Companion mobile apps
Native iOS and Android apps for patient-facing device pairing, data viewing, adherence tracking, and clinician communication. HealthKit and Google Fit integration. WCAG 2.2 accessibility.
Custom Software
AI Engineering for Medical Device Companies
Companion apps, device-to-cloud telemetry pipelines, AI clinical features, and FDA SaMD pathway support for medical device manufacturers. Built by the team that’s been integrating with hospital systems since 2013.
$45K Discovery · $95K Production-Ready · $145K FDA-pathway Pilot-Ready
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📌 Definition
AI for MedTech is the engineering of AI-augmented software for medical device companies — companion apps, device-to-cloud telemetry, clinician dashboards, AI clinical features, and FDA SaMD pathway support. Modern 2026 MedTech AI deployments require BAA-eligible inference paths, FDA SaMD documentation patterns, HL7/FHIR integration with hospital EHR systems, MDR/IVDR-compatible architecture for EU expansion, and SOC 2 plus HITRUST audit-ready infrastructure. Productized fixed-price tiers: $45K (4-week Discovery), $95K (8-week Production-Ready), $145K (12-week Pilot-Ready with FDA SaMD pathway scoping).
What we build for MedTech companies
Device-to-cloud telemetry pipelines
High-throughput, low-latency telemetry from device firmware to cloud backend. Edge processing, batched sync, offline buffering. HIPAA-compliant cloud (AWS, Azure, GCP).
Clinician dashboards
Web dashboards for clinical teams monitoring device data — RPM streams, alerts, intervention queues, population-level views. Role-based access, audit logging.
AI clinical features
Predictive deterioration, anomaly detection, personalized regimen recommendations, clinical decision support. RAG-grounded, citation-traceable, override-and-audit-logged.
FDA SaMD pathway support
$30K productized FDA SaMD pathway assessment. Predicate device research, risk classification, design history file structure, software-of-unknown-provenance (SOUP) documentation.
EHR integration
FHIR R4 and HL7 v2 integration via Mirth Connect. Read device data into Epic, Cerner-Oracle, Athena, Allscripts. Write device-generated alerts back to clinician inbox.
Regulatory documentation infrastructure
IEC 62304 software life cycle documentation, ISO 14971 risk management documentation, MDR/IVDR-compatible technical files for EU expansion.
MLOps for medical devices
Model versioning, drift monitoring, locked vs adaptive model deployment, FDA-aligned Predetermined Change Control Plans (PCCP).
MedTech AI pricing · 2026
What’s included in every MedTech engagement
- HIPAA-compliant architecture from day 1 — encryption at rest and in transit, role-based access, audit logging
- BAA-covered AI providers (OpenAI, Anthropic, AWS Bedrock, Google)
- IEC 62304 software life cycle documentation patterns
- ISO 14971 risk management documentation patterns
- MDR/IVDR-compatible technical file structure for EU expansion
- FHIR R4 and HL7 v2 integration with hospital EHR systems
- Native iOS and Android plus responsive web for clinician dashboards
- HealthKit, Google Fit, and Bluetooth Low Energy device pairing patterns
- Audit logging on every model output and clinical action
- Override-and-audit UX on every clinical AI feature
- SOC 2 Type II and HITRUST audit-ready documentation
- Pre-signed BAA templates with major cloud and AI providers
Common MedTech AI use cases
Use case 1 · Continuous monitoring devices
RPM streams (cardiac, glucose, respiratory, sleep) plus AI deterioration prediction. Tiered escalation to clinical team. Common in cardiology, endocrinology, sleep medicine.
Use case 2 · Diagnostic devices
Imaging devices, dermatoscopes, retinal cameras, point-of-care diagnostics. AI triage or assist features. Requires FDA SaMD pathway.
Use case 3 · Therapeutic devices
Infusion pumps, insulin pumps, neurostimulators, ventilators. AI-driven personalization of therapy. Requires FDA SaMD pathway.
Use case 4 · Surgical robotics + AR
Surgical robotics, AR-guided procedures, AI overlays. Real-time inference on intraoperative data. Latency-critical infrastructure.
Use case 5 · Population-level analytics
Aggregated device data across patient cohorts for clinical research, real-world evidence generation, and post-market surveillance.
Production reality
Ship MedTech AI without breaking FDA pathway
Free 30-min architecture call. We’ll scope your AI feature, FDA pathway requirements, and the right tier for your device class.
FAQs
FAQ
It depends on whether the AI feature diagnoses, screens, or directly influences treatment decisions. Imaging AI, autonomous diagnosis, and clinical-decision-mandating AI usually require FDA SaMD pathway (510(k), De Novo, or PMA). Companion apps, adherence tracking, and patient-facing dashboards usually don’t. We provide a productized $30K FDA SaMD pathway assessment on every engagement where this is a question.
Yes. Every MedTech engagement we ship includes IEC 62304 software life cycle documentation, ISO 14971 risk management documentation, and SOUP documentation. We’ve shipped engagements that passed FDA 510(k) review and EU MDR notified body review.
Same as our hospital engagements. Pre-signed BAA templates with OpenAI, Anthropic, AWS Bedrock, and Google. Zero-data-retention configuration verified in writing. PHI flowing through inference paths is BAA-covered from day 1. Audit logging on every model output.
Yes. We use FHIR R4 and HL7 v2 via Mirth Connect for bidirectional integration with Epic, Cerner-Oracle, Athena, Allscripts. Device data writes into the EHR; clinical context reads from the EHR into the device’s clinician dashboard.
MDR/IVDR-compatible architecture and documentation patterns are included in every MedTech engagement. We can ship US-only first and add EU expansion later, or build for both markets from day 1. The 510(k) and MDR pathways have overlapping but non-identical documentation requirements; we scope per engagement.
4-week Discovery, 8-week Production-Ready, 12-week Pilot-Ready. Full production deployment with FDA SaMD pathway adds 16–32 weeks depending on device class and clinical evidence requirements. EU MDR adds 8–16 weeks for technical file preparation and notified body review prep.
Yes. The Discovery Sprint is sized for early-stage MedTech companies — $45K, 4 weeks, working concept on real data, written go/no-go for production. Many seed-stage MedTech engagements start with Discovery and decide whether to proceed based on the prototype outcome.