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AI FOR SCIENCE · ON THE RECORD

Radical AI

Materials and chemistryNew YorkFounded 2024Website ↗

Uses an AI Scientist + Self-Driving Lab to move materials R&D from predicted candidates toward physical experiments, manufacturing and final applications.

Research on the record

Graded by how far the evidence went, not how good the result is. See the methodology.

Read on AI4S.fyi

Direction analysis

AI4S.fyi's own reading of the public record, last checked 2026-08-09.

The claim

Materials discovery is experiment-constrained rather than compute-constrained; closing the physical loop can materially shorten materials R&D.

What has to hold for this route to work.

Experiments are the bottleneck. Compute can generate far more candidates than a physical lab can validate; the scarce resource is high-quality physical feedback.

Composition is not the material. Real performance also depends on structure, microstructure, processing and manufacturing history.

The lab must sit inside the AI loop. Hypothesis, synthesis, characterization, property testing and the next campaign must form a continuous feedback loop.

The loop must reach manufacturing. Sample throughput becomes industrial value only if the advantage survives scale-up, qualification and application.

Read the full analysis →

Also on the timeline

Founders' research on the record

Papers and results a founder of the company authored, from the timeline's bylines. Most come from before the company existed: they are the team's track record, not results the company has reported.

Graded by how far the evidence went, not how good the result is. See the methodology.

People

Only people the AI4S.fyi record has named: in a round, a timeline entry, commentary, an interview or a sourced role. Not the full team.

Funding rounds tracked

Disclosed funding$55M
Latest round$55MSeed · confirmed · 2025-07-18

Each round links to its line on the funding record, with its source.

Also in Materials and chemistry on the funding board

The other companies the funding board files under the same field, latest round first. A list of what the record tracks, not a ranking or a market map.

  • 2026-10-19MATARIASeed · tens of millions of yuanBuilds a multiscale materials model, from atoms to finished parts, that proposes candidates, narrows them with automated DFT and finite-element tools, and is tested by instrumented experiments; composites come first, then semiconductor and infrared materials.
  • 2026-10-15HolyvoltVenture round · $45MTrains battery-materials models on 18 years of cell-cycling data from the high-throughput lab it acquired, Wildcat Discovery Technologies, and lets the models choose what the lab makes and cycles next. Its first material is DRX, a cathode family with neither nickel nor cobalt.
  • 2026-10-14ScimplifyStrategic round · $25MDevelops manufacturing processes for specialty chemicals and critical materials in its own labs in Bengaluru and Hyderabad, then transfers them to a network of more than 500 partner factories. Its platform, Scinode, runs separate agents for research, manufacturing and quality control, choosing production routes and plants and tracking regulatory requirements.
  • 2026-10-13AlbertSeries B · $55MSoftware and AI for chemistry and materials R&D at chemical and consumer-goods companies: it captures experiments, structures the data and lets scientists search and reason over it, suggest formulations and design experiments.
  • 2026-10-12Matter MachinePre-Series A · £4MA University of Liverpool spin-out pairing AI prediction with experimental and characterisation expertise to find inorganic crystalline materials, aimed at batteries and catalysts.
  • 2026-09-24Soge Intelligent ComputingAngel · tens of millions of yuanAtomistic AI models with long-range interactions, fast parallel simulation and battery device modelling, sold to battery and chemicals firms; spun out of Shanghai Jiao Tong University.

All 17 in this field →

This page compiles what AI4S.fyi has recorded and links each item to its source. It is not a grade of the organization and not its complete history: a blank means the record has not caught up as often as it means nothing happened.