Ai2 Newsletter

Scientific research grows more logistically complex by the day. Scientists have to juggle navigating vast bodies of literature, running experiments, analyzing data, and iterating—quickly. Making matters worse, fragmented tools and unintuitive workflows can easily lead to missed relevant findings, hamstringing the discovery process.

That’s why we developed Asta, an ecosystem of AI tools for science, including a capable agentic research assistant. We believe AI has the potential to support and accelerate scientific discovery, and that Asta – the culmination of years of research – is a significant step in that direction.

What’s unique about Asta is that it’s designed to work the way scientists think, helping frame research questions and tracing ideas back to evidence. Importantly, Asta features benchmark evaluations to ensure its components remain robust and highly transparent—and grounded in science itself.

Jonathan Whitaker, a data scientist at the AI R&D lab Answer.AI, says that Asta’s paper-finding tools surface research artifacts that other agentic assistants miss. 

“We're at ~2,000 papers in our shared library, so we'll often hit questions like, ‘Didn't they do this before in that paper?' and then we'll have a minute or two of nobody remembering the name to go check,” he says. “Having good paper search for something specific like this is so nice, and Asta has nailed it the times I've needed it.”

Asta can also facilitate literature reviews—comprehensive syntheses of scholarly sources on particular subjects. It turns research questions into structured summaries, drawing on a library of millions of papers. 

“[When] some new thing comes out or we're looking at something specific, it's nice to get basically a quick lit review of what else is related [or] narrow in on some specific thread of a work,” adds Whitaker. 

David Hendrickson, CEO and Principal Consultant at GenerAIte Solutions, uses Asta to explain new technologies—and even debunk marketing claims around products. 

“From my perspective, this is the best tool on the market for academic-based research,” he says. “Nothing else comes close.”

There’s even more to Asta than powerful agents for literature search. AstaBench is an environment and toolset to test the scientific reasoning capabilities of agents, while Asta resources is a collection of baseline models and methods to build, test, and refine agents for scientific work.

We plan to expand Asta soon, first with a data analysis capability that can generate hypotheses, run statistical tests, and explain the results succinctly. Down the road, the aim will be to introduce features that support replicating computational experiments and refining research questions, as well as writing code for scientific simulations, simple machine learning, and more.

Our goal isn’t to replace scientists or automate science end-to-end. Rather, we see Asta as an AI collaborator—one that’s empirically validated and trustworthy. Importantly, Asta will always be largely open, allowing researchers to use it how they want and adapt it to their needs. 

Learn more about Asta in our blog, and get started here.