
Blog
The large advisory firms are right to move fast on AI. The choice worth pausing on is where the dependency lands: who sits at the center of the stack, the firm or the model provider. Most leading providers now build their own services too, which means a firm and its core supplier increasingly share territory. A control plane of your own keeps the important things on your side: the client relationship, the methodology, and the freedom to switch or blend models as pricing and regulation shift. That's one of the ideas actAVA KORA is built around. KORA owns token generation and routes tokens to whichever provider fits the task, so adoption and independence grow together. Control the tokens, control your future.

Release Notes
Cura 1T is actAVA's healthcare-specialized language model: a 1-trillion-parameter model post-trained through recursive self-improvement for patient care, clinical reasoning, and agentic EHR workflows. It's the strongest model on 5 of 6 healthcare benchmark panels we ran, holds top-5 on every out-of-domain leaderboard we track, and runs at 5 to 20 times lower cost per output token than the frontier models it beats. Here's what it does, how we trained it, and how to start building on it.

Release Notes
V6 turns KORA agents into a workforce that reaches members directly, improves itself under governance, and proves its value in dollars—a new collection of pre-built Sales & Marketing agents for our customers to use freely. Agents now text members over SMS, inbound and outbound, opt-out-aware, with human approvals routed to the channel reviewers already use. At the same time, a new Agent Self-Learning Loop (the GREEN layer) allows agents to propose their own configuration revisions and ship them only after an evaluation gate is passed. A rebuilt draft-and-released versioning model replaces Test/Prod badges with immutable versions, release notes, and per-step version pinning inside Agent Workspaces, and a single always-on Built-in Master Agent gives every user a master-first chat experience. For healthcare payers, providers, and life-science teams, V6 pairs new outbound reach with tighter governance, encrypted per-organization credentials, and business-event ROI reporting across the entire agent portfolio.

Release Notes
Health plans are running some of the most operationally complex organizations in healthcare — and doing it under the most demanding regulatory scrutiny in the industry's history. CMS-0057 FHIR prior authorization mandates, MHPAEA Non-Quantitative Treatment Limitation analyses, No Surprises Act network adequacy obligations, NCQA credentialing standards, and 834/270/271 eligibility workflows must all execute correctly, simultaneously, at the scale of millions of members and thousands of in-network providers. actAVA's Payer Operations Workflow Library introduces 10 purpose-built agents across six domains — Provider Network & Credentialing, Plan Configuration & Adjudication Rules, Member Operations, Utilization Management, Regulatory Compliance, and VBC Contract Design — each built for the compliance architecture that payer operations require and the audit trail that regulators demand.

Blog
Two things happened in U.S. healthcare AI policy this spring that look opposed but aren't. The federal government moved to deploy AI that can diagnose and prescribe while stripping transparency and testing rules from the tools hospitals already use. At the same time, states are stepping in: Texas, Illinois, Utah, and Colorado all now require the disclosure and oversight Washington just declined to mandate, and four more laws hit on July 1 covering PA/CRNA loan caps, hospital break penalties, PBM reimbursement, and limits on AI in prior-auth denials. The takeaway for AI buyers: deregulation didn't solve the governance problem. It turned it into a 50-state compliance problem, a clinical liability problem, and a trust problem at once. The organizations that built governance into their platform, with audit trails, HITL gates, and approval lifecycles, are the ones who can move fast without creating new risk.

Blog
Every AI vendor is crowding into prior authorization, and CMS-0057 is turning it into a commodity feature. Meanwhile 80% of healthcare's administrative work sits untouched, because each of those workflows is too small for anyone to build a company around. That's your long tail, spanning care management, appeals and grievances, enrollment reconciliation, revenue cycle, and provider operations, and it's where your margin leaks and your staff burn out. This piece breaks down why no point solution will ever build for it, why the token economics (a $15 to $25 labor task runs for $1 to $2 in inference) reward whoever owns the workflow and the model calls behind it, and why owning your long tail beats renting yet more point tools.

