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AKASA builds custom LLMs for health systems to automate revenue cycle workflows—prior authorization, clinical documentation improvement, inpatient coding, and denials appeals. The stack is data-heavy (Kubernetes, dbt, Redshift, PostgreSQL, Prefect) with Llama and Claude at the core, revealing a company operating at the intersection of healthcare data pipelines and large-language-model deployment. The hiring mix is engineering-dominant with significant data infrastructure investment, reflecting the complexity of building production ML systems that must integrate with clinical workflows and regulatory constraints.
Tech Stack 17 technologies
Core StackKubernetes Terraform GitHub dbt Redshift Python PostgreSQL Prefect Grafana AWS CloudWatch SQL Llama AWS SQS FHIR HL7 Claude
What AKASA Is Building
◆Challenges
- Improving clinical documentation accuracy
- Streamlining operations
- Financial integrity
- Improving clinical quality
- Streamlining healthcare revenue cycle
- Improving visibility into system behavior
- Enabling sales teams
- Scaling gtm strategy
- Missing diagnosis identification
- Capturing patient clinical journey
▲Active Projects
- Dbt pipeline development
- In-app dashboarding for product development
- Clinical documentation and medical coding suite
- Core data platform infrastructure and tooling
- Large-scale healthcare ml solutions
- Ongoing product maintenance
- Ci/cd pipeline automation
- Product positioning and launch strategy
- Sales enablement materials
- Market insights analysis
Hiring Activity
Steady15 roles · 5 in 30d
Department
Seniority
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