Claim Intelligence, from evidence to everywhere it appears.
Dimlang is the intelligence layer that sits on top of Veeva, Microsoft 365, SharePoint, and Salesforce, understanding claims as a first-class thing: what they assert, what evidence supports them, who approved them, and everywhere they live.
Four steps, running continuously.
This isn't a one-time import. Dimlang runs continuously against your existing systems, so the map stays current as your evidence, approvals, and content do.
Claim extraction & understanding
Dimlang reads claims out of the documents, decks, and systems where they already live today, and identifies what each one actually asserts, not just the sentence it's written in. A claim restated in different words in a training deck and a publication is still recognized as the same underlying claim.
Automatic linking to evidence & approval history
Every claim is connected back to the specific study, dataset, or source that supports it, and to the approval record that cleared it for use. Provenance stops being a lookup someone has to perform under deadline.
Continuous mapping across systems
The same claim typically resurfaces in more places than any one team tracks: a Veeva-approved piece, a field slide, a congress poster, an internal FAQ. Dimlang keeps a live map of every surface a claim appears on, across the systems you already run.
Proactive impact detection
When source evidence changes, whether it's an updated trial result, a label change, or a withdrawn dataset, Dimlang identifies exactly which claims are affected and ranks them by exposure, so your team acts before the gap becomes a question from the field or a finding in an audit.
The foundational layer of a broader intelligence platform.
Claim Intelligence is the product we ship and support today, and it's also the first application of an enterprise intelligence platform we're building specifically for regulated life sciences organizations: one that understands the relationships between evidence, decisions, approvals, and everywhere they surface, not just where documents are stored.
We're deliberately not trying to be everything on day one. Claim Intelligence is scoped to a problem we understand precisely; the architecture underneath it is built to extend to the next one.
Sits on top of what you already run.
Dimlang connects through native APIs and read access to your systems of record. It does not require migrating content, replacing Veeva, or standing up a parallel repository. Where write-back is needed (for example, flagging a claim for review) it happens through your existing workflows and permissions, not around them.
Built for organizations that already answer to strict scrutiny.
Deployment model
Available as multi-tenant SaaS or within a private/dedicated tenant, depending on your organization's data residency, validation, and IT requirements.
Access & permissions
Role-based access control aligned to how your teams are already structured, so Dimlang reflects your existing permission model rather than introducing a new one.
Audit & traceability
Every claim, evidence link, and approval reference is traceable, with a full audit trail of what changed and when, supporting internal review and regulatory inquiry alike.
Data handling principles
Your evidence and claims remain your organization's data. Dimlang indexes and monitors them; it is not the system of record, and does not use customer content to train models shared across customers.
Validation posture
We work with each customer's validation and quality teams to document the system in line with GxP computerized system validation expectations. Specific certifications available on request.
Vendor relationship
Dimlang is designed to complement your Veeva investment, not compete with it. We do not resell or require changes to your existing Veeva configuration.