Introducing the Wiley x Valyu HLS Startup Program

Wiley’s Health and Life Sciences research is now a knowledge feed AI agents can call. More than one million peer-reviewed articles across 900+ journals, including full text, figures and equations, are now available for purchase by eligible startups through Valyu Search and DeepResearch.

AI is moving into science’s hardest problems: discovering new drugs, understanding disease, reviewing clinical evidence and making sense of a scientific record no individual researcher could read alone.

But the frontier of medicine and biology does not live on the open web. It lives inside the papers, results and evidence scientists rely on.

Today, Wiley and Valyu are making that available to scientific AI applications through the Wiley x Valyu HLS Startup Program.

What we are introducing

Wiley is one of the world’s largest and most established research publishers, with a publishing history spanning more than two centuries. Its journals are read and cited across the global research system, from universities and hospitals to pharmaceutical companies, R&D teams and scientific societies.

The Wiley x Valyu Startup Program can pull from more than 900 of Wiley’s journals across oncology, immunology, neuroscience, genetics, cardiology, pharmacology, physiology, psychiatry, ecology and the wider health and life sciences.

Eligible AI startups can bring this literature directly into their products and research workflows on a pay-per-use basis.

Agents can search across full articles, retrieve the evidence relevant to a question and trace results back to the original publication.

The program is live now.

Wiley HLS as a knowledge feed

Scientific literature has traditionally been somewhere a researcher goes.

They search for a paper, open it, read it and manually carry the relevant information into the next stage of their work.

A knowledge feed changes that relationship.

Wiley HLS can be called while an agent is carrying out a task. Instead of returning only a list of papers, the agent can retrieve the relevant evidence and bring it directly into the workflow.

An abstract can tell an agent that a paper exists. Multimodal full-text retrieval lets it examine what the paper actually says.

Built for the way startups build

Scientific AI startups often begin with one focused problem, one agent or one specialist workflow.

The Wiley x Valyu HLS Startup Program gives eligible startups a self-service, pay-per-use model to have Wiley’s peer-reviewed literature added through Valyu Search, DeepResearch and Valyu’s developer interfaces.

Teams can start with an API key, integrate Wiley HLS into an existing workflow and expand its use as the product grows.

Point your stack at Wiley HLS

Name the source, ask a question in natural language and retrieve full-text results with citations.

from valyu import Valyu
 
valyu = Valyu(api_key="val_***")
 
response = valyu.search(
    "CAR-T cell therapy resistance mechanisms in relapsed lymphoma",
    included_sources=["wiley/wiley-hls"],
)
 
for result in response.results:
    print(result.title, result.url)

The agent can use the retrieved passages as context, while the user can follow the result back to the original Wiley publication.

What is included

• Full text, not abstracts. Agents can retrieve and reason over the article body rather than relying on a title or truncated summary.
• Figures and equations. Figures are included, with mathematical content preserved as LaTeX where available.
• Structured metadata. Results include the DOI, authors, publication date, references and citation information.
• Provenance. Each result traces back to the primary Wiley source.
• Commercial use. Wiley content is licensed for AI retrieval through the partnership on a pay-per-use basis, while blended open-access content is filtered to commercially permissive licences.
• More than one million articles across 900+ journals. The collection covers research from 2019 onwards and is updated as new content is released.

Why this matters for scientific AI

The quality of a scientific AI system depends on more than the capability of the underlying model. It also depends on the evidence the model can reach.

A fluent answer is not necessarily a well-founded one.

Scientific questions rarely sit inside one source. Preprints show where a field is moving. Structured databases expose compounds, targets and assays. Patents show how discoveries are being applied. Peer-reviewed literature provides the published evidence behind scientific claims.

This matters as agents move beyond finding papers and begin carrying out multi-step, long-horizon research work: identifying relevant studies, comparing findings, surfacing disagreement, following references and producing cited answers.

Through Valyu, Wiley HLS can be used alongside these other scientific sources where relevant to the task. An agent can move from an emerging claim to the published research behind it, compare evidence across sources and trace the result back to the original work.

See the wider scientific source coverage in the Valyu documentation.

What you can build

• Drug discovery and target research. Investigate targets, mechanisms, pathways, biomarkers and compounds, compare findings and return cited research briefs.
• Clinical research and evidence workflows. Retrieve the evidence behind a clinical research question and compare findings across studies.
• Evidence synthesis and systematic reviews. Search full text, extract findings, surface conflicting results and preserve a citation trail.
• R&D copilots. Put peer-reviewed literature behind internal tools that can search, compare and cite across a field.
• Scientific and medical writing. Retrieve supporting literature while drafting and connect claims to their sources.
• Landscape and competitive intelligence. Track a therapeutic area or research field across publications, preprints, patents and scientific data.

Teams are already integrating Valyu into research agents and scientific workflows across life sciences and clinical research.

How it works

Use Wiley HLS as a dedicated source when a query should run specifically against Wiley’s peer-reviewed literature.

response = valyu.search(
    "mechanisms of tau propagation in early Alzheimer's disease",
    included_sources=["wiley/wiley-hls"],
)

Run a full research workflow

Search retrieves the evidence relevant to a query.

DeepResearch plans the wider task, searches across sources, cross-references findings and produces a cited report.

task = valyu.deepresearch.create(
    query=(
        "Summarise the current evidence on GLP-1 receptor agonists "
        "in neurodegenerative disease, and where the field disagrees."
    ),
    mode="standard",
    research_strategy=(
        "Prioritise peer-reviewed health and life sciences literature from "
        "Wiley HLS. Cross-reference against PubMed, Patents and the biomedical preprints "
        "in bioRxiv and medRxiv. Favour primary sources from the last three "
        "years and cite every claim back to its DOI."
    ),
)
 
result = valyu.deepresearch.wait(task.deepresearch_id)
print(result.output)

No separate retrieval pipeline to build and no scientific datastore to host.

Learn more in Introducing DeepResearch.

Works everywhere you build

The examples above use the Python SDK. Wiley HLS is also available through REST, MCP, the Valyu CLI, Vercel AI SDK and more.

REST API

curl -X POST https://api.valyu.ai/v1/search \
  -H "Content-Type: application/json" \
  -H "x-api-key: $VALYU_API_KEY" \
  -d '{
    "query": "spider silk mechanical properties",
    "included_sources": ["wiley/wiley-hls"],
    "max_num_results": 10
  }'

Model Context Protocol

https://mcp.valyu.ai/mcp?valyuApiKey=your-key

Command-line interface

valyu search "spider silk mechanical properties" \
  --include-source wiley/wiley-hls

Valyu can also be added as a tool inside applications built with the Vercel AI SDK and other frameworks.

Get started

The Wiley x Valyu HLS Startup Program is live for eligible startups.

• Playground: platform.valyu.ai
• API key: platform.valyu.ai
• Free credits: $10 when getting started, with no credit card required
• Documentation: docs.valyu.ai
• Questions: contact@valyu.ai

Valyu builds the search and research layer for AI applications working with specialist knowledge.

Its Search and DeepResearch APIs connect agents to authoritative sources across scientific research, patents, clinical trials, company filings, market data and the wider web through one natural-language interface.

Every result retains a path back to its source, giving agents the context they need and users the ability to inspect the evidence behind the output.