Ataraxis AI

Pre-clinical

San Francisco, United StatesFounded 2023ataraxis.ai

Ataraxis AI is a clinical-stage AI company spun out of New York University in 2023, focused on developing and deploying AI-powered tools to improve cancer prognosis and treatment selection. The company has raised a $20.4 million Series A round and has launched its first product, Ataraxis Breast, a prognostic tool that delivers results within 24 hours using existing pathology slides. Backed by a world-class team and advisors like AI pioneer Yann LeCun, Ataraxis is collaborating with top international cancer centers to validate and implement its technology across multiple cancer types.

Founded

2023

Focus

AI / Machine Learning

AI Company Overview

Technology Platform

Proprietary AI platform using multi-modal learning and self-supervised foundation models (e.g., Kestrel) trained on hundreds of millions of pathology images to extract novel morphological biomarkers for cancer prognosis and treatment response prediction.

Funding History

Total raised: $3.5M

Seed$3.5MY CombinatorAug 15, 2023

Opportunities

The primary growth opportunity is expanding the application of its Kestrel foundation model beyond breast cancer to develop rapid prognostic tests for other major cancer types with high unmet need.

Additionally, deepening integrations with electronic health records and pathology laboratory information systems can drive seamless adoption and create a durable competitive moat.

Risk Factors

Key risks include the challenge of changing entrenched clinical practices and securing reimbursement from payers for a novel AI-based test.

The regulatory landscape for AI/Software as a Medical Device (SaMD) is complex and evolving, posing potential hurdles for expansion.

Technological competition from both agile startups and well-resourced large tech and diagnostics companies is intense.

Competitive Landscape

Ataraxis competes with established genomic test providers (e.g., Exact Sciences' Oncotype DX) on speed and tissue conservation, and with AI-pathology companies (e.g., PathAI, Paige) by focusing on standalone prognostic tests rather than pathologist workflow tools. Its differentiation lies in its clinically deployed product, proprietary pan-cancer foundation model, and strong academic-AI research foundation.