- Specialization
Biotechnologyand 1 more specialization valuesLess
- Scientific Discovery
- Business
Scientific Researchand 1 more business valuesLess
- Software Applications
- Market
- Life Sciences
- Ecosystem
- AI for science
- Customers
Enterprisesand 1 more customers valuesLess
- Researchers
More details
- Organization type
- Commercial Company
- Ecosystem
- AI for science
- Business
- Scientific Research, Software Applications
- Specialization
- Biotechnology, Scientific Discovery
- Market
- Life Sciences
- Customers
- Enterprises, Researchers
- Delivery models
- Professional Services
- Revenue models
- Services Fees
- Listing status
- Not classified
- Latest equity round
- Not classified
- Reported funding amount
- Not classified
About
Ångström AI builds generative-AI molecular simulations for pre-clinical drug development, selling to biotech and pharma companies as a substitute for wet-lab experiments. Its differentiator is constraining generative models with quantum-accurate physics, producing experimentally accurate results reportedly more than 100× faster than wet-lab work.
Market
Ångström AI competes in AI-powered computational drug discovery and molecular-simulation software for pharmaceutical and biotechnology R&D, positioning its platform as a way to replace or reduce wet-lab experimentation in preclinical development. Its differentiation is the combination of quantum-mechanically accurate physics models such as MACE and machine-learning interatomic potentials with generative and diffusion models, targeting experimental-level accuracy at substantially higher speed than conventional simulation approaches.
Pharmaceutical and biotechnology companies working on preclinical drug development, especially teams responsible for drug discovery, computational chemistry, molecular modeling, or R&D validation. The likely buyer is a preclinical or computational-drug-discovery leader seeking to evaluate drug-candidate efficacy, safety, solubility, and bioavailability while reducing reliance on wet-lab experiments; the company does not publicly specify a particular customer-size band.
At a Glance
Problem
Ångström AI targets the experimental bottleneck in preclinical drug discovery. Pharma and biotech teams traditionally rely on wet-lab assays to determine whether drug candidates will interact effectively and safely, as well as whether they have properties such as solubility, lipophilicity, and crystal stability. The pain is both costly and slow: drug development can take 10–12 years and roughly $2 billion overall, while individual solubility experiments may take days or weeks and require substantial laboratory effort. The killer use case is using accurate simulation to screen or validate candidates—initially solubility and related bioavailability questions—before committing to more wet-lab work.
Product / Service
Ångström AI provides client-facing scientific software and molecular simulations for pharma and biotech. Its public materials point to a B2B engagement model built around demonstrations and pilots rather than a documented self-serve product. The system combines the quantum-mechanically accurate MACE model of molecular interactions with generative and diffusion models that accelerate simulation while keeping generated molecular states physically consistent. The company says its simulations can reproduce wet-lab-level accuracy while running more than 100 times faster, enabling faster evaluation of efficacy, safety, solubility, lipophilicity, and crystal stability.
Market
Ångström AI competes in AI-powered drug discovery, computational chemistry, molecular simulation, and scientific software. Its most relevant adjacent competitors and incumbents include Schrödinger, whose platform provides physics-based molecular simulation for pharmaceutical and biotechnology research, along with BIOVIA, Certara, Chemical Computing Group, and OpenEye Scientific. Ångström’s differentiation is the combination of physics-constrained generative AI, experimental-level accuracy, and substantially faster simulation; the evidence does not establish a formal head-to-head competitor set.
The company has early commercial traction rather than being purely pre-revenue. It entered Y Combinator’s Summer 2024 batch and is listed as active with a five-person team; it reported experimental solubility results within wet-lab error ranges and a $150,000 pilot with a pharma company. Preqin reports a September 2024 seed round from the Pioneer Fund, while one third-party database estimated approximately $900,000 in annual revenue in 2025. However, no public source here names the pharma customer, provides audited revenue, or demonstrates broad recurring adoption, so Ångström remains an early-stage company.
Founders & Leadership
Funding History
Y Combinator
Recent News
Ångström AI announced generative-AI molecular simulations intended to replace wet-lab experiments for pharma and biotech. Its announcement describes fast, experimentally accurate simulations of molecular interactions to assess drug binding and behavior.
Y Combinator lists Ångström AI as an active S2024 company with five employees in San Francisco. The profile says the company developed a physically accurate generative-AI simulation of multiple molecules, published water-solubility results, and began a 150K pilot project with a pharmaceutical company.
Ångström AI researchers and University of Cambridge collaborators released a preprint evaluating CSP-MACE-Å, a machine-learning interatomic potential intended to replace DFT in crystal-structure prediction. The paper reports performance comparable to DFT benchmarks, better results than MACE-POLAR-1 and UMA-OMC, and substantially faster calculations.
Preqin’s profile describes Ångström AI’s generative-AI software for accelerating molecular simulations and records a seed round from the Pioneer Fund in September 2024. This is profile coverage published during the period, not evidence of a new funding round in the last 12 months.
Active Roles
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Get notified when they postBusiness Model
Ångström AI appears to use a B2B project and enterprise model, selling molecular-simulation technology to pharma and biotech customers through paid pilots and drug-development engagements. The evidence cites a $150K pharma pilot and directs prospects to request a demo; standardized public pricing is not shown.