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Deep Principle

Category: AI in Climate / Energy

Deep Principle utilizes AI and first-principles calculations to accelerate materials discovery, chemical reaction optimization, and formulation development. The company specializes in catalytic materials and carbon capture technologies. Deep Principle was founded in 2024. The company is led by Jia Haojun. Based in Cambridge, Massachusetts, USA. Team size: 50+. Total funding raised: ~$24M total (all confirmed rounds). Latest round: Series A (RMB 100M/~$14.1M, Nov 2025 led by Gobi Partners & Ant Group). Key investors include ["Alibaba Entrepreneurs Fund","Ant Group","Lenovo Capital","Taihill Venture","Baidu Ventures","Vertex Ventures (Seed++ round)"].

Founded
2024
Headquarters
Cambridge, Massachusetts, USA
Team size
50+
Total funding
~$24M total (all confirmed rounds)

Value proposition

Reduces R&D timelines for material discovery and chemical processes through autonomous AI-driven experimentation, cutting costs and accelerating innovation cycles.

Products and solutions

["AI platform for high-throughput materials screening","Generative AI models for reaction pathway prediction","Cloud-based simulation tools for property optimization","Automation systems for lab experimentation","ReactiveAI Platform with Agent Mira™ for autonomous materials discovery"]

Unique value

Integration of first-principles quantum mechanics with generative AI models to predict material properties and reaction mechanisms at unprecedented speed, combined with high-throughput autonomous experimentation.

Target customer

Industries requiring advanced materials and chemical solutions, including energy, pharmaceuticals, and industrial manufacturing. Current customers include L'Oréal and Sunsea Innovation with over RMB 10 million in commercial contracts.

Industries served

["Energy (carbon capture, battery materials)","Pharmaceuticals (catalysis, drug discovery)","Industrial chemicals","Sustainable materials","Cosmetics (L'Oréal partnership)"]

Technology advantage

Proprietary AI algorithms reduce computational costs by 70% compared to traditional methods, while maintaining high accuracy in material property predictions. Their L4 high-throughput autonomous laboratory (AI Materials Factory™) enables autonomous materials discovery.

How they differentiate

Deep Principle differentiates through integration of first-principles calculations with AI and high-throughput experimentation, whereas competitors often focus on deep learning architectures or specific domain applications like drug discovery.

Main competitors

["CuspAI","Lila Sciences","Atomwise","BenevolentAI","Insilico Medicine","Valence Discovery","Kebotix","Schrödinger","Citrine Informatics"]

Key partnerships

["Massachusetts Institute of Technology (research collaboration)","Alibaba Entrepreneurs Fund (strategic investment)","Ant Group (venture capital and AI infrastructure)","L'Oréal (commercial customer)","Sunsea Innovation (commercial customer)","DP Technology (strategic investment)"]

Notable customers

["L'Oréal","Sunsea Innovation","State-owned petrochemical company in China"]

Major milestones

["Co-founded by MIT-originated scientists Jia Haojun and Duan Chenru","Secured Series A funding in 2025","Published research in Nature Machine Intelligence","Featured in Forbes 30 Under 30 Asia List","Selected as 2025 World Economic Forum Technology Pioneer","Agent Mira™ AI agent for autonomous materials discovery launched"]

Growth metrics

Secured over RMB 10 million in commercial contracts with industry leaders such as L'Oréal and Sunsea Innovation. Published research in Nature Machine Intelligence. Featured in Forbes 30 Under 30 Asia List.

Market positioning

Positioned as an AI-for-science innovator in autonomous materials discovery, targeting both academic and industrial R&D markets with a focus on computational chemistry and reaction prediction.

Geographic focus

Primarily U.S.-based with research partnerships in academia (e.g., MIT, University of Cambridge), but targeting global materials innovation markets with strong presence in China.

Patents and IP

Holds 12+ patents in AI-driven materials discovery (as of 2025), including US Patent 11,452,341B2 for 'Machine Learning Systems for Catalytic Reaction Optimization'.

About Jia Haojun

MIT Ph.D. in Physical Chemistry, former MIT researcher specializing in AI-driven materials discovery and computational chemistry. Co-founded Deep Principle in 2024 after developing the initial concept during his doctoral studies.

Official website: