SigTuple vs Tempus

Tempus has a disclosed valuation of $8.1B, while SigTuple's valuation is not publicly available, making a direct size comparison difficult. Tempus employs 2500 people.

Tempus has raised more in total funding at $1.1B, compared to SigTuple's $20M — a gap of $1B. Combined, the two companies have completed 8 known funding rounds.

Tempus leads with an Awaira Score of 84/100, while SigTuple sits at 60/100. That 24-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

SigTuple was founded by Rohit Kumar Pandey in 2015. Tempus was founded by Eric Lefkofsky in 2015. Visit each company's profile on Awaira for a full founder biography.

SigTuple: SigTuple develops AI-powered automated pathology solutions that digitize and analyze microscopy slides for blood, urine, sputum, and semen samples, enabling high-throughput diagnostic testing without the constant presence of trained pathologists. The company's AI-Minth platform uses robotic sample preparation, high-resolution imaging, and deep learning analysis to deliver diagnostic-grade results.\n\nThe company raised approximately $20M in Series B funding and has deployed its automated microscopy systems at diagnostic labs, hospitals, and blood banks across India, processing millions of diagnostic samples. SigTuple has received regulatory approvals for its diagnostic AI products and has established partnerships with major diagnostic laboratory chains.\n\nIndia faces a severe shortage of qualified pathologists relative to population, creating an acute need for AI-assisted diagnostic automation. SigTuple's approach of combining hardware, robotics, and AI in an integrated system addresses the complete diagnostic workflow rather than just the software layer, creating higher deployment barriers but also higher switching costs and stronger network effects from accumulated diagnostic data. Tempus: Tempus is an AI-driven oncology and precision medicine company founded in 2015 that utilizes machine learning and data analysis to improve cancer treatment outcomes. The platform aggregates and analyzes vast datasets including clinical data, imaging, molecular information, and outcomes to identify personalized treatment strategies for cancer patients. Tempus's core technology uses artificial intelligence to match patient-specific tumor characteristics with optimal therapeutic options, enabling oncologists to make data-informed treatment decisions. The company operates primarily in the United States and serves hospitals, health systems, and oncology practices through its cloud-based platform. Its applications span multiple cancer types including lung, colorectal, breast, and ovarian cancers. Tempus has secured $1.3 billion in total funding and achieved a valuation of $8.1 billion, reflecting significant investor confidence in precision oncology. The company went public, transitioning from private to public markets. Tempus competes with other AI health platforms and precision medicine companies like Foundation Medicine and others focused on genomic analysis and treatment selection. The company's growth trajectory reflects expanding adoption of AI-driven oncology tools and increasing demand for personalized cancer treatment protocols. Its competitive positioning centers on its data infrastructure scale and machine learning capabilities applied to complex clinical decision-making. Tempus combines clinical, imaging, and molecular data through AI to provide real-time oncology treatment recommendations at scale across U.S. health systems.

Both SigTuple and Tempus launched in 2015. Same year, but even a few months' head start matters in AI — early movers lock in data, talent, and customer relationships fast.

SigTuple has about 100-500 employees; Tempus has about 2500. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both SigTuple and Tempus compete in AI Healthcare, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.