Eight levels.
One system.
Compounding advantage.
Most organizations in 2026 have AI tools. Almost none have AI architecture. level07 is the governed maturity progression that turns disconnected deployments into institutional intelligence — safe, measurable, and defensible at every step.
Not a technology roadmap.
A governed progression.
level07 is VeritAI's proprietary AI maturity framework — eight sequential levels, each building the governance and integration foundation that makes the next level safe to deploy.
It is not a checklist. It is not a scoring report. It is the architecture — governance + data + workflow + measurement — assembled domain by domain, at your pace, in the sequence your organization needs.
Assessment is done domain by domain. It is completely normal for a large hospital to be at L4 in clinical documentation and L1 in revenue cycle. The diagnostic produces that map — without assumptions — and sequences investment to highest combined impact.
Clinical-Grade AI Governance
Complete inventory of every AI tool in active use — with or without governance. AI Steering Committee with explicit decision rights. Clinical risk tiers: patient-safety-critical, administrative-clinical, and operational — each with distinct review requirements and escalation paths. HIPAA AI compliance architecture: PHI handling defined for every vendor before deployment. Immutable audit logging: every AI action attributed, with inputs, outputs, and human review in a tamper-evident log. Shadow AI eliminated through governed alternatives that are genuinely better.
Augmented Departments
Ambient AI documentation embedded in existing EHR workflows — clinicians review and sign, never start from scratch. CDI with AI: 60–70% of encounters coded automatically, accuracy benchmarked against manual. Prior authorization packet assembly: clinical documentation, diagnosis codes, and payer-specific medical necessity evidence compiled before submission. Denial appeal letters drafted from denial reason and clinical guidelines. All L1 deployments reviewed by the AI Steering Committee before activation, classified by clinical risk tier, and monitored for equity impact.
Network Visibility & Data Foundation
Reconciled Master Patient Index across all facilities, EHR instances, billing systems, pharmacy, and laboratory — with real-time conflict detection. AI retrieves patient data from the reconciled MPI, never from system-specific identifiers. Longitudinal clinical context available at point of care. Real-time bed management from housekeeping and nursing systems, not manual entries with 2-hour lag. Prior authorization and MA benefits data available at scheduling and point of care. Social determinants of health integrated from community data sources.
Orchestrated End-to-End Flows
Consequential workflows converted into governed cases: discharge orchestration (readiness criteria tracked continuously; transport, pharmacy, home health, and follow-up coordinated automatically); medication reconciliation (discrepancies surfaced and closed before discharge); critical result routing (critical lab and imaging values trigger governed routing with acknowledgment required and escalation if not received); prior authorization lifecycle (requirements identified at scheduling, documentation assembled, denial routed to appeal with no case going stale); revenue cycle end-to-end.
Role-Aware Intelligence Surfaces
Role-calibrated copilots deployed across clinical and operational functions — not generic chat interfaces, but intelligence surfaces built for the specific decision context of each role. The physician's surface synthesizes clinical context across the patient's longitudinal record, relevant guidelines, and real-time lab and imaging data. The care coordinator's surface tracks discharge readiness, post-acute placement, and follow-up booking in one governed view. The executive's surface shows AI performance, clinical quality, and financial metrics in one governable dashboard.
Governed Multi-Agent Orchestration
Agents that monitor signals and act within a technically enforced autonomy matrix. The matrix classifies each action by type (read, propose, execute-and-notify, execute-and-escalate) and by clinical consequence (none, recoverable, irreversible). No agent executes autonomously on an action with irreversible clinical consequence — regardless of model confidence. When a deterioration event triggers simultaneous activity across sepsis detection, bed management, and clinical summary generation, the orchestrator ensures they act on the same patient record, in a defined sequence, with one reconciled audit trail.
Elastic Care Delivery
Care services deployed where demand is, when demand is there, in the care setting the patient needs. Virtual nursing at scale: AI-assisted virtual nurses monitor multiple patients simultaneously, supporting bedside nurses on documentation and routine monitoring. Post-discharge remote monitoring: wearables and home sensors aggregated; deterioration models applied; high-risk alerts routed with clinical context. Hospital at Home: medically appropriate inpatients managed at home through AI-coordinated nursing visits, remote monitoring, telehealth, and supply delivery. Intelligent patient routing: patients matched to appropriate care setting at first contact.
Continuous Portfolio Intelligence
At L7, the governed intelligence accumulated across all previous levels turns outward. The system continuously synthesizes three signal sources: internal signals (clinical outcome patterns, readmission drivers, denial patterns by service line, surgical quality metrics, care gap closure rates); competitive signals (what peer institutions offer, where outcomes differ, where referral network gaps exist); and market signals (community health data, population need patterns, emerging service demand). These converge in a continuously updated strategic intelligence layer.
Every organization
starts somewhere different.
We find exactly where.
The level07 Diagnostic is the first 90 days of every engagement. It is not a survey. It is a domain-by-domain assessment that produces a level map across every function — and a sequenced investment plan that prioritizes the highest combined clinical, operational, and financial impact.
- Complete L0–L7 map across every department
- Shadow AI inventory — tools in use without governance
- Governance gap analysis with regulatory exposure scoring
- Leadership behavioral profile: capacity, willingness, coordination
- Industry context built in: benchmarks, regulatory requirements, peer signals
- 90-day first phase designed from your actual state
Every industry has its own level07.
Shown above. L0 governance is HIPAA AI compliance. L4 surfaces are Epic-native. L6 includes virtual nursing and Hospital at Home. L7 synthesizes CMS Star Ratings, MA denial patterns, and market signals. Further calibrated by org type: reference vs. regional vs. ambulatory.
L0 protects FERPA and SACSCOC compliance. L1 covers student success AI and retention models. L4 surfaces serve provosts, registrars, and advisors separately. L7 tracks enrollment competition and workforce demand signals. Calibrated for flagship vs. private tuition-driven vs. community college.
L0 governs GxP-compliant AI with inspection-ready audit trails. L3 orchestrates batch review, deviation investigation, and QMS workflows. L7 surfaces competitive pipeline and sponsor risk signals. Calibrated for top-20 pharma vs. growth biotech vs. CRO vs. CDMO.
L0 satisfies SR 11-7 and model risk management. L3 automates fraud detection and compliance reporting workflows. L5 multi-agent orchestration maintains audit trail integrity. VeritOS adds the evidence layer. Calibrated for Tier-1 bank vs. regional vs. fintech vs. insurer.
Your free,
hyper-personalized
level07 assessment.
We'll map your actual state across every domain, identify governance gaps and shadow AI exposure, and design the sequenced investment plan that gets you to L3 in 90 days — with a path to L7.