Financial document extraction API
Field-level provenance and schema validation for a narrow document niche.
- For
- Software vendors processing business financial documents
- Solves
- Document formats vary and break fixed extraction rules.
- Delivers
- Structured document data with source references
- Built in
- about 5 weeks of creation time, MVP in 6 days
- Investment
- $10,000 for the MVP, $40,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For software vendors processing business financial documents, turn defined document types and customer field schemas into structured document data with source references.
- Define extraction schemas.
- Capture source coordinates.
- Validate field formats.
- Flag uncertain values.
- Support correction feedback.
- Deliver structured responses.
What goes in, what comes out
- Defined document types
- Customer field schemas
AI drafts, people review. Client intake portal and staff exception queue.
- Structured document data with source references
How it works
The workflow
- InStart with
Defined document types and customer field schemas
- 1
Choose the request type
- 2
Collect declared facts and required documents
- 3
Extract relevant fields
- 4
Show missing or inconsistent information
- 5
Let the submitter correct it
- 6
Route the complete package to an authorized reviewer
- OutFinish with
Structured document data with source references
AI does the heavy lifting, people stay in charge
Classify submitted material, extract candidate fields and draft clarification questions. Deterministic rules test required fields and formats. Keep uncertain extraction visible and preserve the original statement. Do not infer missing material facts.
What your team sees
Key screens: Schema designer, extraction review, API usage. Give submitters a mobile-friendly step-by-step form with document uploads and a visible completeness checklist. Staff see a queue with missing items and extracted fields. Place the original document beside each uncertain value. Show submitted, clarification required and ready-for-review states. In this product, the first view is schema designer, followed by extraction review and API usage.
Accounts and administration
Secure uploads, configurable checklists, progress saving, duplicate handling, reviewer assignments, clarification threads, deadlines and submission history.
Integrations and data access
Accounting exports, invoice records and finance review processes. Case management, customer records, document storage and notification systems. Begin with an exportable review pack before automating destination writes. 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
6 daysOne buyer segment, one recurring use case; first modules: define extraction schemas; capture source coordinates. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
7 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
2 weeksRemaining modules: flag uncertain values; support correction feedback; deliver structured responses. 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 software vendors processing business financial documents use it to solve "document formats vary and break fixed extraction rules"?
- 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. Process a bounded set of historical and new submissions.
- Measure, then decide. Track field accuracy and cost per accepted document. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. Begin with software vendors processing business financial documents and one recurring use case. Build the first two modules: define extraction schemas; capture source coordinates. Provide operator assistance for the third module: validate field formats. Deliver structured document data with source references 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: flag uncertain values; support correction feedback; deliver structured responses. 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. Secure upload handling, reliable extraction, versioned completeness rules, submitter identity and staff routing. Third-party checklist changes require maintenance.
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: define extraction schemas; capture source coordinates. 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: flag uncertain values; support correction feedback; deliver structured responses. Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$40,500about 5 weeks of creation time · start with the MVP from $10,000
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 | $50–$100 | $40–$90 | $90–$190 |
| Full productabout 50 customers | $190–$380 | $280–$560 | $470–$940 |
Run it or resell it
For your own team
Software vendors processing business financial documents run it inside the business: defined document types and customer field schemas in, structured document data with source references 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
#759127 - accent
#545ac9 - surface
#edf1e4 - ink
#22201e
- Headings
- Archivo
- Text
- Lora
- Voice
- Exact, sober, trustworthy
Selling it to your own clients: the go-to-market playbook
Pricing to test
Test USD 500-2,000 setup plus USD 150-750 monthly for one form family and a capped submission volume. Quote specialist review and unusual document formats separately. Prices are experimental.
Message to test
Financial document extraction API for software vendors processing business financial documents. Field-level provenance and schema validation for a narrow document niche. Demonstrate the claim through a benchmark on representative customer documents.
Where to find buyers
Vertical software developer communities
Lead magnet
A benchmark on representative customer documents
The first 30 days
- Week 1: interview five prospective buyers in this segment: software vendors processing business financial documents. Ask to see a recent example of the problem and their current process.
- Week 2: prepare this demonstration using authorized or synthetic material: a benchmark on representative customer documents.
- Week 3: present it through vertical software developer communities and seek one narrowly scoped paid pilot.
- Week 4: review field accuracy, cost per accepted document, total delivery effort and a concrete renewal decision before increasing scope.
Paid pilot
Process a bounded set of historical and new submissions. Include missing, duplicate and unreadable documents. Compare complete submissions and clarification effort with the current intake method. For this solution, use defined document types and customer field schemas and evaluate structured document data with source references. Agree success thresholds with the buyer before starting; collect a baseline for field accuracy, cost per accepted document. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.
Success metrics
Field accuracy, cost per accepted document
Retention and expansion
Review incomplete submissions and simplify recurring friction. Expand to another form or document family after the first workflow reliably produces review-ready cases.
Why clients would pick it
Document-type expertise, tested completeness rules and a low-friction client experience embedded in a repeat administrative process. For this solution, build around field-level provenance and schema validation for a narrow document niche. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.
Alternatives and positioning
Email collection, generic web forms, spreadsheets and existing case management systems. Differentiate on this specific proposed advantage: field-level provenance and schema validation for a narrow document niche. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.
Main delivery costs
Document processing, storage, exception review, support, checklist maintenance and customer-specific integration work.
Safeguards
Reconcile calculations to approved records. Keep proposed entries and payment actions under finance-team control. Never invent missing financial inputs. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.