COMPLIANCE INTELLIGENCE

Your compliance rules, running as code.

Not a policy binder. Not a quarterly review. A deterministic rules engine that evaluates every operational event against your actual regulatory requirements — before the record is committed, not after the audit finding.

We codify the regulations you operate under into executable rules, then layer a governed AI copilot that translates every outcome into plain-language guidance with a citation attached. Delivered in 4 week cycles. Production-ready at the end of each one.

Compliance fails in the gap between the regulation and the workflow.

The regulation is clear. Your SOP documents it. Someone trained the team on it. And then a technician on a Tuesday afternoon hits a case the SOP does not quite cover, and the only thing standing between your organization and an audit finding is whether that person remembers correctly and has time to check.

That is not a training problem. It is an architecture problem.

The rule nobody applied

The requirement exists in a policy document nobody opens. The event gets recorded without the required field, the record is committed, and the gap surfaces months later when an inspector asks for the trail.


The right fact, the wrong rule

Staff correctly recall a requirement — and apply it to a case where a different rule governs. A Schedule II documentation standard applied to a Schedule III shipment. Both facts accurate. The conclusion is wrong.


The trail that was never assembled

An inspector asks how a decision was made. The evidence exists across an EHR, a spreadsheet, an email thread, and someone's memory. Reconstructing it costs a week of senior staff time under deadline pressure.


Deterministic where it must be. Explanatory where it helps.

The rules engine decides

We codify your regulatory requirements into deterministic, versioned rules — executable logic that evaluates each operational event and returns a pass, warn, or fail outcome with an immutable audit record. No probability. No inference. If a rule fires, you can see exactly which requirement was evaluated and why the outcome was what it was.a

The AI copilot explains

When a rule fails, your team does not see an error code. They see what failed, why it matters, and the specific steps to resolve it — in operator language, with a citation to the exact regulation behind it. The copilot never interprets regulation and never decides what is compliant. It translates an outcome the rules engine already validated.

That division of labor is why this architecture holds up in a regulated environment when a general-purpose AI assistant does not.

Compliance Intelligence has two layers, and the separation between them is the entire point.

Frameworks we have codified.

Every engagement starts with your actual requirements, not a template. These are frameworks we have already modeled into executable rules.

Framework Scope What the rules engine enforces
FrameworkDEA / Controlled Substances Act ScopeFederal — all controlled substance handling What the rules engine enforcesReceipt completeness, perpetual inventory, biennial count timing, record retention windows, custody chain integrity
FrameworkDSCSA ScopeFederal — prescription drug supply chain What the rules engine enforcesLot-level traceability, transaction history completeness, trading partner verification, suspect product handling
FrameworkHIPAA ScopeAll PHI-handling entities What the rules engine enforcesRole-based access enforcement, minimum necessary access, audit log completeness, disclosure tracking
FrameworkUSP Chapter 797 ScopeSterile compounding operations What the rules engine enforcesEnvironmental monitoring cadence, beyond-use dating, batch release documentation, personnel qualification currency
FrameworkState Board of Pharmacy ScopeState-by-state requirements What the rules engine enforcesInventory cadence, technician supervision ratios, policy and procedure compliance, licensure currency
FrameworkFDA 21 CFR Part 820 / QMSR ScopeMedical device manufacturers What the rules engine enforcesDesign history file completeness, CAPA closure integrity, document control, supplier qualification
FrameworkFDA 21 CFR Part 803 (MDR) ScopeMedical device adverse event reporting What the rules engine enforcesReportability determination, 30-day and 5-day window tracking, event classification consistency
FrameworkSOC 2 ScopeSaaS handling sensitive client data What the rules engine enforcesSecurity, availability, processing integrity, and confidentiality control evidence

Operating under something not on this list? The architecture is framework-agnostic. If the requirement can be written down, it can be codified.

Luveo Health — 28 rules, 7 workflows, two delivery cycles.

Luveo Health — Enterprise Pharmacy Operations Platform

28 — COMPLIANCE RULES CODIFIED

7 — PHARMACY WORKFLOWS COVERED

97% — EXPLANATION ACCURACY (100% ON CHAT)

0 — GUARDRAIL VIOLATIONS ACROSS 30 SCENARIOS

The Compliance Rules Engine

28 rules codified across seven workflow families: Receiving, Movement, Waste, Audit, Expiration, Ordering, and Credential. Coverage spanning DEA, DSCSA, HIPAA, USP 797, and state Board of Pharmacy requirements. Load-tested at 35 events per second with p95 latency of 2.9 seconds.

The AI Compliance Copilot

A governed explanation layer translating every rule outcome into plain-language guidance for pharmacy technicians: what failed, why it matters, the steps to fix it, and a citation to the specific regulation. Validated across a 30-scenario structured evaluation: 97% accuracy on explanations, 100% on chat, with zero hallucinated rule keys and zero fabricated regulatory citations.

The rules engine determined what was compliant. The copilot only explained an outcome that had already been validated — with a citation, every time.

Built for organizations where an audit finding has consequences.

Pharmacy operations platforms

Software companies serving pharmacies who need compliance evaluation embedded in their product - DEA, DSCSA, USP 797, and state board requirements enforced at the transaction level.

Specialty pharmacy and infusion

Organizations handling controlled substances or sterile compounding where documentation timing and completeness carry direct regulatory exposure.

Medical device companies

Pre-production and scaling manufacturers facing QMSR documentation requirements, MDR reportability determinations, and post-market surveillance obligations that are outgrowing manual review.

Digital health platforms in regulated workflows

Companies whose product touches a regulated process and who need the compliance layer to be defensible, not just present.

One workflow family. Four weeks. Production, not pilot.

We scope each cycle to a single workflow family or regulatory framework. Narrow enough to finish completely. Real enough to matter operationally.

Week Focus What happens What you get
Week 1 FocusRequirements + Architecture What happensWe work with your compliance team to map the actual requirements, connect to source systems, and establish the governance model What you getWorking data pipeline and a documented rule specification for review
Week 2 FocusRules Engine What happensWe codify requirements into deterministic, versioned rules and validate outcomes against your real operational records What you getLive rules engine evaluating your events — first demo to your team
Week 3 FocusCopilot + Hardening What happensWe layer cited explanations, add audit logging and access controls, and run the structured evaluation set What you getGoverned copilot layer plus an evaluation report on accuracy and guardrails
Week 4 FocusProduction What happensDeployment into your environment, team walkthrough, documentation, and the roadmap for expansion What you getProduction system your team owns, plus a written scale roadmap

At the end of week four you decide whether to run another cycle. Luveo ran two. Most clients run three to six as they expand coverage across workflows and frameworks.

Reasonable questions.

Bring us one workflow. We will tell you what four weeks looks like.

Thirty minutes. Three questions: which workflow carries the most regulatory exposure, what systems hold the data behind it, and what would have to be true for you to consider it solved. If we can scope it into a cycle, we will tell you exactly what that includes and what it costs. If we cannot, we will tell you that too.