AI for established healthcare software
AI your practices will trust, built into the healthcare software they run every day.
For dental, veterinary, clinic and healthcare data platforms with paying customers. We build it in your cloud and repository, under your name, so practices spend less time on forms, notes and callbacks, and you have a feature you can price.
- Patient names kept away from the model
- The clinician approves anything that reaches the chart
- Runs in your cloud, under a BAA when the work needs one
Three ways to start, from $5,000: Build Sprint · Planning Sprint · AI Scorecard
app.acmedental.example / calls / yesterday
Acme Dental · Yesterday's calls
AI checkedRebookly by Datics AI · Try it step by step →
Illustrative demo on a fictional practice. Not client work.
Who it is for
Built for established healthcare SaaS.
Each page leads with the modules that fit that kind of platform, the questions its buyers ask and where most teams start.
Dental and veterinary practice software
Specialty clinic and patient intake platforms
Healthcare data and analytics platforms
Do not see your platform here? We likely cover it.
Book a 30-minute Product ReviewWhy healthcare products stall on AI
What gets in the way, and how we handle it.
- 01
Patient data cannot go to a model vendor
Identifiers stay out of the model
We strip names and dates of birth before any AI call, and run the work inside your own HIPAA cloud account.
- 02
Clinicians will not accept unsupervised AI in the chart
Drafts wait for the clinician
AI drafts the note or summary; the dentist, vet or physician edits and approves it before anything is filed.
- 03
The data AI needs arrives from systems you do not control
Validate before it becomes a record
Each event or record is checked against a typed model before it is stored, and providers are verified against the NPI Registry.
- 04
A pilot that worked in one practice breaks in fifty
Built for many practices from the start
Practice isolation, roles and per-provider billing come before the screens, so one practice never sees another.
- 05
Nobody can say what it costs per practice
Cost measured in the Sprint
Every Build Sprint ends with the cost to serve per practice or per provider, on two models, and a packaging recommendation.
Why AI earns its place in your product
Grow revenue
Sell AI, do not just add it.
Price it per provider or as a paid AI tier, with a known cost per practice behind the price.
Keep practices
Less admin, every day.
Fewer forms retyped, fewer notes written after hours, fewer callers forgotten.
Pass review
Made for privacy review.
Short, true answers for your practices' and partners' security and HIPAA questions.
Modules by Datics AI
Start from work we have already delivered, not from zero.
Each module runs on a fictional practice, so you can see it before you buy. Each one builds on AI and integration work we have already delivered.
Patients answer before the visit. The physician starts with a summary.
Fits: Specialty clinic platforms, patient engagement and intake products, practice management software
Every call becomes a record. Every caller who did not book gets a follow-up.
Fits: Dental and veterinary practice software, practice communications and patient engagement platforms
The note is drafted during the visit and filed only after the doctor signs.
Fits: Dental and veterinary practice software, clinical documentation products, specialty EHRs
Staff ask in plain words. Answers come from your policies, with the source.
Fits: Practice management software, dental service organization platforms, practice operations tools
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
Your product connected to the practice systems behind every front desk.
Fits: Any healthcare software that needs data from practice systems
Intakelyby Datics AI
AI patient intake and visit summaries
Patients answer before the visit. The physician starts with a summary.
Fits: Specialty clinic platforms, patient engagement and intake products, practice management software
Rebooklyby Datics AI
AI call follow-up for dental and veterinary practices
Every call becomes a record. Every caller who did not book gets a follow-up.
Fits: Dental and veterinary practice software, practice communications and patient engagement platforms
Chartlyby Datics AI
AI clinical notes with clinician approval
The note is drafted during the visit and filed only after the doctor signs.
Fits: Dental and veterinary practice software, clinical documentation products, specialty EHRs
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
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
Connectlyby Datics AIService
Practice management, EHR and phone system integration
Your product connected to the practice systems behind every front desk.
Fits: Any healthcare software that needs data from practice systems
Also for your product
Your product, inside Claude and ChatGPT.
We build a connector so your users can ask their own AI assistant about their data in your product, each signed in with their own login and seeing only what they can already see. It starts read-only, only the fields you approve leave your product, and actions each user approves can come later.
How we build connectorsHow many open slots do we have tomorrow, by provider?
Nine: four with Dr. Reyes, five across the other two providers.
Proof
Our healthcare work.
Healthcare products we have shipped AI and integrations into.
57 featured AI case studies across our work
MIRA
Healthcare · AI patient intake
Pain physicians start each visit with an AI summary of the patient's history
Pain histories used to be taken in the room. Now patients answer adaptive questions first, by tap or voice, and AI drafts the summary.
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.
Peerlogic Technologies
Dental and veterinary · Call intake
Our engineers inside Peerlogic's team turn raw phone events into trusted call records
Each phone system reported calls its own way. Now raw events become validated records that Peerlogic's dental and vet call AI relies on.
More healthcare work
MIRA
Healthcare · Multi-clinic intake SaaS
Clinics sign up, pay per provider and run their own AI patient intake
The AI intake worked in three practices but was hard coded. Now any clinic signs up, pays per provider and runs it, and names never reach the model.
