Arrowhead AI vs Faculty AI

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Arrowhead AI employs 10-50 people, while Faculty AI has 100-500 employees.

Faculty AI has raised $42M in disclosed funding across 0 known rounds. Arrowhead AI's funding history is not publicly available.

Faculty AI holds the higher Awaira Score at 60/100, compared to Arrowhead AI's 35/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 25-point gap that reflects meaningful differences in scale or traction.

Arrowhead AI was founded by Suraj Sharma in 2020. Faculty AI was founded by Marc Warner in 2014. Visit each company's profile on Awaira for a full founder biography.

Arrowhead AI: Arrowhead AI is an early-stage industrial AI solutions company building machine learning applications for manufacturing and process industries, focusing on quality control automation, predictive maintenance, and production optimization use cases that reduce defect rates and unplanned downtime in industrial facilities. The company targets Indian manufacturing companies undergoing digital transformation who need practical AI applications rather than research-grade solutions.\n\nThe company is in Seed stage with limited disclosed funding and is in the process of building initial customer deployments and validating its AI models in real manufacturing environments. Arrowhead AI operates in the industrial AI category that has seen growing enterprise interest as manufacturers seek to use production data they have historically collected but not fully utilized.\n\nIndia's manufacturing sector is a significant AI adoption opportunity, with millions of production workers and substantial installed equipment base that generates rich operational data. Arrowhead AI is building at the intersection of industrial domain expertise and modern AI capabilities, targeting a market where the combination of local presence, domain knowledge, and technical capability is essential for successful deployment. Faculty AI: Faculty AI provides applied AI consulting, products, and platform services to government agencies and enterprise clients across the United Kingdom and beyond. The company builds custom machine learning models, deploys AI decision-support tools, and offers its Frontier data science platform for teams that need to build, deploy, and monitor models at scale.\n\nFaculty has raised approximately $42 million in venture funding and counts the UK National Health Service, the Cabinet Office, and major private sector firms among its clients. The company gained significant visibility for its work supporting the UK government COVID-19 response, supplying data analytics and epidemiological modelling capabilities. It maintains a team of AI researchers and engineers drawn from academic institutions including Oxford and Cambridge.\n\nThe company occupies a distinctive position in the UK AI services market, combining a commercial consulting practice with proprietary software products. Faculty competes with large consultancies such as McKinsey and Accenture as well as boutique AI firms for government and enterprise contracts. Its proximity to policymakers and its record of sensitive public-sector engagements give it a reputational edge in regulated-industry deployments where trust and UK data sovereignty are primary buying criteria.

Faculty AI was founded first in 2014, giving it 6 years of additional market experience. Arrowhead AI was founded later in 2020. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Arrowhead AI has approximately 10-50 employees, while Faculty AI has approximately 100-500. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Arrowhead AI and Faculty AI are direct competitors — both operate in the Enterprise AI space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.