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AddedJun 26, 2026
UpdatedJun 26, 2026
Ataraxis AI

Ataraxis AI

Series A

Ataraxis AI develops AI-powered precision medicine tools for cancer care, integrating digital pathology and clinical data to personalize treatment selection.

HQ
New York, NY, US
Founded
2023
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Contents

  1. 01Executive Summary
  2. 02Products & Services
  3. 03Competitive Strengths
  1. 01Executive Summary
  2. 02Products & Services
  3. 03Competitive Strengths

Memo

Ataraxis AI aims to impact at least 50 percent of new cancer cases by 2030 through its AI-powered precision medicine platform. The company is expanding beyond breast cancer into pan-cancer applications, building on its foundation models trained on hundreds of millions of pathology images.

The company has established clinical partnerships with top international cancer centers and continues to validate its tests through real-world studies and prospective clinical trials. Ataraxis Breast tests are delivered as laboratory-developed tests through a CLIA-certified laboratory.

Product Overview

Ataraxis Breast integrates digitized H&E pathology slides with clinical data to generate prognostic and predictive insights for breast cancer treatment. The platform includes RISK for recurrence prediction, CTX for chemotherapy benefit, and NEO for neoadjuvant therapy response.

Tests are delivered through a CLIA-certified laboratory with same-day turnaround, using only standard biopsy slides without exhausting tissue or requiring additional procedures.

Competitive Advantages

Ataraxis AI leverages AI foundation models trained on hundreds of millions of pan-cancer pathology images to extract novel morphological features correlated with patient outcomes. The company delivers same-day results using standard H&E slides without exhausting tissue, a significant improvement over traditional molecular genomic tests.

Unlike legacy assays often limited to specific breast cancer subtypes, Ataraxis Breast supports all major subtypes including TNBC and HER2-positive disease, and offers quantifiable individualized predictions rather than non-actionable risk categorizations.