The Burgeoning Ecosystem for AI-Accelerated Science

Welcome to the party, Anthropic!

If you haven’t seen Anthropic’s announcement of Claude Science, their new workbench for enabling the scientific workflow, it’s well worth a read. They’re the latest entrant into a fast-growing ecosystem of AI tools built to accelerate the pushing of boundaries. Google has its Co-Scientist (now peer-reviewed in Nature), OpenAI has Prism, and now Anthropic has Claude Science.

But the AI-accelerated research ecosystem isn’t just made up of products from the frontier model companies. Smaller, independent labs are building real systems too — like FutureHouse’s Robin, a multi-agent system for experimental biology. The ecosystem is growing in other places, too: AI authoring systems, AI reviewing systems, co-scientist systems, and a host of other providers. At Valency, we’ve been thinking a lot about this ecosystem since our inception and about how all of these components might interlock in the agentic science era.

In some ways, our initial offering Valency Bond shares some of the same components as Claude Science. We make reasoning agents smarter at doing science by giving them easy access to real scientific articles. We even surface some of the same data sources. But ultimately, we think Valency Bond is a uniquely positioned offering in this ecosystem. Here’s why:

1. Built for academics and non-profits. Valency Bond is people-centric, designed first and foremost around the needs of researchers at universities and non-profit institutions. We don’t charge for their access.

2. LLM-agnostic. Whether you’re using Gemini, ChatGPT, or Claude, our connector plugs into your scientific and research workflows. And through bearer tokens, you can use Valency in your own LLM harness — including with open-weight models in your own front end.

3. Cross-source data quality. This one is more subtle, and perhaps more important. Any single data source served through MCP comes with its own data-quality challenges. As we’ve brought more and more sources into our growing corpus, we’ve found that intercomparing across all of these different sources is a powerful way to clean them up — and to provide better, fresher answers to our growing community. On top of that, our toolkit includes capabilities like semantic search and trending topics. We’re distilling the actual questions researchers are asking into tools that give them better, faster answers.

4. Discovery and ideation happen across fields. Serving individual data sources as separate tools risks the siloing effects we as scientists want to avoid during discovery and ideation phases. De-balkanizing search across academic and other data sources is extremely potent and we’ve taken steps to ensure that is how our users can work.

Today’s announcement is a great reminder that this new agentic science ecosystem is just starting to flourish — and we welcome Anthropic’s entrance. This AI-accelerated scientific ecosystem will only broaden, and we can’t wait to tell you about our new product offerings. Watch this space — and definitely sign up to use Valency Bond.