Point solutions cover the head. Agents run the tail.
Prior authorization has forty products. Results routing, incident surveillance, release of information, and the fee schedule reconciliation someone rebuilds in a spreadsheet every month have none, and your staff absorbs all of it. actAVA turns that long tail into governed agents on one platform, with KORA, CURA, CHRYSO, and χ-BENCH behind every one.
Your processes need your agents, not your vendor's general AI.
Software gets built where thousands of health systems share the same process. Ambient documentation gets a category. Denial management gets a category. Critical results routing, alert rule governance, census-matched staffing, and telehealth modifier capture never will, so those workflows stay with the people already holding them. Six of the thirty priority provider workflows have no product category at all, and each one still carries malpractice exposure, labor cost, or lost reimbursement.
Complex U.S. healthcare workflows that frontier models fail on χ-BENCH.
Agents that stay successful when the same task repeats.
Tools across 21 healthcare applications, grounded in real managed care policy.
The long tail becomes workable when the next agent is cheap.
Pointing a frontier model at the tail yourself looks like the way out until the work repeats. On χ-BENCH, frontier models fail 72% of complex U.S. healthcare workflows, and fewer than 8% of agents stay successful when a task runs again. Most of those failures trace back to dense policy rather than broken integrations, and the scaffolding around the model decides the outcome. On one platform the thirtieth workflow costs a fraction of the first, and work that never justified a purchase order suddenly justifies an agent.
Read the χ-BENCH studyEvery actAVA product works the same problem, making your next workflow cheap to automate and safe to run.
Build the long tail on KORA
Compose agents from healthcare-native building blocks instead of standing up a codebase per workflow. KORA orchestrates multi-step work across chat, voice, and background processes, reaches your EHR and billing systems through one integration layer, and tests every agent against χ-BENCH-grade simulation before it touches a patient record.
Explore KORARun CURA, frontier models, or both
Swap models without rewriting a workflow. CURA, actAVA's trillion-parameter healthcare model, scores 94.0 on MedAgentBench for EHR tool use and holds a full case in a 256K context window. It serves an OpenAI-compatible endpoint and runs in your cloud at lower cost.
Explore CURAGovern all of it with CHRYSO
One governance frame covers the first agent and the three-hundredth. CHRYSO maps 110+ controls across NIST AI RMF, HIPAA, CMS, and ONC HT1, holds the physician and committee gates the tail depends on, and turns an audit request into a package instead of a scramble.
Explore CHRYSOStart from working agents, then build the workflows only you have
Provider organizations draw on three actAVA collections at once: care management for the longitudinal and revenue-cycle work, behavioral health for the clinical programs, and HR and people for the workforce underneath both. Every agent ships with HIPAA controls, human approval gates, and full audit logging, and forking one beats specifying an agent from scratch.
- AI
- Compliance
- HITL · Human in the loop
Johns Hopkins is building the AI the market won't sell, and benchmarking every agent before it deploys.
A $10 million gift from Dr. James Gills, an ophthalmologist and early NVIDIA investor, launched the Gills AI Innovation Center. Dr. Alvin Liu directs it and sits on the Johns Hopkins Medicine AI Oversight Team. He started with a harder question than which workflow to automate. Can frontier agents finish policy-dense, end-to-end work at all? His team ran them through χ-BENCH on actAVA before deploying anything, and the results pushed him toward ownership over rental. Hopkins measures reliability first, tracks token consumption and per-agent cost against baselines, and holds off on reporting financial return until the evidence earns it.
- of workflows no vendor sells
- 0% of workflows no vendor sells
- cheaper per token, owned against rented
- 20–100x cheaper per token, owned against rented
- tools tested before deployment
- 0+ tools tested before deployment
“Accountability requires knowing which agent did what, under which policy, and with what result.”
90-day value realization
Start quickly.
Plan your agent roadmap and digital workforce budget.
Build agents immediately with the actAVA team beside you.
Integrate your systems of record and launch from the prebuilt library.
Run safely.
Establish your AI policies, frameworks, and evaluation rubrics.
Evaluate agent performance, inspect behavior, and improve it.
Govern every agent and orchestrate them across your systems.
Grow intelligently.
Control model costs with real-time consumption monitoring.
Distribute agent resources as functions and demand shift.
Measure ROI for every agent on a configurable dashboard.
Agents for the workflows on nobody's roadmap but yours.
Every agent tests before it deploys, every action lands in the audit log, and the intelligence runs in your cloud under your control. Name the workflow your team carries by hand and we will show you the first agent running against it.