Atrium
Compact. Compliant. Customizable.

Atrium: Custom Small Language ModelFor Healthcare

Atrium is a healthcare-tuned Small Language Model (SLM ≤10B params) that performs clinical reasoning, coding assistance, chart summarization, medical imaging interpretation, and retrieval-augmented generation (RAG) while protecting PHI.

Clinical Intelligence

Draft evidence-linked differentials; summarize encounters; structure SOAP/H&P.

Smart Coding

Suggest ICD-10 / CPT / HCPCS with explanation, confidence, and source links.

Knowledge Retrieval

RAG over clinical guidelines, PubMed/PMC, payer policies, formularies, and SOPs.

Multimodal Ready

Interpret imaging metadata with optional vision adapters and radiology language.

Built For
Physicians
Nurses
Billing Teams
Care Coordinators
Researchers
Health IT
Overview

What is Atrium?

Atrium is a multimodal, healthcare-specific SLM that can:

Clinical Documentation

Draft evidence-linked differentials; summarize encounters; structure SOAP/H&P.

Medical Coding

Suggest ICD-10 / CPT / HCPCS with explanation, confidence, and source links.

Knowledge Retrieval

Perform RAG with a built-in agent over clinical guidelines, PubMed/PMC, payer policies, formularies, SOPs, and your local policy binders.

Imaging Interpretation

Interpret imaging metadata (with optional vision adapters) and link to radiology language.

Integration

Integrate with EHRs, CRMs, billing, and analytics through standards-based APIs.

Optimized For
Accuracy
Privacy
Auditability
Low Latency
Easy Domain Adaptation
Use Cases

Who Uses Atrium?

Clinicians

Encounter summaries, guideline lookups, order-set cross-checks.

Care Teams & Support Staff

Intake triage, referral letters, prior-auth packets.

Billing & RCM

Code suggestions, claim narratives, denial appeal drafting.

Researchers & QI

Cohort extraction, literature synthesis, protocol drafting.

Health IT

Safe automation across service lines with fine-grained controls.

Patients

Interpret medical data, understand test results, and access personalized health insights.

Training Data

Data Sources

Atrium's knowledge base combines public medical literature, de-identified clinical datasets, and your proprietary EHR data.

PubMed / PMC

Example Use

Literature-based clinical reasoning, evidence synthesis

MIMIC-III / MIMIC-IV

Example Use

ICU case studies, clinical note templates

eICU-CRD

Example Use

Multi-center critical care analytics

i2b2 NLP Datasets

Example Use

Named entity recognition (medications, diagnoses)

MedQuAD

Example Use

Consumer health Q&A, patient education

HCUP (NIS, NEDS)

Example Use

Population-level coding & billing patterns

Customer EHR / Logs

Example Use

Site-specific workflows, local protocols, formularies

Payer Guidelines

Example Use

Prior-auth criteria, coverage policies

Connect your own policy manuals, SOPs, and formularies via our ingestion API—the built-in RAG agent will automatically index and query them.

Integration

Interoperability

Atrium fits seamlessly into your existing tech stack:

Multi-Model Orchestration

Atrium can hand off to GPT-5, Claude, Med-PaLM, or other frontier LLMs when a task exceeds its own parameters—then synthesize the result.

API-First Design

RESTful endpoints for text generation, RAG queries, coding suggestions, and image interpretation. Integrate with EHRs, CRMs, or custom workflows.

FHIR & HL7 Support

Ingest and produce FHIR resources (Patient, Encounter, Observation, etc.) and parse HL7v2 messages for seamless interoperability.

Federated Deployment

Deploy on-prem, in your VPC, or via our secure cloud. Maintain full data sovereignty while benefiting from model updates.

Standards-Based: Works with Epic, Cerner, Allscripts, and any system supporting FHIR or HL7.

Why SLM

The Power of Small Language Models

Smaller doesn't mean less capable for domain-specific tasks:

Faster Response Times

Smaller models run locally or in lightweight cloud instances, delivering sub-second inference for real-time clinical workflows.

Enhanced Privacy

Deploy on-premises or in your VPC to keep PHI within your security perimeter, meeting HIPAA and other compliance requirements.

Lower Operating Costs

Reduced compute requirements mean lower infrastructure costs and more predictable pricing at scale.

Domain-Specific Excellence

Fine-tuned on healthcare data, SLMs can outperform general-purpose LLMs on specialized medical tasks.

Target Metrics & Validation
92–97%
Clinical Accuracy
on MedQA, PubMedQA, and USMLE Step-style tasks
~0.88
ICD-10 F1
across 10k+ billing scenarios
<200ms
Median Latency
for typical clinical queries (CPU or 1× GPU)
>85%
RAG Retrieval Precision
at k=5 over indexed guidelines and literature
Technical Overview

Architecture at a Glance

Atrium's modular architecture combines a healthcare-tuned SLM with a built-in RAG agent, optional frontier LLM handoff, and standards-based I/O.

Step 1

User Query

Input
Parsed Request

Clinician or system submits a prompt (text, FHIR, or image metadata).

Step 2

Intent Classification

Raw Query
Task Type

Atrium determines task type (documentation, coding, retrieval, etc.).

Step 3

RAG Agent (if needed)

Query
Enriched Context

Query external knowledge bases (PubMed, EHR, guidelines) and retrieve context.

Step 4

SLM Inference

Context + Query
Generated Response

Generate response using healthcare-tuned parameters and retrieved context.

