$100 | $100–$200 |
| Full productabout 50 customers | $190–$380 | $350–$700 | $540–$1,080 |
Run it or resell it
For your own team
Clinic operations managers buying routine supplies run it inside the business: supply usage, stock counts and supplier lead times in, reviewed replenishment suggestions 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
#27912c - accent
#b054c9 - surface
#e4f1e5 - ink
#22201e
- Headings
- Archivo
- Text
- Lora
- Voice
- Careful, kind, clinically plain
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.
Message to test
Medical inventory planning tool for clinic operations managers buying routine supplies. Small-clinic planning combines consumption with expiry and storage constraints. Demonstrate the claim through a supply usage and expiry review.
Where to find buyers
Medical supply distributors
Lead magnet
A supply usage and expiry review
The first 30 days
- Week 1: interview five prospective buyers in this segment: clinic operations managers buying routine supplies. Ask to see a recent example of the problem and their current process.
- Week 2: prepare this demonstration using authorized or synthetic material: a supply usage and expiry review.
- Week 3: present it through medical supply distributors and seek one narrowly scoped paid pilot.
- Week 4: review stockouts, expired stock value, total delivery effort and a concrete renewal decision before increasing scope.
Paid pilot
Reproduce a known historical plan, test missing inputs and boundary constraints, then run a new scenario. Compare feasibility, reconciliation and observed error rather than judging the quality of the explanation alone. For this solution, use supply usage, stock counts and supplier lead times and evaluate reviewed replenishment suggestions. Agree success thresholds with the buyer before starting; collect a baseline for stockouts, expired stock value. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.
Success metrics
Stockouts, expired stock value
Retention and expansion
Refresh inputs, compare recorded assumptions with actual outcomes and refine validated constraints. Expand scenario complexity only when the buyer uses it for a decision.
Why clients would pick it
A validated domain model, customer-approved constraints and forecast or decision history that improves practical planning. For this solution, build around small-clinic planning combines consumption with expiry and storage constraints. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.
Alternatives and positioning
Spreadsheets, planners, specialist forecasting tools and existing scheduling or configuration software. Differentiate on this specific proposed advantage: small-clinic planning combines consumption with expiry and storage constraints. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.
Main delivery costs
Data preparation, domain modeling, validation, scenario computation, reviewer support and ongoing assumption maintenance.
Safeguards
Begin with administrative scope or clinician-reviewed material. Minimize sensitive patient data, restrict access and obtain required organizational review before connecting clinical systems. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.