19 Jul 2026AI Healthtech4 min readBy Tayyab Hanif
The best AI agency for a healthtech product is the one that talks about controls before features: PHI data flows, BAAs, audit trails, and what happens when the model is wrong about a patient. This guide compares seven agencies on that standard, with stated criteria, a snapshot table, and our own entry listed last with a disclosure.
Compare agency websites in this category and a pattern appears: the credible ones lead with named standards, PHI handling, and audit mechanics, while generalists lead with adjectives like "secure" and "trusted." That pattern is your first filter. The second is whether they can draw your PHI data flow on a whiteboard before quoting. The third is whether their AI experience is in production or in press releases. The list below applies those filters.
A healthcare-focused development firm that cites ISO 13485, ISO 27001, and HITRUST alignment in its public materials: the certification-led posture regulated buyers look for. The fit: clinical products where certified quality systems are a procurement requirement. The trade-off: that machinery is built for medical-device-grade work, more process than an early wellness MVP needs.
A US firm specialising in custom healthcare software, with public emphasis on PHI handling and medical billing integrations. The fit: provider workflows, billing, and systems that must speak to existing clinical infrastructure. The trade-off: verify AI/LLM depth for your use case, since the healthcare pedigree is stronger than the published AI casework.
Enterprise conversational-AI specialists with healthcare assistants in the portfolio. The fit: chat and voice front doors for large patient populations. The trade-off: enterprise engagement model; early-stage teams will be a small fish.
An AI-focused development shop with visible digital-health casework across patient apps and health data products. The fit: startups building consumer-facing AI health experiences. The trade-off: probe compliance depth per project, because consumer wellness and regulated PHI products have different bars.
A well-known enterprise AI builder with published healthcare projects among a broad portfolio. The fit: organisations wanting one vendor across several AI initiatives. The trade-off: breadth first, with healthtech as a practice area rather than the identity.
A development firm appearing in AI agency rankings with healthcare projects in the mix. The fit: budget-conscious builds across AI use cases. The trade-off: the same as any generalist, so make the compliance questions below non-negotiable.
Full disclosure: our list, our entry, same criteria. We build AI products for funded healthtech and wellness startups, including telehealth platforms, patient triage, and retrieval over clinical knowledge, with HIPAA-aware architecture designed in from the first sprint: PHI-conscious data flows, audit trails, and access controls, documented on our HIPAA compliance page. Independent signal: 4.6/5 across 58 verified client reviews on our public profile. Entry point: a fixed $499 Tech Audit, then fixed-scope builds of 6–14 weeks. Where we are not the fit: SaMD/medical-device firmware, FDA clearance programmes, or on-site enterprise teams.
| Agency | Best for | Compliance posture (as published) | Entry point | HQ |
|---|---|---|---|---|
| Glorium Technologies | Certified medical software | Cites ISO 13485, ISO 27001, HITRUST | Not published | United States |
| TATEEDA | Provider systems, PHI integrations | PHI handling, medical billing focus | Not published | United States |
| Master of Code | Patient-facing conversational AI | Enterprise security posture | Not published | Ukraine / US |
| Markovate | AI-first digital health apps | Per-project | Not published | United States |
| LeewayHertz | Enterprise AI platforms | Enterprise security posture | Not published | United States |
| SoluLab | Cost-flexible AI builds | Per-project | Not published | India / US |
| Robust Devs (us) | Funded HIPAA-aware AI MVPs | HIPAA-aware architecture from sprint one | $499 Tech Audit | United Kingdom |
Ask every shortlisted agency, us included: Will you sign a BAA, and does your hosting recommendation come with one? Draw my PHI data flow: where does patient data enter, where is it stored, what does the model see? What is in the audit trail when a clinician disputes an AI-assisted decision? How do you evaluate model behaviour on clinical content before and after each release? An agency that answers on a whiteboard is a partner; an agency that answers with a brochure is a risk. The official HHS HIPAA resources are the primary source for what the rules require.
If it touches PHI, the architecture needs to be HIPAA-aware from day one: encryption, access controls, BAAs with vendors, auditability. Formal compliance programmes mature as you grow, but data-flow decisions made in week one are the ones you cannot cheaply undo.
Only under the right agreements and architecture: BAA-covered services, PHI minimisation before anything reaches a model, and logging that proves what was shared. "We send the chart to the API" is not an architecture; de-identification and scoped retrieval are.
Compliance posture pushes healthtech builds toward the upper half of typical AI MVP budgets. The full driver-by-driver breakdown is in our AI MVP cost guide.
A scoped, HIPAA-aware MVP fits a 6–14 week fixed-scope build after discovery, with the compliance work running inside the build rather than after it.
Written by
Founder & CEO
Founder & CEO of Robust Devs. Leads delivery and works directly with every client, across AI marketing, healthtech, and fintech builds, and has done since 2019.
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