Your product now carries AI. Its validation evidence has to carry it too.
You build AI-driven systems for pharma — embedded AI features as much as pure AI products. Your customers cannot deploy what they cannot validate, and every stalled validation at a customer site is stalled revenue on yours. ValiCore ADVISORS turns AI validation from a per-project effort into a product asset: the AI evidence layer built once and anchored into the validation package you already have. Adapted per site, kept current per release.
Every deployment hits the same wall
Your product is proven, and your validation package — OQ libraries, installation verification, risk files — has carried it through CSV for years. AI features change the question: they introduce an evidence class that package was never designed to carry — training-data lineage, drift control, retraining change management, transparency duties. That layer, and only that layer, is what each customer now asks for at every site. It should be built once, precisely scoped.
The validation package for AI-driven systems in six families.
A structured, risk-based validation approach for your AI product, aligned with the frameworks your customers are inspected against. Built once as the backbone; each deployment adds only what is genuinely site-specific. If your product already has a validation package, we assess the AI gap and build only the delta — into your structure.
1
Plan & Scope
Intended-use and claims dossier, component classification and the validation master plan — what the product promises, and how its validation is scoped.
2
Design & Evidence Model
Model design specification, dataset qualification, performance against specification and claims, explainability — the records only the maker can produce.
3
Operational Controls
Human oversight, drift monitoring, retraining change control, audit-trail conformance, privacy and re-identification, incident handling — how the AI behaves in service, and what happens when it doesn’t.
4
Verification Records
IQ, OQ and PQ executed per release, traceability matrix, validation summary — every claim traced to a result.
5
Customer-facing Evidence
Shared-responsibility matrix, quality-agreement readiness, AI Act role and classification file, customer deployment kit — what their QA and auditors touch.
6
Change and Currency
Release classification and defined refresh scope per change; where the AI Act high-risk regime applies, the conditional file the 2027/28 dates demand.
Validation stalls in the quality review
Your customer's QA asks how the model was validated, what happens when it drifts, who approves what — and every customer asks it in their own house style, against their own SOPs. Your team knows the product better than anyone; we take the compliance side of that conversation, with audit-side credentials their QA recognises."
Two pillars. The evidence set — and the deployments it has to hold up in.
We shape the collaboration around what you need. Nothing runs on a retainer — the delivery and upkeep work ends with your team running it.
1
A. Assess
Gap assessment of your existing package against the AI control set.
→ Gap map and a priced delta plan.
B. Build
The AI delta into your structure — or the full package for AI-native products.
→ Current package; every claim traced to a test.
C. White label
The framework and deployment kit under your name, licensed per major version.
→ Your branded set, validity stated.
2
D. Deploy and transfer
We work the first customer-side qualifications alongside your team, then qualify your implementation and quality team to carry the rest.
→ Shorter path from contract to go-live — and a validation service you can put on your own quote.
E. Keep it current
Each release gets a class and a defined re-validation scope. Your team runs it.
→ Evidence that keeps pace with your release cycle, run by your own team.
ValiCore ADVISORS commitments: we do not audit validation evidence we have authored — that would weaken the audit your customers rely on. And the package reduces their validation effort without replacing their own qualification: their records stay theirs, and nothing we deliver may be presented as a certification.
One backbone every deployment cycle
Your customers have to ask — before they buy (Annex 11 §3.2, §3.3), when they validate and leverage your documentation (§4.5; GAMP 5), whenever a model is involved (draft Annex 22 §2.2), when they audit you, and when an inspector asks them about you (§3.4). The package answers all five from one filed evidence set, mapped against audit-grade checklists — 80+ control points for GxP software with AI, 75+ for API-only providers — so each moment verifies instead of discovers.
Explore a partnership
Your product carries the AI; the validation questions arrive with every customer. We turn them into one filed evidence set — built once, anchored in your existing package, current per release — and work the first deployments with your team until they carry it themselves. Your product, your customers, our second seat where it counts. Let's start the partnership with a conversation.
