QpiAI vs Scale AI

Scale AI has a disclosed valuation of $29B, while QpiAI's valuation is not publicly available, making a direct size comparison difficult. Scale AI employs 1,000 people.

Scale AI has raised more in total funding at $15.9B, compared to QpiAI's $3M — a gap of $15.9B. Combined, the two companies have completed 6 known funding rounds.

Scale AI leads with an Awaira Score of 84/100, while QpiAI sits at 35/100. That 49-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

QpiAI was founded by Nagendra Nagaraja in 2019. Scale AI was founded by Alexandr Wang in 2016. Visit each company's profile on Awaira for a full founder biography.

QpiAI: QpiAI develops a hybrid quantum-classical computing platform designed to accelerate AI and optimization workloads, combining quantum processing units with conventional AI accelerators. The company builds both quantum hardware prototypes and a software stack that abstracts quantum circuits for enterprise and research users in India.\n\nThe company raised approximately $3M in Seed funding and has partnered with national research institutions and defence organizations pursuing quantum-AI applications. QpiAI targets industries where combinatorial optimization problems — logistics routing, drug discovery, financial portfolio optimization — stand to benefit from quantum speedup.\n\nIndia's national quantum mission has allocated significant capital to domestic quantum computing development, and QpiAI is positioned as one of the few vertically integrated players with both hardware and AI software capabilities. As quantum hardware matures, the company's early investment in the full stack gives it a differentiated position in the emerging quantum-AI convergence market. QpiAI competes at the intersection of quantum computing and AI, a niche that remains largely experimental but is attracting increasing attention from enterprises exploring post-Moore's Law compute architectures. Its primary competitors include IonQ, Rigetti, and D-Wave in the quantum space, though QpiAI differentiates by focusing specifically on AI workload optimization rather than general-purpose quantum computing. Based in Bengaluru, the company is one of the few Indian startups operating in quantum-AI infrastructure, giving it a first-mover position in a domestic market where government investment in quantum research is accelerating through the National Quantum Mission. Scale AI: Scale AI is a data infrastructure company founded in 2016 that specializes in data labeling and annotation services for artificial intelligence model development. The company provides managed workforce solutions and software platforms that enable organizations to prepare high-quality training data at scale. Scale AI's core offerings include data labeling, model evaluation, data generation, and managed workforce services across computer vision, natural language processing, and other AI domains. The company serves enterprise customers across automotive, defense, technology, and other sectors requiring large-scale data annotation for machine learning applications. Notable use cases include autonomous vehicle development, where precise labeled data is critical for training perception systems. Scale AI operates a hybrid model combining software automation with human-in-the-loop annotation capabilities. With a Series F valuation of $13.8 billion and total funding of $1.6 billion, Scale AI represents one of the highest-valued data infrastructure companies in the AI stack. The company competes in the data labeling market alongside firms like Labelbox, Snorkel AI, and various in-house solutions deployed by large technology companies. Its growth trajectory reflects increasing enterprise demand for quality training data as AI model development accelerates. Scale AI's positioning emphasizes enterprise-grade reliability, security, and quality assurance in data preparation workflows. Scale AI has achieved unicorn valuation by solving the critical bottleneck of high-quality labeled data production at enterprise scale.

Scale AI got there first, launching in 2016 — that's 3 years of extra runway. QpiAI didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

QpiAI has about 10-50 employees; Scale AI has about 1,000. 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 QpiAI and Scale AI compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.