AI Medical Coding Software
Automate ICD-10 and ICD-11 diagnosis coding from clinical notes. AutoICD uses medical NLP to extract conditions, match codes, and flag negated findings, in seconds, not hours.
Why AI for Medical Coding?
Manual ICD-10 coding is slow, error-prone, and hard to scale. AI medical coding automates the routine work so your team can focus on complex cases and quality review.
Faster Than Manual Coding
AI processes clinical notes in seconds, not minutes. Reduce turnaround time from hours to moments and accelerate your revenue cycle.
Fewer Coding Errors
Medical NLP trained on clinical language catches diagnoses that manual review can miss. Confidence scores help coders prioritize review.
Handles Complex Documentation
Negation detection, abbreviation expansion, spell correction, and clinical context understanding handle the messiness of real-world notes.
Full ICD-10-CM & ICD-11 Coverage
74,000+ ICD-10-CM codes and 17,000+ ICD-11 codes with SNOMED CT and UMLS cross-references for interoperability.
HIPAA Compliant
Patient data is processed in memory only, never stored, logged, or used for training. All data encrypted in transit. BAAs available.
Easy Integration
REST API with TypeScript and Python SDKs. MCP server for AI assistants. Interactive playground for non-technical users.
How AI Medical Coding Works
Send clinical text (progress notes, discharge summaries, consult reports) to the API.
Medical NLP identifies every diagnosis, symptom, and condition in the text.
Each finding is matched against 74,000+ ICD-10-CM codes using medical embeddings enriched with SNOMED CT and UMLS synonyms.
Results include ranked code candidates with confidence scores, negation flags, and clinical context.
Who Uses AI Medical Coding?
Clinics & Practices
Code encounter notes at the point of care. Reduce claim denials and speed up reimbursement without adding headcount.
Billing & RCM Teams
Automate first-pass coding to let certified coders focus on complex cases and audits instead of routine assignments.
Health Tech Developers
Embed AI medical coding into your EHR, telehealth, or billing platform with a simple API call.
Clinical Research
Standardize diagnosis data across study cohorts by converting free-text notes to structured ICD-10 codes at scale.
AutoICD vs. General-Purpose LLMs for ICD-10 Coding
How does a purpose-built medical coding API compare to using general-purpose LLMs like ChatGPT, Claude, or Gemini?
| General-Purpose LLMs | AutoICD API | |
|---|---|---|
| Speed | Seconds per request, slower at scale | Sub-second structured response |
| Scalability | Rate limits and token costs grow fast | Unlimited volume, flat per-request pricing |
| Accuracy | May hallucinate non-existent codes | Verified 2025 ICD-10-CM set (74,000+ codes) |
| Consistency | Non-deterministic, different answer each time | Deterministic results for the same input |
| Output format | Requires prompt engineering for structured output | Structured JSON with codes, scores, and flags |
| HIPAA compliance | Patient data sent to general-purpose AI providers | PHI processed in memory only, never stored |
| Integration | Custom prompt chains and output parsing | REST API, TypeScript SDK, Python SDK, MCP |
| Cost at scale | Token-based pricing adds up fast | Predictable per-request pricing |
| Confidence scoring | No confidence metrics | Similarity score + confidence level on every code |
| Interoperability | No standard terminology mappings | SNOMED CT and UMLS cross-references built in |
LLMs are powerful general tools, but medical coding requires verified code sets, structured output, and clinical precision. AutoICD is purpose-built for this, no prompt engineering needed.
Try AI Medical Coding Free
7-day free trial with 100 requests per day. No credit card required.
Or explore: ICD-10 Coding API · PHI De-identification · HIPAA Compliance · ICD-10 Code Directory