Step 5

Confidence & Citations

Raw Output
Validated Response

Attach source links, confidence scores, and audit metadata.

Step 6

Handoff (optional)

SLM Response
LLM Enhanced

If task exceeds SLM capability, route to frontier LLM and merge results.

Step 7

Output

Processed Data
Structured Format

Return structured response (JSON, FHIR, Markdown, or plain text).

Technical Note: Atrium's RAG agent uses semantic search (FAISS, pgvector, or Weaviate) to retrieve relevant context before inference. The handoff layer (Step 6) is optional and configurable—disable it for air-gapped deployments.

Security & Privacy

Security & Compliance

Atrium is designed from the ground up to meet healthcare's stringent security, privacy, and compliance requirements.

HIPAA-Ready Infrastructure

Encryption at rest (AES-256) and in transit (TLS 1.3). BAA templates and audit logging included. Deploy on-prem or in your HIPAA-compliant VPC.

Role-Based Access Control (RBAC)

Granular permissions for clinicians, billing staff, researchers, and IT. Control who can query what data sources and approve/reject model suggestions.

Audit Trails & Provenance

Every inference is logged with user ID, timestamp, input hash, output, confidence scores, and source citations. Meet compliance and liability requirements.

De-Identification & Redaction

Built-in NER for PHI (names, MRNs, dates). Automatically redact or pseudonymize sensitive fields before logging or exporting data.

Compliance & Certifications

HIPAA
SOC 2 Type II
GDPR-Ready
HL7 FHIR R4
Questions

Frequently Asked Questions

Common questions about Atrium's capabilities, deployment, and compliance.

Atrium is optimized for healthcare-specific workflows and benchmarks. While GPT-5 and Claude excel at general reasoning, Atrium offers lower latency, on-prem deployment, and domain-tuned accuracy for clinical documentation, coding, and retrieval tasks. For complex edge cases, Atrium can hand off to frontier LLMs and synthesize the result.

Yes. Atrium supports fine-tuning via LoRA, QLoRA, or full-parameter training. You can adapt it to your specialty (e.g., oncology, cardiology), local protocols, formularies, or preferred documentation styles. Our team provides tooling and support for custom training runs.

Atrium can be deployed on-prem (your own servers), in your VPC (AWS, Azure, GCP), or via our secure managed cloud. All options support BAAs and HIPAA-compliant configurations. Choose the deployment model that fits your security and latency requirements.

Yes. Atrium supports standard healthcare data formats (HL7 v2, FHIR R4, CDA) and can integrate with major EHR platforms including Epic, Cerner, Meditech, Allscripts, and athenahealth via API connections. We provide pre-built connectors for common systems and can develop custom integrations for proprietary platforms. No code changes are required in your EHR—Atrium operates as a middleware layer.

Implementation timelines vary by scope: Proof-of-concept (single department, basic workflows): 2-4 weeks. Pilot deployment (multi-department, custom fine-tuning): 6-8 weeks. Full production rollout (organization-wide, integrated workflows): 3-4 months. This includes environment setup, data integration, user training, and validation testing. Our team manages the technical implementation while your IT and clinical teams focus on workflow optimization.

Atrium is designed for HIPAA compliance from the ground up. PHI never leaves your security perimeter in on-prem deployments. For cloud deployments, data is encrypted in transit (TLS 1.3) and at rest (AES-256), with comprehensive audit logging of all access and operations. We sign Business Associate Agreements (BAAs) and support additional frameworks including HITRUST, SOC 2 Type II, and GDPR. Role-based access controls ensure only authorized users can access specific data types.

Yes. Atrium's SLM architecture is specifically designed for edge and offline deployment. Unlike cloud-dependent LLMs, Atrium runs entirely on your local infrastructure without internet connectivity. The optional frontier LLM handoff feature can be disabled for air-gapped environments. You'll still get full clinical reasoning, coding assistance, and RAG capabilities using only your local knowledge bases.

Atrium automates multiple clinical workflows: Clinical Documentation: Auto-generate SOAP notes, H&P summaries, discharge summaries from voice or text input. Medical Coding: Suggest ICD-10/CPT codes with evidence and confidence scores. Prior Authorization: Draft PA request narratives with supporting clinical evidence. Chart Review: Extract key findings, medication lists, problem lists from unstructured notes. Literature Search: Query PubMed/clinical guidelines and synthesize evidence-based recommendations. Referral Letters: Generate specialty referrals with relevant history and diagnostic reasoning.

Atrium is multimodal-ready and can interpret imaging metadata (DICOM headers, radiology reports) and integrate with vision adapters for preliminary image analysis. While Atrium doesn't replace radiologists, it can assist with: Pre-populating reports from imaging findings, Cross-referencing imaging results with clinical history, Flagging critical findings for urgent review, Suggesting relevant follow-up imaging protocols. For deep image analysis (lesion detection, segmentation), Atrium can integrate with specialized vision models and synthesize results.

No. Atrium is a clinical decision-support tool, not a medical device. It does not diagnose, treat, or make autonomous clinical decisions. All outputs must be reviewed and validated by qualified clinicians. Regulatory requirements vary by jurisdiction and use case—consult your compliance team.

Contact us via the form below to schedule a demo or proof-of-concept. We'll work with you to understand your workflows, data sources, and compliance requirements, then configure a pilot deployment. Most POCs are up and running within 2–4 weeks.

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