Domain-specific AI for medical affairs

Precision evidence
at scientific scale.

Precision

The strongest evidence that's relevant to your project, not the strongest in general. Every paper categorized, with the reason stated.

Scientific scale

Thousands of publications on a single drug. We screen every one the databases return. A writing team can read a few hundred.

An evidence base you can inspect and overrule.

Talk to us See the foundation

One foundation, four things built on it

Evidence Library Evidence Delta SCP Engine Simulations
One build · heart failure our own run on the public literature · edition of 16 Oct 2026
336papers graded in full,
with quoted evidence
23,858 records read
6,584 met the criteria
336 in the library, placed with a reason and graded in full, with quoted evidence
1 in 71 records made the cut
✦ Read the field, not a sample

A human search stops at what one person can read.

A writer scopes a search to a hundred results because that is what a deadline allows. The question becomes "what can I afford to read", not "what does the literature say". Posteros removes that limit. It screens every record the databases return for your asset against the questions the asset raises, and places each paper by the question it answers, with the reason.

1
Search at scale. Searched for every question the asset raises, with each search recorded and dated.
2
Filtered on rigor and relevance. Design fit for the question, then relevance to it.
3
You own the final selection. Overrule any decision, on the paper itself.
✦ The work, shown

Every system decision visible; you can overrule any of them.

Six questions a skeptical reviewer asks, answered on one screen with denominators: did you look everywhere, how much did you read, is it current, is it the right evidence, how hard were you on it, where did you use judgment. A reviewer can audit the library in ten minutes.

The Evidence Library →
Inspect six questions
Breadth
Did you look everywhere?
Depth
How much did you look at?
Currency
Is it current?
Quality
Right kind of evidence?
Selectivity
How hard were you on it?
Judgment
Where did you use judgment?
Four things built on it

From evidence to impact.

The same screened, reasoned evidence base, used four ways. Each one arrives as something you can open, inspect and overrule.

01 · The evidence

Evidence Library

What you receive: the library itself.

The published literature for your asset, screened and placed for every question, with the reason on each paper. Read it, inspect how it was built, select what you take forward.

Evidence Library →
02 · The documents

SCP Engine

What you receive: Draft Zero, an initial draft that traces.

Your questions, the claims the evidence supports with a verdict on each, and Draft Zero, an initial draft of the scientific communication platform (SCP) in which every sentence traces to its sources.

SCP Engine →
03 · The change

Evidence Delta

What you receive: what moved, and what it asks for.

The same evidence base, re-run. Each edition shows what has changed beneath an SCP and what each change asks of it: add, reinforce, requalify, defend.

Evidence Delta →
04 · The experts

Simulations

What you receive: the objections, before you present.

A simulated panel of experts or patients reads your document or your direction and tells you where it pushes back, panelist by panelist, and why.

Simulations →
The check

Your teams draft with AI every day.
We check their work against the literature.

A reason to be wary

The Lancet has measured what happens when nobody checks: fabricated references in the published literature, up more than 12× in three years since large language models came into everyday use. A system built for the domain has the evidence inside it and every claim checkable against its source. The data on AI risk and quality →

Start from the evidence.
Everything else follows.

One evidence base your writers can inspect and overrule; then the documents, the change and the expert reactions built on it.

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