Geodesic Intelligence

Build AGI that discovers the shortest path from biology to medicines

[Geodesic Intelligence @Geodesiclab]

Introducing NovaAtom-Lite, an all-atom structure prediction model for drug discovery.

It predicts the structures of proteins, nucleic acids, and the molecules they bind, including how they fit together.

NovaAtom-Lite outperforms both IsoDDE and AlphaFold 3 on FoldBench antibody–antigen structure prediction (DockQ ≥ 0.23):

NovaAtom-Lite: 79.07% (n=172)

IsoDDE: 75.58%

AlphaFold 3: 47.90% (n=167)

Our evaluation uses 5 seeds × 5 samples, with the top-1 prediction selected by the model's own ranking score.

Better structure prediction. A stronger starting point for your next experiment.

Live today via Geodesic API and NovaDDE.

🔗 API: https://t.co/mBdzq3sA2s

🔗 NovaDDE: https://t.co/hoCwjST34V

🔗 Model Card: https://t.co/p4aoXHuc7B

[Geodesic Intelligence @Geodesiclab]

Runs N’ Poses tests how well models predict protein–ligand structures on examples that look different from the training data. The chart goes from the least familiar cases on the left to the closest matches on the right.

NovaAtom-Lite leads across all eight groups:

• Least familiar (n=63): NovaAtom-Lite 47.6% vs AlphaFold 3 23.8% · OpenDDE 15.9%—twice AlphaFold 3’s success rate.

• Most familiar (n=664): NovaAtom-Lite 91.0% vs AlphaFold 3 88.2%.

From the most familiar cases to the least familiar, NovaAtom-Lite’s success rate drops 43 points. The other models drop 64–75 points. It holds up better on examples that look less like the training data.

We used the publicly available predictions from AlphaFold 3, Chai-1, and Boltz-1, while running NovaAtom-Lite and OpenDDE ourselves. All results use the same ligands and success criteria: symmetry-corrected RMSD < 2 Å and LDDT-PLI > 0.8.

[Geodesic Intelligence @Geodesiclab]

Introducing NovaAtom-Lite, an all-atom structure prediction model for drug discovery.

It predicts the structures of proteins, nucleic acids, and the molecules they bind, including how they fit together.

NovaAtom-Lite outperforms both IsoDDE and AlphaFold 3 on FoldBench antibody–antigen structure prediction (DockQ ≥ 0.23):

NovaAtom-Lite: 79.07% (n=172)

IsoDDE: 75.58%

AlphaFold 3: 47.90% (n=167)

Our evaluation uses 5 seeds × 5 samples, with the top-1 prediction selected by the model's own ranking score.

Better structure prediction. A stronger starting point for your next experiment.

Live today via Geodesic API and NovaDDE.

🔗 API: https://t.co/mBdzq3sA2s

🔗 NovaDDE: https://t.co/hoCwjST34V

🔗 Model Card: https://t.co/p4aoXHuc7B

[Geodesic Intelligence @Geodesiclab]

We also tested NovaAtom-Lite on PXMeter’s PXM-22to25-AB antibody–antigen set—528 PDB entries, compared with 172 targets in FoldBench.

• NovaAtom-Lite 66.05% (528 entries / 383 clusters) vs OpenDDE 51.0% (494 entries)—a 15-point margin.

• ESMFold2 follows at 42.9%, Protenix-v1 at 40.2%, and Boltz-1 at 19.6%.

PXMeter is an open-source toolkit for evaluating predicted structures. This set draws on PDB releases from 2022–2025, filtered for low homology to earlier structures. Success here means DockQ ≥ 0.23.

[Geodesic Intelligence @Geodesiclab]

Excited to partner with @GenScript to launch the Beyond Binding Challenge! 🧬

AI-designed antibodies need to go beyond binding affinity to become real therapeutics.

Let's push the boundaries of AI-driven antibody design and turn computational breakthroughs into real-world impact.

Up to $2.5M in awards. Stay tuned!

[GenScript @GenScript]

Binding is just the beginning 🧬

@GenScript and @GeodesicLab are launching the Beyond Binding Challenge to benchmark AI-designed antibodies for binding and developability.

