Full-Time
Healthcare RCM automation using AI
$180k - $220k/yr
San Francisco, CA, USA
Hybrid
Weekly on-site Wednesdays required; hybrid with remote work
AKASA uses computer vision-based RPA, machine learning, and human-in-the-loop workflows to automate Revenue Cycle Management in healthcare. The platform analyzes clinical and administrative documents, extracts data, applies ML decisions, and uses robotic automation to complete tasks within healthcare IT systems, with humans reviewing uncertain outcomes to ensure accuracy. This end-to-end solution aims to reduce errors, increase transparency, and scale RCM, delivering measurable financial gains for providers. By specializing in healthcare, AKASA differentiates itself from generic automation tools and has demonstrated impact, such as a $30M gross yield increase at Methodist Health System.
Company Size
201-500
Company Stage
Series C
Total Funding
$205M
Headquarters
San Francisco, California
Founded
2018
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Flexible vacation policy.
Generous coverage for health, dental, and vision insurance.
Free membership to One Medical for you and your family.
Health FSA account.
Full employee coverage for life insurance.
401K plan.
AKASA Launches GenAI-Powered CDI Optimizer to Enhance Clinical Documentation Integrity. by Jasmine Pennic 05/05/2025 Leave a Comment. What You Should Know: – AKASA, the preeminent provider of generative AI (GenAI) solutions for the healthcare revenue cycle, today announced the launch of AKASA CDI Optimizer™. – The new GenAI assistant is designed to help healthcare organizations significantly enhance clinical documentation integrity (CDI), improve compliance, and ensure the full clinical picture is captured for every patient encounter.Addressing Mid-Cycle Revenue Cycle ChallengesThe launch of CDI Optimizer comes as healthcare provider organizations face mounting pressures within their mid-cycle operations – the crucial steps encompassing clinical documentation, coding, and compliance. Factors like rising denial rates, constantly evolving regulatory requirements, and persistent staffing shortages challenge traditional CDI processes. AKASA notes that many health systems still depend on manual chart reviews or older, rules-based systems, which can often miss crucial revenue opportunities and fail to capture necessary quality and compliance metrics.Leveraging Generative AI for Deeper InsightsCDI Optimizer utilizes clinically trained large language models (LLMs) – a form of generative AI – to automatically review 100% of inpatient encounters across all service lines. This AI-driven approach allows the tool to identify documentation gaps and surface high-impact query opportunities that might be missed by other methods.“CDI Optimizer is more than a new product — it’s a strategic leap forward for the mid-cycle,” said Malinka Walaliyadde, CEO and co-founder of AKASA
What You Should Know:– Cleveland Clinic and AKASA have established a strategic collaboration to deploy generative AI tools to support efficient and accurate medical coding practices.– Through this partnership, Cleveland Clinic will apply multiple AKASA AI-powered tools during the mid-revenue cycle – the phase between patient care and billing, where documentation and coding occur – across its U.S. locations.Cleveland Clinic Advances Revenue Cycle Operations with AI-Powered Coding and Documentation ToolsCleveland Clinic, a nonprofit multispecialty academic medical center based in Cleveland, Ohio, continues to drive healthcare innovation by integrating clinical care, research, and education. Founded in 1921 by four physicians dedicated to cooperation, compassion, and innovation, the institution remains a leader in delivering outstanding patient care.Reflecting the complexity of patient care through accurate documentation and coding has long been a time-intensive task. Revenue cycle staff at Cleveland Clinic typically review over 100 clinical documents per case—including progress notes, discharge summaries, and pathology reports—and select from more than 140,000 coding options. This manual process can take up to an hour per patient encounter.To enhance efficiency and accuracy, Cleveland Clinic has begun implementing new AI tools:AI coding assistant : Capable of reading clinical documents in less than two seconds and processing over 100 documents in 1.5 minutes, this tool supports comprehensive and efficient coding by understanding clinical context beyond keyword matching and adapting to patient complexity.: Capable of reading clinical documents in less than two seconds and processing over 100 documents in 1.5 minutes, this tool supports comprehensive and efficient coding by understanding clinical context beyond keyword matching and adapting to patient complexity. Clinical Documentation Integrity (CDI) AI tool: Currently in pilot testing, this tool aims to further improve documentation accuracy by ensuring clinical narratives align with coding practices.Developed with AKASA’s health-system-specific approach, these AI solutions are designed to learn from real-world documentation practices and recognize institutional nuances
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What You Should Know:– AKASA, the preeminent provider of end-to-end generative AI (GenAI) solutions for the revenue cycle, announced the release of AKASA Medical CodingTM, a first-of-its-kind GenAI assistant to transform the $23B medical coding field. – AKASA Medical Coding puts the power of GenAI at medical coders’ fingertips, enabling them to work with unprecedented efficiency, accuracy and comprehensiveness. Revolutionizing Medical Coding with AKASA GenAI TechnologyAccuracy, comprehensiveness, and compliance are critical priorities for medical coding within health systems. However, delivering reliable code recommendations has long been a significant pain point with preexisting technology solutions. AKASA Medical Coding addresses this issue by adding justifications and direct links to medical text, offering a dependable solution that both health systems and their coders can rely on.Powered by proprietary GenAI technology, AKASA Medical Coding is trained on each health system’s clinical and financial data. This advanced AI technology performs the ‘heavy lifting’ of meticulously combing through every relevant medical document for each patient encounter. The solution then identifies recommended codes, each accompanied by justifications linked directly to supporting medical text, allowing coders to accept or revise these recommendations. By leveraging a health system’s unique data, the AKASA Platform outperforms popular generic models like GPT-4 by as much as 40%.AKASA Medical Coding is unparalleled in its ability to analyze a broad range of document types — including clinical notes, imaging reports, and clinical observations