Achira

Achira

Atomistic drug-discovery simulation platform

Overview

Achira develops atomistic foundation simulation models for drug discovery, combining geometric deep learning, physics, quantum chemistry, and statistical mechanics to create advanced potentials and generative models. These models produce large synthetic datasets free from experimental artifacts, enabling true inverse design where researchers optimize compounds from desired properties. Achira serves pharmaceutical and biotech clients through partnerships, licensing, and collaborations, differentiating itself by integrating physics-based simulations with data-driven learning to mitigate data scarcity and high costs. The company's goal is to accelerate and make drug discovery more reliable by enabling inverse design that reduces time and expenses in identifying promising compounds.

Significant Headcount Growth

About Achira

Simplify's Rating
Why Achira is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & Analytics

AI & Machine Learning

Biotechnology

Healthcare

Company Size

11-50

Company Stage

Seed

Total Funding

$33M

Headquarters

New York City, New York

Founded

2024

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Simplify's Take

What believers are saying

  • Achira announced a $33M raise from Dimension, NVIDIA, Amplify, and Compound.
  • June 2026 BIO collaboration with NVIDIA expands distribution into life-sciences discovery workflows.
  • Hiring across ML, backend, and distributed systems shows active platform buildout in San Francisco and New York.

What critics are saying

  • Achira is still a 2024 company; product-market fit remains unproven by 2026.
  • Six open roles signal heavy burn before meaningful customer revenue arrives.
  • If NVIDIA or pharma partnerships stall, Achira becomes a research project, not a business.

What makes Achira unique

  • Achira pairs atomistic foundation models with physics, quantum chemistry, and geometric deep learning.
  • Its models generate synthetic molecular data, reducing dependence on scarce, artifact-prone experiments.
  • NVIDIA collaboration on molecular world models gives Achira compute and credibility.

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Funding

Total Funding

$33M

Above

Industry Average

Funded Over

1 Rounds

Seed funding is usually the first official round after pre-seed, when a startup has a prototype or concept. It’s typically used to develop the product, test the market, and start building the team. Investors here are often angel investors or early-stage venture capitalists.
Seed Funding Comparison
Above Average

Industry standards

$3.3M
$2M
Netflix
$2.3M
Instacart
$3M
Robinhood
$33M
Achira

Benefits

Remote Work Options

Hybrid Work Options

Flexible Work Hours

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Disability Insurance

Health Savings Account/Flexible Spending Account

PTO/vacation

Paid Vacation

Paid Holidays

Unlimited Paid Time Off

401(k) Retirement Plan

Stock Options

Company Equity

Wellness Program

Mental Health Support

Gym Membership

Conference Attendance Budget

Professional Development Budget

Phone/Internet Stipend

Home Office Stipend

Family Planning Benefits

Fertility Treatment Support

Professional Development Budget

Confluence

Growth & Insights and Company News

Headcount

6 month growth

20%

1 year growth

20%

2 year growth

28%
The National Herald
Apr 10th, 2025
Achira AI Secures $33M in Funding

Greek startup Achira AI has secured $33 million in funding from top investors, including Dimension, Nvidia, Amplify, and Compound. Achira aims to revolutionize AI-enabled drug development by integrating geometric deep learning, physics, quantum chemistry, and statistical mechanics to create advanced simulation models. This approach seeks to overcome limitations in current biomolecular simulations and machine learning models, accelerating the discovery of new molecules and treatments.

Endpoints News
Feb 21st, 2025
Nvidia-backed Achira debuts, blending AI and physics to model molecules

As he was testing new antivirals to halt a future pandemic, John Chodera encountered an unlikely set of new problems that ultimately helped lead to his new job. The computational ...

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