AI for healthcare data platforms
Contracts, provider records and documents turned into data your analysts can trust.
For healthcare data companies. Extraction that reads any layout with a source for every value, provider data verified against NPI, all inside your own HIPAA cloud account.
Built for: Provider data, contract analysis and healthcare analytics products.
Already built or tried AI? Get it scored with the AI Scorecard.
app.northfieldhealth.example/contracts/upload
Northfield Health Data · Paperly
DemoStep 1 of 3
Illustrative demo on a fictional practice. Not client work.
Where these products get stuck
What gets in the way, and how we handle it.
- 01
Extraction breaks on the next layout
One pipeline for every layout
Retrieval and extraction replace layout rules, so new layouts do not need new code.
- 02
Guessed values in regulated documents
Blanks, never guesses
Fields are filled only from passages found in the document, with the source shown.
- 03
Data cannot leave your boundary
Built inside your account
We work inside your restricted cloud account, with permissions you grant.
AI inside your product
The modules that fit this kind of platform.
Each one is shown on a fictional practice. It is built into your codebase and ships under your name, on an engine we license to you.
What it connects to: Your document storage and data warehouse, with the NPI Registry for provider verification. Sprints use sample or de-identified documents.
Paperlyby Datics AI
AI document extraction for healthcare
Contracts, referrals and forms read into fields, every value tied to its page.
Fits: Healthcare data and analytics platforms, credentialing, revenue cycle and contract management products
Desklyby Datics AI
AI assistant for practice staff
Staff ask in plain words. Answers come from your policies, with the source.
Fits: Practice management software, dental service organization platforms, practice operations tools
Proof
What we have built that this rests on.
57 featured AI case studies: AI products and AI built into live products, each written up on our Work page.
Datascape
Healthcare data · Document extraction
Compensation terms read from any physician contract, built inside the client's HIPAA cloud
Extraction code broke whenever a contract changed layout. One RAG pipeline now reads any contract, inside the client's own AWS account.
Healthcare data consultancy
Healthcare data · Provider verification
Provider data from scattered practice websites, verified against NPI inside the client's AWS
Practice sites are all built differently and many lack sitemaps. One crawler in the client's AWS now turns them into NPI verified records.
NenoDoc Lexicon by Neno Technologies
AI engine · Cited answers
Archive teams get cited answers in French and English on one client-owned GPU
Sensitive archives could not go to an outside AI. Now teams ask in French or English and get answers cited to the page, all on the client's GPU.
How it works
Three ways to start, each at a fixed price.
Most healthcare data teams start with Paperly in a Build Sprint: one document type read into your schema, with a source for every value.
Healthcare Product Review · 30 minutes, no chargeStart here. We look at your product with you, agree the practice outcome you want, and tell you which of the three below fits.
Book a 30-minute Product ReviewNo AI yet, and a module fits
Build Sprint
$10,000 fixed3 weeks
Pick it when: One of our modules delivers the outcome you want.
- One practice outcome (2 to 3 related capabilities) working in your staging, behind a feature flag
- Pull requests to your repo, built on synthetic or de-identified patient data
- Quality and safety evals, the cost per practice and a packaging recommendation
- A fixed-price quote for production
Something new, or a plan first
Planning Sprint
$5,000 fixed2 weeks
Pick it when: You need something our modules do not cover, or want a plan before you build.
- Where AI fits across your product, including beyond our modules
- A prioritized capability map, with what each one depends on
- A readiness review of your architecture, data, integrations and permissions
- A fixed-price quote to build it and take it to production
AI already built or tried
AI Scorecard
$5,000 fixed2 weeks
Pick it when: You have already built or tried an AI feature in your product, live or not.
- One AI feature you have built, tested in staging on 50 of your own de-identified cases
- PHI leakage, cross-practice access and misuse tests
- Cost per practice and a packaging recommendation
- A scorecard, ranked fixes, draft security answers and a fixed quote
Not a compliance audit or certification.
How the AI Scorecard worksProduction, at a fixed quote
We take what your Sprint built or planned live for your practices, by pull request, with no standing production access. It typically includes load testing at your peak and a spend cap per practice. Your Sprint or Scorecard fee counts toward it.
After go-live, optional support
The product is finished and yours to run. If you want us to stay on: a named lead engineer, a monthly quality and cost report, testing before any model change, and more capabilities, each at its own fixed quote.
Stop after any Sprint and keep what you got.
How a Build Sprint runs
- In the setup week we map your integrations and agree what the Sprint touches.
- We follow your coding standards, tests and CI; your engineers review and merge every pull request.
- Half at signature, half when the Sprint Pack is delivered.
- Your time: about 2 to 3 hours a week from a product owner, plus an engineer to review pull requests.
Product improvements you can measure
What we agree to measure: quality and cost on test sets in the Build Sprint, adoption and outcomes once it is in production, so the decision to go further is made on evidence.
Fewer documents read by hand
Share of fields filled with a source
Provider data you can trust
Share of provider records verified against NPI
We set the success measures with you in the setup week.
Built for patient data
Controls your customers' security reviews ask about.
Each control is a design fact about how the module is built and how we work, not a compliance claim.
Works with what you run
Reads schedules, patient records and calls through the APIs and roles your product already has.
De-identified data in Sprints
Sprint work uses synthetic or de-identified data and ships as pull requests to your repo.
Cited, and the clinician approves
Answers show their source; anything that reaches a chart or a patient waits for a person.
We work within your HIPAA, privacy, security and customer requirements, and sign a BAA when the work needs one. Compliance depends on the complete product, contracts, policies and operating environment; Datics does not present software engineering alone as legal certification.
How we handle patient dataQuestions we hear on the first call
Straight answers before you book.
Can you work inside our AWS account under a BAA?
Yes. We have worked inside a client's restricted HIPAA AWS account under a BAA, with permissions the client granted.
Other healthcare platforms we build for
See it on your own product.
Bring one product, workflow or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per practice and what your customers' privacy review will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.