Every breakthrough already exists in fragments.
The treatment for Spinal Muscular Atrophy was scattered across databases and filings for decades before it reached a single patient.
Children waited years for a treatment that already existed.
That’s the cost of silence. Not a data problem. An infrastructure problem.
collabIQ is the context graph connecting science and strategy.
A knowledge graph tells you what is. A context graph tells you what to do about it. It doesn’t aggregate data; it’s the foundational infrastructure that links scientific rigor to business logic, every node traced to its source.
This is the new standard for life science strategy.
Explore the Intersection of Science & Strategy →What’s true. What’s connected. What’s next.
One graph. Three levels of intelligence: grounded facts, inferred connections, predicted outcomes. Every node traced to a primary source.
Grounded facts, inferred connections, predicted outcomes. Every node traced to a primary source.
We find the signal. You run the diligence.
Your platform doesn't need another dashboard. It needs the intelligence layer. One API call returns scored evidence, predicted whitespace, and full provenance in under 42 milliseconds, delivered straight into the tools your team already uses.
Not another dashboard. The intelligence layer, delivered into the tools you already use. Scored evidence, predicted whitespace, and full provenance in one call.
Your platform. Our intelligence. One integration.
Explore the API schema →Your platform. Our intelligence. One integration.
Explore the API schema →Most data adds up. Ours multiplies.
A competitor’s new source adds rows to a table. Ours multiplies against the 1.4 billion connections already built, so every category compounds instead of stacks.Every new source multiplies against 1.4 billion connections. It compounds, it doesn’t stack.
Most data adds up. Ours multiplies.
A competitor’s new source adds rows to a table. Ours multiplies against the 1.4 billion connections already built, so every category compounds instead of stacks.
Anyone can license the same sources.
No one can replicate how they’re connected.
A competitor licensing the bottom step is licensing about one percent of the graph. The other 99% has to be built.
That’s the flywheel.
Four domains. One graph.
all four domains
across four domains
Anyone can license the sources. No one can replicate how they’re connected.
A competitor licensing the bottom step is licensing about one percent of the graph. The other 99% has to be built.
Data is a commodity. Context is the moat.
Every industry shift settles on one truth: advantage moves from the entities that own the most assets, to the infrastructure that connects them best. Life sciences is no different.
The future of biopharma strategy isn’t waiting to be discovered, it’s waiting to be connected. Powered by a context graph, what’s connected predicts what’s next.
Advantage moves from owning assets to the infrastructure between them.
Biopharma’s future isn’t waiting to be discovered, it’s waiting to be connected. What’s connected predicts what’s next.
The context graph for life sciences.
Where science meets strategy
Every great platform made the same bet:
connection over ownership.
The old economy rewarded ownership.
The platform economy rewards infrastructure.
Studied the science. Twice. Then built the infrastructure to connect it.
One of the first ten Apple ResearchKit apps in clinical trials was hers. Then a decade inside BMS, Pfizer, and CSL Behring, watching billion-dollar decisions run on disconnected spreadsheets.
So she built the production knowledge graph powering a top-20 biopharma’s $9M+ AI initiative. Then she built collabIQ. Pharmacologist. Economist. Engineer. It’s a context graph because she is the context.
The best drug companies of the future won’t invent every asset themselves.
They’ll win by becoming platform economies,treating patients without owning every drug they sell.
The way Uber moves people without owning cars.Asset-light. Evidence-first. Startup speed.