Blog
The 2026 Stanford AI Index makes it official: 90% of leading AI models now come from industry, 88% of organizations have adopted AI, and real-world incidents are climbing faster than the controls meant to catch them. In healthcare, that gap shows up as governance debt, accruing quietly with every agent that touches prior auth, clinical decisions, or revenue cycle. Here's how actAVA CHRYSO (automated compliance, evidence, and policy under one roof) and actAVA RED (continuous, production-grade testing for hallucinations, bias, and drift) close that gap before your next audit, incident, or patient interaction.

Blog
AI agents are joining org charts. Not as side experiments, but as operational team members taking on real work across real workflows. Around 80% of U.S. workers may see AI affect at least 10% of their tasks, with 19% facing disruption to more than half of their core responsibilities. This is a structural change in how work is organized, not task-level automation. And yet most organizations are treating it as a technology procurement decision rather than a workforce management decision. actAVA's answer is Non-Human Resources: the same Build, Deploy, Govern, and Improve infrastructure that HR provides for people — applied to the AI agents now joining the team.

Press Release
actAVA is now available on the AWS Marketplace — and for healthcare and enterprise technology leaders, that changes the procurement equation for agentic AI entirely. The full actAVA Agentic Platform (KORA, CHRYSO, and χ-BENCH) is now purchasable through the same consolidated procurement channel AWS customers use for all of their cloud infrastructure: no new vendor onboarding, no separate contract vehicle, consolidated billing, and purchases that count toward AWS Enterprise Discount Program committed spend.

Blog
Two signals came out of the frontier this year, and for anyone running AI in healthcare, they say the same thing. Satya Nadella warned that "a frontier without an ecosystem is not stable," because models now learn from how you work, and that expertise can flow back out and get commoditized. In Responsible Scaling Policy v3.0, Anthropic dropped its signature pledge to pause when a model outpaces its own safety measures, shifting the burden of preventing catastrophic failures onto whoever deploys the model. Put together: you can't rent your sovereignty, and you can't rent your safety. The fix is to own the layer between your workflows and the frontier. A learning loop that compounds your institutional expertise so you can swap models without losing your "company veteran," and a compliance harness that contains the model in deterministic infrastructure code, not a vendor's promise. KORA runs on a single spine, where the same component that routes you to a better model also routes you away from a flagged one. That's the layer the frontier can't commoditize, and no policy change can take back.

Blog
Gabriela Perez is a seasoned, multi-exit senior commercial leader focused on the intersection of healthcare, artificial intelligence, and venture building. When she isn't scaling companies from the inside, Gabriela is fueling the broader tech ecosystem. She serves as a Venture Partner at NextGen Venture Partners, backing next-generation healthcare startups, and supports AI-native healthcare solutions with the venture firm Neo. An alumna of Harvard Business School, Gabriela regularly lends her expertise as a mentor at the Harvard Innovation Labs, helping early-stage founders navigate the complex bottlenecks of scientific R&D, data infrastructure, and enterprise scaling. She is also an advisor to actAVA.ai.

Blog
Nursing turnover alone drains U.S. hospitals of billions each year. The problem isn't a staffing shortage — it's a people-operations failure. Here's what it costs, where the money goes, and how actAVA.ai's AI agents are built to stop the bleeding.

Blog
As healthcare operations shift toward agentic AI, actAVA’s new χ-BENCH benchmark reveals that today's frontier agents are not yet ready to run complex workflows independently. Developed alongside leading academic and clinical institutions, the benchmark found that the best-performing agent setup completed only 28% of complex administrative workflows on the first try, consistency never exceeded 8%, and performance dropped to 0% at critical provider-payer handoffs. Because these policy-heavy workflows carry high stakes—where failures can delay care, increase costs, and introduce compliance risks—healthcare leaders must prioritize systems that can be safely measured and governed rather than automating blindly. To address this trust gap, actAVA offers a purpose-built agent-lifecycle platform that provides the orchestration, safety guardrails, and auditability required to reliably scale AI across enterprise operations