AI that survives a GxP audit.
The question that kills every life-sciences AI pilot is "can we validate it?" SphereIQ answers it — every response cited, every action ledgered, deployed in a validated GxP environment.
Yes, AI can run in a GxP environment. Here's the path.
Governance isn't a dashboard you check afterward — it's enforced in the request path. Every answer is scoped, cited, and signed to the record, the way your controlled processes already work.
Intended use, defined
A validated system with a documented intended use — not an open-ended model loose in your environment.
Only approved sources
The AI reads your controlled SOPs, batch records, and specs — the documents your quality system already governs.
Enforced in the path
Policy, PII, and human-approval checks run on every request — before an answer returns, not audited after the fact.
Every answer traceable
Each answer carries the document, page, and clause it came from, so a reviewer verifies it in seconds.
Written to the ledger
Every query, answer, and approval is attributable, timestamped, and immutable — exportable as audit evidence.
Evidence you can hand an auditor.
Not a promise that it's compliant — the artifacts that prove it. Every deployment produces the documentation a quality review actually asks for.
Validation documentation pack
IQ/OQ/PQ support documentation and intended-use definitions, mapped to your quality system — validation starts from a template, not a blank page.
Immutable audit ledger
Every query, answer, and human approval recorded in an append-only ledger your quality and IT teams can export on demand.
Citation trace to source
No ungrounded claims — each answer links to the controlled document, page, and exact clause. A reviewer verifies, not re-researches.
Timestamped e-signatures
Actions attributable to a person and a moment, with electronic-record integrity built into the architecture — not bolted on.
It already cleared the highest bar.
A life-sciences services firm runs a SphereIQ knowledge assistant in a GxP context — controlled documents in, cited answers out, every interaction ledgered. If it clears life-sciences quality review, your industry's bar is already met.
What the GxP edition ships with.
Deployment starts at mile ten: a pre-built Twin schema, agent templates, and compliance packs for life sciences — not a blank canvas.
GxP validation pack
IQ/OQ/PQ support documentation, intended-use definitions, and audit ledger exports mapped to your quality system.
Manufacturing & quality agents
SOP assistant, deviation support, batch-record Q&A, and training-compliance agents — grounded in controlled documents only.
Life-sciences Twin
Pre-modeled entities: sites, suites, equipment, SOPs, roles, and the approval chains that connect them.
The GxP AI Validation Checklist
The two-page checklist our team uses to scope validated AI deployments: intended use, data controls, audit evidence, and the questions your quality team will ask — answered before they ask them.
Asked in every evaluation
Does using AI mean revalidating our quality system?
Can it run fully inside our environment?
What about 21 CFR Part 11?
Your competitors are waiting for permission. The permission structure now exists.
Start with a scoped, validated pilot on one controlled-document collection.