Dental clinical documentation AI company
Dental · Clinical note drafting
Dentists approve a clinical note drafted during the appointment, not rebuilt after it
Dentists rebuilt notes from memory after each visit. Now AI drafts the note during the appointment, and only the dentist can release it.
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.
“Amazing level of proficiency and responsiveness. We are looking forward to moving on to our next project!”
Soorena Khojasteh · Founder, MIRA
See the work“His engineers have a deep well of knowledge they can tap for tackling complex development problems.”
Jordan Emrie · Datascape, healthcare data consultancy
See the work
How it works
Three ways to start, each at a fixed price.
A 30-minute review tells you which one fits. Whichever you pick, you know the production price before you commit, and your fee counts toward it.
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.
Intakely · Rebookly · Chartly · Deskly · Paperly
- 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.
Need integrations first? Connectly covers PMS, EHR and phone integration. Ask in the Product Review.
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 dataIn AI and data since2018
- AWS: Select Tier Partner
- Anthropic: Partner · Claude models
- CopilotKit: Agent user interface
- LangGraph: Production agent engineering
- Databricks: Governed AI & agent workflows
- Cursor: Agentic development environment
- Microsoft Azure: Production AI delivery
- Google Cloud: Production AI delivery
AI shipped inside products for
Questions we hear on the first call
Straight answers before you book.
The questions healthcare product and engineering leaders ask most.
Do you need access to our production patient data?
No. Every Sprint and the AI Scorecard run on synthetic or de-identified data, production PHI stays in your cloud under your access controls, and code reaches your product as pull requests. In production we work only through access you grant, and you can revoke it at any time.
Will patient names or dates of birth reach the model?
Not unless you decide they must. We remove identifiers before any AI call by default, as we did for a multi-clinic intake product, and the data-flow sheet shows exactly what each model sees.
How do you handle HIPAA, and will you sign a BAA?
We work within your HIPAA requirements and sign a BAA when the work needs one. Compliance belongs to your complete product, contracts and policies, so we do not claim it for software alone. We build with approval steps, audit logs and practice isolation.
How do you stop AI writing something wrong into a patient record?
Nothing reaches the chart without the clinician's approval. Answers and drafts come from your sources and show them, and when the sources do not cover something the module says so instead of guessing. We measure all of it on your own cases before launch.
Which practice systems do you integrate with?
We have integrated with practice management systems such as Dentrix, OpenDental, Eaglesoft, Denticon, ezyVet and Vetspire, EHRs over HL7 and FHIR, and phone systems such as GoTo Connect, Jive, Netsapiens and Bandwidth. We scope yours in the Product Review.
Which AI models do you use, and do they train on our data?
Your choice of model and hosting, including Azure OpenAI and Amazon Bedrock inside your own account. Models run under your account's terms, such as Azure OpenAI or Amazon Bedrock, which do not use your prompts for training, and the Sprint Pack compares the cost on two models.
Why not build it with our own team?
Your team can build a demo. Shipping it into a live multi-practice product, inside your permissions, tested on your cases, with a cost per practice and privacy answers, is what we do, starting from engines we have already delivered. Your team reviews every pull request, and the code lives in your repository.
Who owns the code?
What we build for your product lives in your repository and ships under your name. The reusable engine underneath stays ours and is licensed to you; the terms are in your contract.
Do you have SOC 2?
Not yet. We work in your staging by pull request, under your accounts, and in production only through access you grant and can revoke.
Where are you based?
Datics is headquartered in Austin, Texas, with a named lead engineer and US-hours overlap on every engagement.
Healthcare insights
How we think about the hard parts.
Answers for product and engineering leaders, from the team that builds it.
Healthcare practices
How much time does AI clinical documentation save?
What AI clinical documentation saves practice teams, from JAMA and AMA-reported studies, and how to build it so notes get reviewed and data stays private.
Umair Majeed · Sep 2, 2026AI security and compliance
What does HIPAA AI compliance mean for software vendors?
HIPAA AI for software vendors: what the product company owns, what the engineering team builds, and how to keep patient identifiers away from models.
Umair Majeed · Oct 7, 2026RAG and AI assistants
How do you stop hallucination in AI document extraction?
AI document extraction from long documents gets reliable with type detection, retrieval per field, clear field definitions and empty values, not guesses.
Rana Umar Majeed · Sep 14, 2026AI agents
Where should human in the loop AI review happen?
Human in the loop AI works when review happens field by field, before anything ships. Learn where to place checkpoints and how to measure accuracy.
Rana Umar Majeed · Oct 16, 2026AI security and compliance
How do you enforce tenant isolation beyond database rows?
Tenant isolation beyond database rows means boundaries per field and per role, in caches, files, payments and jobs, so no tenant sees what another owns.
Rana Umar Majeed · Oct 29, 2026AI security and compliance
How do you build an AI audit trail you can reproduce?
An AI audit trail records who or what made each change, with which inputs and model, so reviewers can tell AI entries apart and reproduce any output.
Rana Umar Majeed · Sep 4, 2026See 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.
Own several healthcare software products? Datics for private equityCalls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.