Google Earth AI introduced Population Dynamics Foundation Model (PDFM) embeddings as plug-and-play geospatial inputs for public-health ML workflows across multiple diseases and geographies. In evaluations, PDFM improved MMR vaccination coverage explained variance for 146 U.S.-Canada border counties from 16% to 22% (+36%) by adding cross-border context. Public health modeling can now use monthly-refreshed, privacy-preserving location embeddings to reduce data-lag and help forecast and risk-predict with comparable or better accuracy versus conventional inputs.
SAP is acquiring Belgian AI startup TechWolf to use its workforce skills and work understanding for its talent strategy. The company was founded in 2018, and TechWolf has raised more than $50m in total. The acquisition is expected to close in Q4 this year, expanding SAP’s AI-driven HR and workforce planning capabilities via TechWolf’s technology.
Vocca raised a $20 million Series A led by Norrsken VC to deploy an AI phone assistant for medical practices. The funding brings total investment to $25 million, and Vocca serves 15,000 practitioners. It will expand deeper scheduling infrastructure, add channels beyond voice, cover more specialties and scenarios, and grow its US presence.
Valon raised $150M in a Series D led by a16z and new investor Ribbit Capital, valuing the AI-native fintech at $2.3B as it expands ValonOS and AI agents for mortgage servicing. The company says one in six US mortgages is under contract to run on ValonOS, after signing over $200M in contracted annual recurring revenue within six months of opening it to outside customers. Valon will use the funding for product development, hiring, and broader rollout so additional servicers can migrate to its unified platform and agent workflows.
calliora raised $6M pre-seed with Bertelsmann Healthcare Investments and redalpine to develop an AI platform that targets hospital billing errors before invoices are submitted. From 2027, German hospitals with rejected audited invoices above 35% could face audits of up to 40% of invoices, and above half rejected could allow up to 100% audits. This shifts hospitals toward earlier error checking in the billing workflow, and calliora expands its AI and product teams to cover more stages of hospital cases.
calliora raised $6 million in a pre-seed round to build an AI platform that checks hospital invoices before they are sent to insurers. The funding was led by Bertelsmann Healthcare Investments and redalpine. Its software rollout is expanding and the 2027 changes to German audit caps increase the urgency to reduce billing errors before invoices go out.
Oura is expanding its Health Radar features and GLP-1 Insights to track how users respond to GLP-1 weight-loss drugs, while also adding blood pressure and nighttime breathing analyses in more markets. The rollout will reach more than 30 additional markets, including the European Union. As a result, Oura ring users can log GLP-1 doses and side effects alongside sensor-derived sleep, recovery, stress, and longer-term blood pressure and breathing trends.
Nettle raised an oversubscribed seed round to expand its AI workspace for commercial insurance loss control. The company secured $4.8 million, bringing total funding to $6.8 million. It will use the money to expand across the US and Europe and add engineering and go-to-market staff, allowing faster risk inspections and broader data collection.
Nettle announced a $4.8 million seed financing round led by MTech to address commercial insurers’ inspection backlog and staffing constraints. The company said inspections can be completed five times faster, with an April 2026 Allianz Türkiye pilot finding inspections up to three times faster. The new funding will be used to expand in the US and Europe and hire more engineers and sales staff, while rolling out its inspection data-gathering product to agents and policyholders.
Utah approved Nolla Health to run a pilot in which an AI agent can automate acne prescription refills with limited physician involvement. The pilot is planned in three stages, starting with 100 patients where physicians approve every AI-generated prescription before it goes to users. If the early checks show no serious problems, the process expands to AI issuing prescriptions directly for the next 500 patients and ending with monthly review of at least 10% of automated prescriptions.
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