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PubCompare

PubCompare is a scientific protocol database with 40M+ indexed protocols from peer-reviewed literature (PubMed, PMC, Open Access PDFs), preprints, and patent offices. The corpus is a linked knowledge graph — every protocol, product, organization, and topic has a stable, crawlable URL — so both bench scientists and AI agents can deep-link to any node and follow the connections between them.

For agents: Scientific protocol database with 40M+ indexed protocols from literature, preprints and patents, linked as a crawlable knowledge graph of protocols, products an

lab protocolsscientific protocol databasepeer-reviewed methodslab products searchpatent protocols

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-23T03:12:49.412Z. Cached copy · Source on pubcompare.ai

# PubCompare

> PubCompare is a scientific protocol database with 40M+ indexed protocols from peer-reviewed literature (PubMed, PMC, Open Access PDFs), preprints, and patent offices. The corpus is a linked knowledge graph — every protocol, product, organization, and topic has a stable, crawlable URL — so both bench scientists and AI agents can deep-link to any node and follow the connections between them.

On top of a keyword-based protocol search, PubCompare offers advanced protocol search and grinding technologies:

**Protocolyze** — PubCompare's consensus engine — extracts and compares experimental parameters across the literature so researchers can design, reproduce, or justify an experiment in minutes instead of days, turning months of protocol design into days with fewer trial-and-error cycles.

**Product Application Reports** — confirm whether a product has been used in a given experimental context and surface the surrounding parameters that real labs applied.

Swiss company. Product at https://www.pubcompare.ai.

## Core capabilities

PubCompare combines a structured protocol corpus with a consensus engine that turns raw protocols into comparable, parameter-level data.

### Search the corpus

- **Keyword search** across the 40M+ protocol index.
- **Semantic search** for intent-based retrieval when the exact terminology isn't known.
- **On-site AI agent** that guides query refinement and protocol discovery inside pubcompare.ai.

### Protocolyze — consensus engine

For a given experimental question, Protocolyze:

1. Retrieves the protocols that match the question along three dimensions: the **model** (cell line, organism, in vitro system), the **intervention** (treatment, compound, perturbation), and the **readout** (the measured endpoint).
2. Extracts experimental parameters from each protocol — concentrations, durations, equipment, controls, statistical handling, sample sizes, and so on.
3. Aligns parameters across protocols and computes a consensus value per parameter.
4. Returns a **Protocolyze report** — a web page on pubcompare.ai or JSON delivered to AI agents, containing: a consensus parameter matrix; a confidence tier per parameter (Confirmed when ≥3 protocols agree, Limited when 2 agree, Caution when only 1 reports the value, No Data otherwise); a materials & equipment section; full source citations; and a QA verification block surfacing any inconsistencies the engine detected.

Every consensus value links back to the primary sources that support it. Traceability is non-negotiable: if a claim can't be backed by citations, it isn't shown.

### Product Application Reports

For a given product (an antibody, kit, cell line, instrument, etc.), the PubCompare engine retrieves every protocol that uses it — whether referenced by its exact identifier or by its generic type — and surfaces the surrounding experimental parameters along the same three dimensions as Protocolyze: **model**, **intervention**, **readout**. The output confirms whet
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Claim my listing on Agent Web Map for pubcompare.ai:
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