Healthcare
AI and software for healthcare — without patient data leaving your control.
We build healthcare software and AI that run inside your own cloud environment — with encryption, access controls, and audit trails designed in from the first architecture decision. Eighteen years of building software for sensitive data — applied to patient data.
- Built to HIPAA requirements
- Your cloud, your data
- Senior engineers only
Your cloud account
AWSAzureGoogle Cloud
Your documents
policies · claims · records · contracts
AI agent + knowledge base
model runs in your account · not trained on your data
Answer with sources
This claim meets the coverage terms in section 3.2. Recommend approval — route to a handler for sign-off.
Policy §3.2Claim form, p.2Human review
Public AI APIs stay outside the line. Prompts and documents never leave your environment.
18 yrs
Delivering software since 2008
HIPAA
Requirements designed in
4–6 wks
To a working AI pilot
ISO
27001:2022 certified
01The problem
Healthcare technology fails for different reasons
Most IT projects fail for predictable reasons. In healthcare, the reasons are different — and the consequences are bigger.
Challenge 01
Clinical workflows cannot be disrupted
A system that slows staff down by minutes per patient costs more than it saves. We map workflows with your team before designing anything.
Challenge 02
Public AI tools are a data risk
Pasting patient information into a public chatbot is a HIPAA problem. We deploy AI inside your own cloud account, so PHI never leaves your control.
Challenge 03
Audit requirements keep changing
The HIPAA Security Rule and OCR enforcement priorities evolve. We document safeguards as we build, so your next audit doesn't start from scratch.
Challenge 04
Staff burnout amplifies every problem
Any system that adds friction makes burnout worse. We design for the exhausted clinician at the end of a 12-hour shift, not the administrator during a demo.
Challenge 05
One vendor mistake is enough
Most breaches trace back to a misconfiguration or a vendor shortcut. Security controls are designed into our architecture — not added after launch.
02What we build
What we build for healthcare teams
Practical AI and software that saves staff time — deployed in your environment.
Private Knowledge Assistants
Staff ask questions in plain language and get answers from your policies, procedures, and payer rules — with sources cited, running in your own cloud.
Learn more →Document & Intake Automation
Extract and route information from referrals, intake forms, and prior-authorization paperwork so staff stop re-keying data.
Learn more →Patient-Facing Portals
Scheduling, forms, and status tracking for patients, built with access controls and audit trails from day one.
Data Platforms & Reporting
Bring operational data together for reporting and analytics, with role-based access to sensitive fields.
Learn more →System Integration
Connect existing systems through HL7 and FHIR APIs so information flows without manual copying.
Legacy Modernization
Move aging internal applications to modern, supportable technology without disrupting daily operations.
Learn more →03Why us
Why healthcare teams work with us
Not because of our technology. Because of how we handle sensitive data.
We architect for audits from day one
Encryption, audit trails, access controls, and Business Associate Agreement alignment are designed into the architecture before we write the first line of code.
Your data stays in your cloud
AI models and data pipelines run inside your own cloud account. No patient data is sent to public AI services.
Our security discipline comes from law enforcement
For 16 years we built law enforcement software to CJIS Security Policy requirements — one of the strictest data-security standards in the US. The same discipline protects patient data.
Real healthcare experience
We built Watermark Medical's home sleep-testing platform end to end — Wi-Fi data capture, analysis, reports, and doctor booking — under HIPAA requirements. We also built PeproTech's online ordering platform for life sciences researchers.
Read the Watermark Medical story →Senior engineers, architect oversight
A senior architect reviews the design of every engagement. You work with senior engineers — not a rotating junior bench.
See our case studies →04HIPAA safeguards
Built to HIPAA requirements. Documented for your audits.
Patient data (PHI) needs the highest level of protection. We design to HIPAA technical, administrative, and physical safeguards:
- AES-256 encryption at rest, TLS 1.2+ in transit
- Role-based access control (RBAC) with least privilege; MFA for all access
- Audit trails — who accessed what, when, and from where
- Automatic session timeout and secure disposal of PHI
- Business Associate Agreements (BAAs) signed where required
- Deployment in your own cloud account using HIPAA-eligible services
05Your journey
Where are you in your healthcare IT journey?
A typical path from foundation to optimization. Where are you today?
Stage 01
Foundation
- HIPAA safeguards review
- Integration planning
- A first AI pilot in 4–6 weeks
Stage 02
Expansion
- Patient and staff portals
- Document automation
- Analytics & reporting
Stage 03
Optimization
- AI across more workflows
- Managed AI operations
- Continuous improvement
Not sure where you are? Schedule a free strategy call →
06FAQ
FAQ for healthcare clients
We're a senior engineering team with hands-on leadership. Security is how we think — we've built software to HIPAA and CJIS Security Policy requirements for years — and we deploy AI inside your own cloud so patient data stays under your control. You work directly with the senior engineers who are accountable for the result.
Yes. We sign BAAs whenever our work involves protected health information.
We integrate through standard HL7 v2 and FHIR APIs. During discovery we confirm which integration options your EHR vendor supports and plan around them.
No. We deploy models through services that run inside your own cloud account, so prompts and data stay in your environment.
A focused AI pilot: 4–6 weeks. A portal or integration: 8–16 weeks. A larger platform: 4–6 months. We give you a fixed scope and timeline after discovery.
Yes. We have delivered healthcare work under HIPAA requirements and can arrange a reference conversation where our client agrees.
Evaluating healthcare AI or data modernization? Start here.
We'll help you assess feasibility, HIPAA implications, and expected operational impact — before any build discussion begins.