Healthcare AI development for hospitals, clinics, and medtech.

Aiinfox engagements are HIPAA-aligned for healthcare clients. BAAs are signed before any engagement touches PHI. Self-hosted Llama 3 deployments inside customer VPC are standard for zero data egress. Audit logs cover every model call. SOC 2 Type II is in progress. We work with US and international healthcare clients across hospital chains, clinics, healthtech SaaS, and medtech devices.

For HIPAA-scoped engagements, patient data never leaves your network. We deploy Llama 3 70B or 8B on vLLM inside your AWS, Azure, or GCP VPC, or on-prem on your hardware. Self-hosted vector store (pgvector inside your existing Postgres, or Qdrant) keeps retrieval local. Reference deployment: a medical-inquiry RAG agent running fully inside hospital VPC with zero internet egress.

Five layers. Hybrid retrieval grounds every answer in your clinical corpus. Required citations link every claim to a source document. A refusal layer activates explicitly on safety-critical categories (drug dosage, contraindications, triage) — the system says "I cannot answer — escalating to a clinician" rather than guessing. Confidence scoring routes low-confidence answers to human review. An eval harness blocks any change that regresses safety-critical accuracy.

Yes. We fine-tune open-weight models (Llama 3, Mistral) on de-identified clinical data via LoRA, running entirely inside your environment. Reference: a fine-tuned Llama 3.1 for healthcare inquiries deployed self-hosted in a customer VPC for zero data egress. Reproducible pipelines with versioned datasets and weights, re-runnable as your clinical guidelines evolve.

No. Every Aiinfox healthcare deployment is built so the AI assists, scribes, summarises, retrieves, and flags — but every clinical decision remains with the clinician. The system defers (explicit refusal) on safety-critical queries and routes to a human. This is not just compliance theatre — it is the only design that clinicians actually adopt long-term.

Six to eight weeks for a clinical chatbot or RAG agent pilot. Eight to twelve weeks for AI HMS implementation in a single facility (including migration from HL7 / FHIR / legacy HMS and clinician training). Twelve weeks for a fine-tuned healthcare LLM with curated training set and self-hosted deployment. Multi-facility rollouts replicate per site after the first.

Most healthcare AI v1 engagements at Aiinfox land between $40,000 and $180,000 fixed-price depending on regulatory scope, integration complexity, and whether fine-tuning is required. AI HMS deployments are priced per-bed or per-clinician with mid-size facilities landing between $1,800 and $6,500/month all-in. On-prem deployments include a one-time setup and an annual support agreement.

HL7 v2 and FHIR R4 for clinical interoperability — we migrate from and integrate with major EMR / HMS systems via these protocols. DICOM for imaging. ICD-10, SNOMED CT, RxNorm, LOINC for coding. HIPAA Privacy + Security rules for US deployments, GDPR for EU, DPDP for Indian clients. SOC 2 Type II in progress.