Bea Bakshi
Founder
C the Signs
C the Signs offers an AI-powered platform that evaluates more than 1,000 clinical and laboratory data points to produce cancer risk scores and actionable recommendations in under 60 seconds. The solution integrates with EHR systems via HL7/FHIR, providing clinician dashboards and patient portals that enable rapid referral and shared decision‑making while maintaining 99% sensitivity for cancer detection.
- Artificial Intelligence
- Healthcare Technology
- Software Only
Updated 6 months ago
Funding
Raised to date
$14.4MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 3 rounds
$8M · Series A
Announced Jan 2025
Disclosed cumulative: $14.4M
3/3
RoundDateAmountValuationInvestors
Founders
Product
Problem
Timely identification of cancer often requires multiple diagnostic steps and specialist interpretation, leading to prolonged intervals between symptom onset and definitive diagnosis. Underserved and ethnic minority populations face additional barriers that result in later-stage detection and poorer outcomes. Conventional workflows lack rapid, data-driven decision support that can be applied at the point of care.
Solution
C the Signs delivers an AI-powered diagnostic platform that evaluates over 1,000 validated clinical and laboratory data points to assess cancer risk in under 60 seconds. The system generates evidence‑based risk scores and actionable recommendations that clinicians can review instantly, enabling earlier referral and treatment planning. Its predictive models achieve 99% sensitivity, reducing missed cases while maintaining specificity. The platform integrates with existing electronic health record (EHR) systems and provides both clinician dashboards and patient‑facing portals to support shared decision‑making. By automating risk stratification, C the Signs shortens the diagnostic pathway and expands access to early detection for underserved communities across health systems.
Target Audience
Primary users are oncologists, primary‑care physicians, and diagnostic teams within hospitals and integrated health systems seeking rapid, AI‑assisted cancer risk assessment, particularly in settings serving ethnically diverse or underserved patient populations.
Features
- Multi‑modal AI engine trained on >1,000 clinically validated datapoints, including imaging, pathology, lab results, and demographic factors
- Real‑time inference delivering risk scores and recommendation reports in <60 seconds per patient
- 99% sensitivity for cancer detection with calibrated thresholds to balance false‑positive rates
- Seamless bidirectional integration via HL7/FHIR APIs for automatic data pull from and push to EHRs
- Clinician dashboard with visual risk stratification, trend analytics, and evidence citations for each recommendation
- Patient portal that presents personalized risk insights, educational content, and next‑step guidance while preserving data privacy (HIPAA‑compliant)
- Scalable cloud‑native architecture supporting deployment across large hospital networks and community health centers
- Continuous model monitoring and periodic re‑training using anonymized real‑world outcomes to maintain performance across diverse populations