131 PUBLIC SECTOR three to five times return on investment within the first year, along with meaningful reductions in administrative cost, burden, and improved experiences for patients and providers. IgniteData deploys agentic AI to automatically capture data from clinical trials. These agents ensure seamless, error-free, human-in-the-loop data exchange between healthcare providers, research institutions and trial sponsors, dramatically accelerating research timelines and enhancing patient safety monitoring. The reduced manual effort and real-time synchronisation improve the quality of patient care during studies and delivers financial efficiencies for hospitals by minimising redundant documentation and compliance risks. Agentic AI can also be used to manage healthcare risk adjustment with minimal human intervention. Unlike AI-assisted tools requiring constant oversight, Raapid’s specialised agents work independently, identifying HCC (Hierarchical Condition Category) codes, validating MEAT (Monitor, Evaluate, Assess/ Address, Treat) evidence, checking compliance risks and citing supporting documentation. Raapid’s technology uses neuro-symbolic AI, which integrates neural networks for pattern detection with symbolic reasoning for powerful insights with clear explanations. Multiple agents collaborate through what Raapid terms “agent orchestration”, reaching consensus on coding decisions. In production environments, organisations reduce chart review time from 30-40 minutes to under eight minutes – a five times productivity gain – while maintaining higher than 98 per cent coding accuracy. Each recommendation includes traceable audit trails linking to source clinical evidence, addressing RADV (Risk Adjustment Data Validation) audit defence requirements. As an M12 (Microsoft venture fund) backed company with HITRUST certification, Raapid provides deployment within organisations’ existing Microsoft Azure environments, ensuring data sovereignty. The system integrates with current EHR (Electronic Health Record) infrastructures enabling continuous learning from human coder feedback. These Microsoft for Startups companies share several common themes that reflect broader trends in agentic AI for healthcare and life sciences. First, there is a clear emphasis on interoperability and integration, ensuring that AI systems work harmoniously. Second, explainability and transparency are prioritised to foster trust among clinicians and patients. Third, these startups demonstrate the value of continuous learning, with AI agents that adapt to new data and clinical guidelines over time. Looking ahead, agentic AI is poised to drive further personalisation of care, streamline research and operational processes, and support population health initiatives. As regulatory frameworks evolve and adoption accelerates, these innovations will likely become standard practice across the sector. Sally Ann Frank is global lead for health and life sciences at Microsoft for Startups Atropos Health’s AI agents combine medical data so that clinicians can find the information that they need faster when serving patients
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