Compete for up to $2.5M in awards. Stay tuned: https://t.co/hkcm1Xxvzy

#AIProteinDesign #DrugDiscovery

[Geodesic Intelligence @Geodesiclab]

What does an AI-native workflow for protein binder design look like in practice?

In our latest post, we walk through a pilot design run using NovaDDE:

Given a target, the AI agent analyzes the design problem, helps select an epitope and design approach, submits the job, and guides the computational evaluation of the resulting candidates.

We also share some of the directions we’re exploring as we continue to develop the workflow.

A closer look at NovaDDE and where we’re taking it next:

https://t.co/I9eOefsOP6

[Geodesic Intelligence @Geodesiclab]

Today, we’re launching the Geodesic API Platform.
https://t.co/0NrJSBzYG1

For the first time, Geodesic is making our AI models and drug discovery capabilities available through APIs.

At its core is NovaAtom, our in-house model for predicting the structures of proteins, small molecules, nucleic acids, and their interactions.

Now available in Lite Preview, this is the first time NovaAtom has been made available beyond Geodesic’s own discovery platform.

Alongside NovaAtom, we’ve integrated the field’s core models — carefully curated and continuously updated.

To use the API:

curl -X POST https://t.co/6HF70T4oSQ \
-H "Authorization: Bearer $GEODESIC_API_KEY" \
-F "model=novaatom" \
-F 'params={"jobName":"rbd-nanobody","sequences":">rbd\nTNLCPFGEVFNATRFASV...\n>nb\nQVQLVESGGGLVQAGGSLR..."}'
Poll the job, pull the results, and feed them directly into the next model.

Your AI assistant can use the platform directly, too. Connect Claude Code, Codex, or your own agent with one URL and an API key.

We manage the integrations and handoffs. You focus on the science.

Understand biology. Predict structures. Design proteins. Discover molecules.

One key. One interface.

Start building today!

[Geodesic Intelligence @Geodesiclab]

NovaDDE Plus is now live!

Built for scientists who use AI for drug discovery every day — more compute, priority access, concurrent runs, API access, and end-to-end campaign execution.

$30/month and sign up by September 25 to get your first month free.

Our goal is simple: put the most powerful AI for drug discovery into the hands of every scientist.

https://t.co/eOpEF3XKoQ

[Geodesic Intelligence @Geodesiclab]

We’re launching the Geodesic Grand Challenges.

What are the hardest questions in drug discovery that, if solved, could change what’s possible over the next 5–10 years?

We’re asking you to help define them.

Selected questions will become official Geodesic Grand Challenges. Each selected contributor receives 10,000 Geodesic credits.

Once the challenges are selected, we’ll open a call for solutions, with a $1 million prize for a verified solution to each challenge.

The next breakthrough starts with the right question.

Submit yours！
https://t.co/hQZUWhuqyN

[Geodesic Intelligence @Geodesiclab]

6/ Today is Day 1 for Geodesic Intelligence.

NovaDDE is live.
NovaAtom-Lite-Preview is here.
Larger NovaAtom models are coming.
Our wet lab is scaling.
And there is much more ahead.

We’re building AI to create medicines, and we’re hiring exceptional people to build it with us.

Explore NovaDDE: https://t.co/o42snNpXK9
Join us: https://t.co/LqdvL4OWFf

[Geodesic Intelligence @Geodesiclab]

1/ Today, we’re introducing Geodesic Intelligence, and launching NovaDDE and NovaAtom-Lite-Preview.

Geodesic is building an AI-native platform for protein therapeutics, building AGI for drug discovery to find the shortest path from biology to medicines.
https://t.co/SNuR5NPVxs

[Geodesic Intelligence @Geodesiclab]

5/ But computation alone isn’t enough. Biology has to work in the real world.

That’s why we’re building our own wet-lab capabilities alongside our AI stack, and creating a closed learning loop between AI and the physical world:

AI → Design → Experiment → Learn → Repeat.

Better models generate better experiments. Better experiments generate better data. Better data builds better models.