Eric Olson

If whatever you are building touches science, build it on Consensus. 💻 API & MCP portal: consensus.app/api-mcp/ 📄 Docs: docs.consensus.app/api-quick…

One call now runs multi-step research across 400M+ papers using our custom tools: - Semantic search - Citation crawling - Author search - DOI lookup - Full AI analysis Every response also returns word-for-word snippets from open access and licensed paywalled papers.

The world’s scientific knowledge is now one API call away 🌎 Today we’re launching the full Consensus agent within our API & MCP. Below is a tool we built on it in under an hour 👇

Finding an under-researched area you can start a study in has always been time-consuming. But not anymore. The new Research Gaps Matrix feature in Consensus turns one question into a coverage map to show you where research is missing. This makes it much easier to: 🔍 Find a under-researched niche you can start a study in ❗️ Identify gaps in your library of research that you should fill 📄 Find a cross section of population/method (or anything custom) to run a targeted follow up search Here's an example. If you went to a collection in your library and searched: "Show me a research gaps matrix comparing population to study method in this collection so I can see what I am missing" Consensus will create a table showing you different populations, different study types, and how many papers you have that cover each different area. If there are any missing, you can instantly run a targeted search for them. Read the full announcement and try it for free in Consensus today: consensus.app/home/blog/intr…

Today we're announcing our partnership with @aaas to bring the full text of the @ScienceMagazine journals to Consensus. We can now index, search, and cite from the full-text of every article in the Science family, so the next breakthrough is visible to researchers on day one.

Research doesn’t always start in a search engine anymore. That’s why we’re bringing Consensus to the AI tools people already use. Consensus is available in: → ChatGPT → Claude → Microsoft 365 Copilot The assistant you use may change. Your standard for evidence shouldn’t. Read more: consensus.app/home/blog/cons…

📚 New in Consensus: Collection Sharing Working on a group project? Now your whole group can search, save, and organize papers in one shared Collection. Add papers as you find them, ask questions across what your group has collected, and keep everything in one place. Less duplicate searching. Fewer lost links. Better group research.

The Consensus API & MCP are live 🎉 After a few months in closed beta with pharma teams, AI bio startups, and materials science groups, anyone can sign up and start building today. The academic search that powers Consensus, is now callable from your own systems.

We are excited to announce our partnership with @degruyter_brill, one of the world's leading publishers in the humanities and social sciences. Consensus can now index and utilize the full text of their paywalled journals. More precise results, AI responses cited from full text.

When Dr. Barbara Han reaches a question no one has studied directly, she uses Consensus to find the closest related research and identify the connections her lab needs to make. 🔎 That often means entering an unfamiliar field, learning its terminology, and tracing a path through adjacent bodies of literature. Consensus helps her get oriented quickly, surface vetted papers, and trace each answer back to the source. 📚 As she puts it, it helps her get past “that impenetrable wall of new disciplinary jargon” and reach the crux of what she needs to know.

Dr. Barbara Han’s lab at the Cary Institute looks for the missing connections between fields like virology, animal behavior, ecology, and soil chemistry to help predict outbreaks before they happen. Watch the short video to see how she uses Consensus to connect those disconnected areas of research, then read her full story: consensus.app/home/community…

🦠 What does soil have to do with Ebola? 🔬 Dr. Barbara Han, a disease ecologist at the @caryinstitute of Ecosystem Studies, uses machine learning to predict where infectious diseases may emerge next. 🦇 In this clip, she explains why that means following a virus far beyond the animal carrying it and into the overlooked systems that shape where it goes next.

Her lab helped identify which species could become new reservoirs for SARS-CoV-2. 220M+ papers. Plain-language questions. Every answer tied back to the most relevant sources. The full story of how she works with Consensus↓ consensus.app/home/community…

Dr. Barbara Han's lab (@caryinstitute) uses AI to predict which animal will carry the next pandemic. The clue could be in a virology paper. Or a soil chemistry paper. Or a geology paper. She uses Consensus to find where those fields meet and make predictions that save lives.

Trying the new Claude Science app from @AnthropicAI ? Set up the @consensusapp connector before you run anything. Just like humans, your bio agents should spend their cycles / tokens on needle-moving work, not on monotonous searching.