> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://imo.ferndocs.com/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://imo.ferndocs.com/_mcp/server.

# Solution Accelerators

Each accelerator includes production-ready code, deployment guides, and best
practices.

#### Ambient Listening

**Python · REST API** — Convert medical transcripts into structured clinical
data. Uses Entity Extraction, Precision Normalize, and Search & Capture to
turn patient-provider conversations into SOAP notes, then extract, normalize,
and code clinical entities.

*Real-time entity extraction · Normalization with enrichment · Automated clinical coding*

#### Real World Evidence

**Python · REST API** — Transform raw clinical data into clean, standardized
OMOP-ready datasets and precisely targeted patient cohorts using Precision
Normalize and Precision Set.

*IMO API integration · OMOP-ready output · Multi-source data support · Data lake integration*

#### Coding Intelligence

**Python** — Validate every diagnosis code against real-world billing rules,
flagging unspecified laterality, non-primary diagnoses, and CMS Excludes1
conflicts as they're entered.

*Real-time code validation · Billing accuracy checks · Multi-code system support*

#### Clinical NLP

**Python · REST API** — Turn unstructured clinical notes into an organised,
de-duplicated problem list. Identifies coded entities, groups them by
specialty, and flags duplicates, related conditions, and lapsed problems.

#### Precision Normalize with Cohorting

**Python · REST API** — Build reproducible patient cohorts from raw clinical
terminology. Standardizes terms to IMO lexical codes and FHIR-compliant
terminologies, applies inclusion/exclusion value set criteria, and exports a
matched cohort.

#### Precision Normalize with Enrichment

**Python · REST API** — Submit clinical terms alongside contextual metadata
and get richer, more precise normalized mappings — ideal for refining
ambiguous terms before cohort building or coding workflows.

#### Search and Capture

**Python · REST API** — The full clinical coding lifecycle, from interactive
term search and specialty grouping through duplicate detection and ICD-10-CM
coding rule validation.

#### Knowledge Graph Traversal

**Python · GraphQL API** — Walk from a raw lexical code to a fully navigated
concept hierarchy. Query code system mappings and surface the specificity
that unspecified codes leave on the table.

#### MCP Server through Databricks

**MCP · Databricks Marketplace** — Build an AI-powered diagnostic specificity
agent using Databricks and IMO Health's MCP Server, with a step-by-step guide
to creating, deploying, and publishing an IMO-enabled agent.

#### MCP Server through Microsoft Copilot Studio

**MCP · Microsoft Copilot Studio · Low code** — Create an IMO-enabled agent
that analyzes clinical documentation, identifies opportunities for diagnosis
refinement, and guides users toward greater specificity.

## Build with the SDKs

Several accelerators above call Precision Normalize directly over REST. In this
portal that API also ships as generated clients, so the same workflows can be
written in idiomatic TypeScript, Python, or Java with authentication and token
refresh handled for you.

#### [Client libraries](/sdks/overview)

TypeScript, Python, and Java SDKs with automatic OAuth token refresh.