Triatomic Capital
VC Fund
New York, United States
Triatomic Capital is a VC fund in New York focused on Software and Manufacturing. Deep tech. Health tech. New economy. AI. Helping great entrepreneurs build 'century-defining' technologies & businesses.
- Total investments:
- 20
- Last investment:
- Lead investor:
- 40%
Last updated:
For AI agents: llms.txt
Industries Triatomic Capital invests in
Stages Triatomic Capital invests in
Countries Triatomic Capital invests in
Round sizes
Round size
- Seed
- $5M–$50M
- Series A
- $7M–$100M
- Series B
- $35M–$500M
Investment Focus
Industry
- Software 5 (25%)
- Manufacturing 4 (20%)
- Artificial Intelligence 4 (20%)
- Computer 3 (15%)
- Life Science 3 (15%)
Stage
- Series A 10 (50%)
- Series B 5 (25%)
- Seed 2 (10%)
- Series C 1 (5%)
- Post-IPO Equity 1 (5%)
Country
- United States 14 (70%)
- Japan 1 (5%)
- Spain 1 (5%)
Investments
| Company | Description | Round | Links |
|---|---|---|---|
Radical Numerics
|
Radical Numerics develops a unified AI model that comprehensively understands and generates biological data, integrating DNA, RNA, proteins, and all molecular components of living systems into a single framework. The company is known for its Evo and Evo 2 models, which are large biological AI models that have been trained on extensive DNAsequences. | $50M / Seed / Jun 15, 2026 | |
Zapata Quantum
|
Zapata Computing is a quantum software company that offers computing solutions for industrial and commercial use. It provides hardware-agnostic solutions for simulation, optimization, and machine learning applications in chemistry, finance, logistics, pharmaceuticals, engineering, and materials.Zapata Computing is a spun out of Harvard Universitylaunched by a group of Harvard scientists, including Alán Aspuru-Guzik.The company was founded in 2017 and is headquartered in Boston, Massachusetts. | $15M / Post-IPO Equity / Apr 08, 2026 | |
Gimlet Labs
|
Gimlet Labs is an applied research lab focused on developing next-generation AI infrastructure. | $80M / Series A / Mar 23, 2026 | |
Axiom
|
Axiom Math AI is information technology startup that builds self-improving superintelligence. | $200M / Series A / Mar 12, 2026 | |
MatX
|
MatX, a manufacturer of computer chips, is dedicated to constructing a computing platform for artificial general intelligence (AGI). Their specialty lies in creating hardware that combines profound domain experience tailored for large language models, graphics processing units, and various machine-learning models. By doing so, MatX aims to empowerdevelopers and programmers to enhance the efficiency, speed, and affordability of AI applications. | $500M / Series B / Feb 24, 2026 | |
Efficient Computer
|
Efficient Computer develops processor technology focused on improving energy efficiency for compute-intensive workloads. The company designs general-purpose processors and computing architectures that aim to reduce power consumption while maintaining performance across embedded and edge applications. Its technology is built to support artificialintelligence, signal processing, and other demanding tasks within constrained power environments. Efficient Computer provides hardware platforms and related tools that enable device manufacturers and developers to integrate energy-efficient processing into their products. The company’s offerings address applications where performance per watt is a key design consideration. | $60M / Series A / Feb 18, 2026 | |
d-Matrix
|
D-Matrix is developing a platform that enables data centers to handle large-scale generative AI inference with high throughput and low latency. The company’s offering includes the Corsair™ inference accelerator card, the JetStream™ I/O networking accelerator, and the SquadRack™ rack-scale system, all designed to work together to deliverefficient inference compute. Their technology brings memory and compute closer together, embedding processing inside memory to reduce data movement, improve speed, and energy efficiency. The stack also includes software tools for deployment, model debugging, and performance monitoring, enabling enterprises to scale inference workloads across models and usage scenarios. | $275M / Series C / Nov 12, 2025 | |
Chemify
|
Digitising Chemistry and Chemical Discovery | $50M / Series B / Oct 21, 2025 | |
Chalk
|
Chalk is a data platform that powers machine learning and generative AI. Chalk's best-in-class developer experience enables data teams to declare features and their dependencies with idiomatic Python in online, streaming, and batch environments. Chalk compiles these definitions into parallel pipelines that run on a Rust-based engine. Thesepipelines use the same source code to serve temporally consistent training sets to data scientists and live feature values to models. This re-use ensures that feature values from online and offline contexts match and dramatically cuts development time. With Chalk, engineers, data scientists, and analysts can focus on their unique products while Chalk seamlessly handles data infrastructure. | $50M / Series A / May 28, 2025 | |
iPronics
|
iPronics develops the innovative concepts of general-purpose integrated programmable photonic systems. | $20.9M / Series A / Jan 28, 2025 | |
| See all 20 investments → | |||
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FAQ
What does Triatomic Capital invest in?
Triatomic Capital invests primarily in Software, Manufacturing and Artificial Intelligence startups, most often at Series A and Series B stage. Most of the 20 investments tracked by Shizune back companies in United States. The Investment Focus section breaks down every industry, stage and country in the portfolio.
What is Triatomic Capital's check size?
Triatomic Capital typically joins rounds of $5M–$50M at Seed, $7M–$100M at Series A and $35M–$500M at Series B. These ranges are 10th–90th percentile round sizes calculated from confirmed public funding rounds, so they are a realistic guide to the rounds Triatomic Capital participates in.
When did Triatomic Capital last invest?
The most recent investment recorded for Triatomic Capital closed in Jun 2026. Shizune tracks 20 investments in total for this profile, including round sizes, stages and portfolio companies, all sourced from confirmed public funding rounds and refreshed monthly.
Is Shizune's investor data accurate?
Yes — every stat on this profile is calculated from confirmed public funding rounds monitored across hundreds of sources since 2020. This profile was last refreshed in Sep 2026 and is updated monthly. Spotted something off? Use the “Suggest an edit” link near the top of the page.
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