Luvia / A research system for life sciences
01 Thesis

The hard part
isn't the AI.

An LLM can summarize, reason, and write — it can search the web. What it still can't do, an analyst can. And that's the problem we solve.
01

Know what's true

Web search returns press releases and outdated articles. A curated, cross-referenced database of 827,000 drug programs returns signal.

02

Cross-reference

MK-3475, pembrolizumab, and Keytruda are the same molecule. Identity resolution across 56 identifier systems makes it obvious.

03

Query at scale

An LLM looks up one drug at a time. We run structured queries across 41M molecules, 264M patent links, and 577k trials.

04

Show its work

Every answer traces back to a primary source — a specific database record, a specific trial ID, a specific patent family. No hand-waving.

The AI is the interface.
The value is in the infrastructure underneath.
01 — thesis
02 What we maintain

A data layer,
not a search engine.

We maintain the substrate — curated, cross-referenced, and refreshed. Ask a question in plain English; the system decides what to query.
Drug programs 827K Every publicly-disclosed program, with company, target, indication, phase, and regulatory status.
Molecules 41M Structures, properties, identifiers, parent/salt resolution — all reconciled into one record.
Patent links 264M Molecule-to-patent links with evidence tiers, expiry, jurisdiction, family.
Clinical trials 577K The full ClinicalTrials.gov corpus, linked to molecules, targets, and sponsors.
25+ live APIs on top — PubMed, OpenFDA, ChEMBL, AlphaFold, OpenTargets. The system decides when to use them.
02 — scale
03 Positioning

We do one thing.
Make your analytical work faster and sharper.

Where Luvia fits

Due diligence. Competitive landscapes. Patent and IP exposure. Target-indication analysis. Portfolio monitoring. Live readouts filtered to what you actually work on.