Amazon SageMaker
Microsoft Azure ML
Google Vertex AI
Featured partners
See how our healthcare AI agent development company covers strategy, engineering, integration, and validation across your clinical stack
We build custom healthcare AI agents trained on your own clinical data and workflows, so every agent handles a real task and knows all needed context to return effective results.
Our healthcare AI integration services wire agents into Epic, Cerner, claims engines, and scheduling tools over HL7 FHIR without moving patient data offsite.
Our healthcare AI consulting services score agent use cases for your clinical workflows by payback and set guardrails your compliance team will approve before any build starts.
We ship a working healthcare agent on one narrow workflow first, so you can get and review real measured results before funding a full rollout across departments.
Each agent below owns one clinical or administrative job and logs every action it takes for review
Autonomous coding & billing
The agent assigns ICD-10 and CPT codes straight from clinical notes, then routes low-confidence charts to a human coder.
Clinical documentation
The agent drafts visit notes from ambient audio and structured vitals, then writes them back into the patient chart.
Personalized treatment
The agent ranks guideline-based options for a physician to accept or override, and it stops short of autonomous prescribing.
Clinical workflow automation
The agent runs multi-step admin work across scheduling and referrals, and it escalates to staff when a rule requires review.
Medical data triage and routing
The agent classifies inbound faxes, lab results, referrals, and portal messages, then routes each item to the right care team.
Patient assistants
The agent answers patient questions by chat or voice around the clock and updates appointments in your scheduling system.
Registry submission
The agent pulls measure data from charts and prepares registry submissions for your quality team to approve.
Prior authorization and claims
The agent assembles payer packets from chart data and tracks each submission until an approval or a denial lands.
We help healthcare organizations identify and build AI agents that fit existing clinical workflows and deliver results their teams can measure
Germany
Healthcare
Challenges solved with of a health insurance claims agent:
Learn about Cleveroad’s expertise in Projects Portfolio
in Projects Portfolio
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DenmarkCTPO of Penneo A/S
"Cleveroad proved to be a reliable partner in helping augment our internal team with skilled technical specialists in cloud infrastructure."
We approach every AI agent development in four main stages, focused on creating autonomous agents considering healthcare requirements
Our analysts map the target workflow with your coders and clinicians, step by step. You leave with a scoped use case and success criteria your board can sign off on.
We pull the clinical records the agent needs and strip identifiers before any model sees them. Your data team reviews the pipeline before a single prompt runs in production.
The first agent goes live in one department under clinician review, with results tracked against the baseline you set. You approve rollout from measured numbers.
We extend the agent department by department and train the staff working beside it. Dashboards track accuracy, escalation rates, model drift, and cost per task after go-live.
Our analysts map the target workflow with your coders and clinicians, step by step. You leave with a scoped use case and success criteria your board can sign off on.
We pull the clinical records the agent needs and strip identifiers before any model sees them. Your data team reviews the pipeline before a single prompt runs in production.
The first agent goes live in one department under clinician review, with results tracked against the baseline you set. You approve rollout from measured numbers.
We extend the agent department by department and train the staff working beside it. Dashboards track accuracy, escalation rates, model drift, and cost per task after go-live.
Below are the agentic AI building blocks behind every healthcare agent we ship, and what each one handles in production
Chain-of-thought planning for multi-step clinical tasks
Model choice matched to task and budget
Fine-tuning on your own medical corpus
A supervisor agent assigns every subtask
Shared state passed across agent handoffs
Retry and fallback paths for each step
Vector search over your clinical documents
Citations back to the source record
Incremental reindexing without a full rebuild
Medical entity and billing code extraction
Mapping to SNOMED CT and LOINC
De-identification of records before model calls
HL7 FHIR and HL7 v2 connectors
Function calling against typed API schemas
Scoped credentials for each agent action
Approval gates on every high-risk action
Full audit trail behind each decision
Prompt-injection and PHI leak checks on output
We offer flexible engagement options from a classic human team to AI-native squad. Pick the model that matches your scope and budget
The dependable, human-led baseline suited to any kind of project.
