Patient-facing, clinician-facing, and operations agents symptom routing, ambient documentation, prior-auth, coding, and more. GenGuardX is the shared environment where clinical, operational, risk, and compliance teams validate and monitor any AI agent whoever builds it with the evidence to approve before launch and the monitoring to trust it after.
It's rarely one bot, it's a roadmap of patient, clinician, and operations-facing agents, and every one clears the same gate. Clinical and operational leaders need confidence the AI helps patients and staff accurately. Risk, compliance, and legal need evidence it won't cause harm, leak PHI, or create liability. Most pilots stall because neither side has a shared, defensible way to test, decide, and document.
Clinicians and operations leaders own the patient experience, but are often sidelined during technical testing. GGX lets your SMEs interact with the AI, validate it against real scenarios, and build evidence-based confidence to sign off.
Before clinical GenAI goes live, risk and compliance teams need more than a demo they need evidence. GGX stress-tests models against unsafe behavior, tracks how gaps close, and builds an audit trail that holds up to scrutiny.
"In healthcare, confidence can't come from a demo it has to come from evidence."
The agents on your roadmap span the whole care journey: patient-facing, clinician-facing, and operations. For each one, GGX defines the risks that matter, runs standardized evaluations, and produces the evidence to approve and monitor.
Patient-routing IVR and chat that route patients by acuity, follow clinical protocols, and escalate emergencies safely without over- or under-prioritizing.
Summarize charts, prior history, and visit notes, and surface relevant context to clinicians grounded in the record, never invented.
Automate scheduling, FAQs, prescription refills, and prior-auth status deflecting call volume while keeping answers accurate and on-policy.
Interpret and flag results, route abnormal values to the right team, and draft patient-friendly explanations that stay within clinical bounds.
Turn encounters into structured notes and reduce clinician documentation burden with faithful capture and no fabricated findings.
Suggest accurate diagnosis and procedure codes from documentation to reduce denials and rework with traceable justification for every code.
The same four steps clear the gate for any agent, whether patient-, clinician-, or operations-facing. Identify the risks that matter, measure them with standardized evaluations, mitigate the gaps, and monitor after launch, with evidence at every step.
Select use-case risks: clinical accuracy, groundedness to the EHR, PHI leakage, hallucination, demographic bias, unsafe escalation, prompt injection.
Repeatable tests against curated clinical datasets, expected outputs, protocols, and thresholds, not one-off scripts or vibes.
Apply guardrails, escalation logic, retrieval grounding, or prompt changes, then prove the gap is actually closed.
Turn production traces into alerts, evidence, and new test cases as inputs, models, and content change after go-live.
Each flag, rating, and annotation from a clinical SME becomes reusable, structured ground truth, supporting objective measurement, faster iteration, monitoring, and future evaluation sets. SME time is scarce; GGX captures it once and reuses it across the whole AI lifecycle.
Pre-built, healthcare-specific evaluation categories, plus your own custom risks, thresholds, and datasets.
Answers stay faithful to the record, the protocol, and the evidence not invented.
Detect exposure of protected health information and privacy violations.
Catch fabricated findings, citations, and clinical detail before patients see them.
Verify emergencies escalate and high-acuity cases are never downplayed.
Test for disparate performance across patient populations and groups.
Stress-test against manipulation, data exfiltration, and out-of-scope use.
The same modules your clinical, risk, and compliance teams use to test, approve, and monitor any AI agent (patient-, clinician-, or operations-facing), connected to your stack and your evidence.
Compose multi-agent systems: an orchestrator routing to specialized sub-agents, each with its own model, tools, and grounding. Then compare whole configurations to find the safest setup for each clinical use case.
Clinical SMEs run real patient scenarios against the AI, flag issues, and rate responses: human judgment combined with automated scale and a closed feedback loop.
Starter clinical tests and customizable reports for accuracy, groundedness, PHI, toxicity, and bias: versioned, reusable, and ready for audit.
A single, defensible readiness measure, rolled up from objective sub-metrics and tracked version over version, so progress and approval are provable.
Role-based access, lineage, versioning, and approval workflows so clinical, risk, and compliance teams work from one shared, auditable record.
Out-of-the-box LLM connectors plus API hooks into your EHR and clinical systems, grounded to the record, for pre- and post-production monitoring.
Two very different agents, one operational and one patient-facing, with very different risk profiles. Both reached production with the same method and real evidence, not guesswork. Details anonymized at the customer's request.
The challenge: a high-volume assistant for scheduling, FAQs, and call routing. Clinical risk was low, so the real bottleneck was confidence and sign-off, not the model. What GGX did: ran standardized accuracy, tone, and policy evaluations, captured SME feedback in one place, and produced approval evidence fast enough to launch in about a month.
"The evaluations gave our operations and risk leads one objective view. Sign-off went from stalled to a few weeks."Director, Digital Operations, at a leading US health system
The challenge: a patient-facing assessment assistant with direct clinical-safety stakes. It had been considered "ready" for months but could not clear risk and legal. What GGX did: mapped the risks with clinicians, ran exhaustive testing across protocol adherence, safe escalation, groundedness, and bias, and iterated with SME validation until every threshold was met and the evidence held up to review.
"We finally had evidence the committee accepted, not a demo. That was the difference between stalled and shipped."VP, Clinical Informatics, at a leading US health system
Clinical AI doesn't ship until your CISO, privacy, and legal teams sign off too. GenGuardX is built to pass that review: your PHI stays protected, your deployment stays in your control, and every action is logged and auditable.
We never train models on your data. Everything is encrypted in transit and at rest, with configurable retention and de-identification. Your protected health information never leaves your control.
SOC 2 Type II and HIPAA-aligned, with a Business Associate Agreement available on request.
Secure SaaS, your own VPC, or fully on-prem, with data-residency options.
OpenAI, Google, Anthropic, or your own private and self-hosted LLMs.
SSO/SAML, role-based access, and immutable audit logs across every test, approval, and version.
Built on Google Cloud, Azure, and AWS, with the isolation and reliability enterprise health systems expect.