Agents can help you do more science, but you still need to understand what they’re doing to direct them and communicate results to your colleagues. That’s why we built Rao’s new Reports feature.
Launch Rao to work on a problem or assemble findings from a conversation and report back to you in a concise, visual deck. Iterate on ideas by asking Rao to run new analyses and add slides. When it comes time to read out to others, assemble decks for talks or meetings in minutes, not hours.
Reach out to try it!
Check out matplotgym - our new benchmark for AI scientific figure generation!
1/ A scientific paper starts and ends with its figures. A figure compresses a scientific claim and the evidence for it, and making the right figure is evidence that you understand the science you’ve done.
So: given a paper’s raw data, can a model create a figure that accurately represents a claim?
Introducing matplotgym, our new benchmark on scientific figure generation from @TuvaAI.
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Introducing Tuva Reports: a new way to discover more, faster, by turning every scientist into a PI managing a team of agents.
Launch agents on long horizon tasks and have them report back to you in concise, understandable slides. All of the agents' work is backed by detailed traces and Rao's research memory so you can double check and dig into every result. Build on ideas by having agents add to decks with new results, all under your supervision.
Use Tuva Reports to have agents work on threads in parallel to you and generate precise decks for talks in minutes. Reach out to learn more!
At Tuva, we think of scientific research like a tree diagram. You start at layer 0, and from there you have n possible edges leading to different nodes on layer 1.
We think AI is most useful for surfacing more of those edges - helping you see all the directions your research could go before you pick one.
That's why we're building proactive agents that find those edges for you, based on where you are in your project, without you having to ask.
ALT Branching tree diagram. Source: Wikimedia commons
An AI researcher at Princeton uses Rao to explore new research directions! He prefers Claude as a sounding board for ideas, but wants Codex to do preliminary analysis on his topics of interest. Rao lets him orchestrate agents across both.
Reach out if Rao could be useful for you! DM us or check out our website linked below.
The GPT-6 release might have you toggling between Claude Code & Codex - Rao’s new daily log makes it easier to keep track of the work you’ve done across both. The daily log automatically catalogs progress across Claude Code, Codex, and Rao.
As always, reach out if Rao could be useful for your work! DM us or check out our website linked below.
A biophysics PhD student uses Rao to connect his conversations across Claude Code, Codex, and Rao itself. By centralizing context, he uses Rao to look across his entire workspace and recognize open threads.
If Rao could be useful for your research, we’d love to talk! DM us or visit our website linked below.
Excited to announce the the new Rao desktop app! Here, you can coordinate agents that can work across the Rao interface, Claude Code, and Codex and act based on where your project actually is.
One new agent runs proactive literature reviews, referencing your project context to find papers most relevant to your recent progress and ideas. It’s hard to know when inspiration will be most helpful and it’s often tucked away in years-old papers, so we’ve designed this Rao agent to inspiration-hunt for you.
Visit our website or DM us to try Rao! Link in the comments.