Development budget
Team composition
Iterative delivery
Spec evolves during delivery
Write a sprint scope, deliver it, try it, then revise the spec or functionality.
Best for
Flexible-scope projects where each iteration reshapes the plan as you go
Your familiar full-stack squad, accelerated with AI support in every role.
Development budget
Team composition
Iterative delivery
Spec evolves during delivery
The same write-deliver-review sprint repeats, just accelerated with AI.
Best for
Brownfield projects that need fast iteration without locking scope too early
A minimal lean team with maximum AI leverage and strict human oversight.
Development budget
Team composition
AI Solution Architect. Owns the approved spec and the architecture the build follows
Prompt Engineer. Turns the spec into precise prompts and guardrails for AI code generation
AI Product Owner. Owns milestones and acceptance against the fixed spec
Milestone delivery
Spec locked before delivery
Approve once upfront. The spec becomes the source of truth for milestones.
Best for
MVPs and greenfield projects with fixed scope and milestone-driven delivery
Below is the stack we use for healthcare AI agent development, from clinical integrations to model serving and cloud
Epic
Cerner
Meditech
Veradigm
Athenahealth
HL7 FHIR R4
HL7 v2.x
DICOM
C-CDA
X12 EDI 837/835
Zoom for Healthcare
Twilio
Vonage
Amazon Chime SDK
Okta
Auth0
SMART on FHIR
SAML 2.0
OAuth 2.0
Apple HealthKit
Google Health Connect
Fitbit API
Withings API
Availity
Waystar
Stripe
Braintree
LangChain
LangGraph
AutoGen
CrewAI
OpenAI
Anthropic Claude
Amazon Bedrock AgentCore
Vertex AI Agent Builder
Azure AI Foundry
PyTorch
TensorFlow
Amazon SageMaker
MLflow
Weights & Biases
Pinecone
pgvector
Weaviate
LlamaIndex
AWS
Microsoft Azure
Google Cloud
Docker
Kubernetes
Amazon ECS
Terraform
Jenkins
GitLab CI
GitHub Actions
Prometheus
Grafana
OpenTelemetry
Langfuse
React
Vue.js
TypeScript
Next.js
Node.js
Python
.NET
C#
PostgreSQL
MySQL
BigQuery
GraphQL
REST
Swift
Objective-C
SwiftUI
Kotlin
Java
Jetpack Compose
Flutter
React Native
We keep deepening our expertise to meet your highest expectations and build business innovative products
ISO 27001
Information Security Management System
ISO 9001
Quality Management Systems
AWS
Select Partner Tier
Anthropic
Certified in the Claude Partner Network
AWS
Solutions Architect, Associate
AWS
SysOps Administrator, Associate
Our healthcare AI agents ship against the rules your auditors check, from privacy law to clinical data standards
70 clutch reviews
4.9
Award
Clutch 1000 Service Providers, 2024 Global
Award
Clutch Spring Award, 2025 Global
Ranking
Top AI Company,
2025 Award
Ranking
Top Software Developers, 2025 Award
Ranking
Top Web Developers, 2025 Award
Ranking
Top Staff Augmentation Company in USA, 2025 Award
Four reasons healthcare companies pick Cleveroad as their AI agent development partner, backed by 15 years of delivery
Our AI engineers build agentic systems on LangGraph, Amazon Bedrock AgentCore, Vertex AI Agent Builder, and OpenAI AgentKit. As an AWS Select Tier Partner, we pair that with SageMaker and Textract work that shortens the path from pilot to production.
Since 2011 we have delivered EHR platforms, remote patient monitoring systems, telemedicine products, and a healthcare LMS. ISO 9001 and ISO 27001 certificates back the quality and security processes your compliance team will audit.
One team covers the whole path: AI consulting, proof of concept, agent engineering, clinical integration, and post-release support. You brief a single vendor instead of coordinating a strategy consultancy and two separate engineering shops.
Our engineers have wired products into Epic, Cerner, laboratory systems, and claims clearinghouses over HL7 FHIR and HL7 v2 interfaces. Agents then read and write real patient data without a parallel database or a manual export step.
