ABEJA vs FarEye

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. ABEJA employs 100-500 people, while FarEye has 500+ employees.

FarEye has raised more in total funding at $100M, compared to ABEJA's $50M — a gap of $50M.

FarEye holds the higher Awaira Score at 68/100, compared to ABEJA's 55/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 13-point gap that reflects meaningful differences in scale or traction.

ABEJA was founded by Shoichiro Aoyama in 2012. FarEye was founded by Kushal Nahata in 2013. Visit each company's profile on Awaira for a full founder biography.

ABEJA: ABEJA develops AI platform products for retail operations and manufacturing quality control, applying computer vision to analyse in-store customer behaviour and product performance in retail environments, and deploying visual inspection AI for defect detection in manufacturing production lines. The Tokyo company has built an enterprise software business serving Japanese retailers and manufacturers seeking to apply AI to operational problems without building internal AI engineering teams.\n\nThe company raised approximately $50 million in venture funding from investors including SBI Investment, SMBC Venture Capital, and KDDI Open Innovation Fund. ABEJA serves major Japanese retailers, convenience store chains, and manufacturing companies with AI analytics that derive insights from existing camera infrastructure in stores and factories. The company ABEJA Platform cloud product allows enterprise clients to build, deploy, and manage computer vision AI applications with managed infrastructure that reduces the AI operations burden.\n\nABEJA competes in the Japanese enterprise AI market alongside Retail AI (a Seven-Eleven Japan subsidiary) and international computer vision vendors. Japan large retail and manufacturing sectors, combined with limited English-language AI vendor support and preference for domestic supplier relationships in enterprise procurement, create a favourable environment for domestic AI platform companies with established enterprise relationships. The company participation in Japan government digital transformation initiatives has provided additional channels for deploying AI in public sector and infrastructure applications. FarEye: FarEye is an AI-powered intelligent delivery management platform that helps enterprises, 3PLs, and retailers optimize last-mile delivery operations through real-time visibility, dynamic route optimization, carrier management, and customer experience orchestration. The platform processes delivery data across owned fleets and third-party carriers to predict delivery windows, reduce failed deliveries, and minimize operational costs.\n\nThe company raised approximately $100M in Series E funding from investors including Fundamentum, Eight Roads Ventures, and Saif Partners, and serves major global retailers, logistics providers, and courier companies across North America, Europe, and Asia. FarEye's customer list includes DHL, Walmart, and other top-tier enterprises with large-scale delivery operations.\n\nLast-mile delivery is the most expensive and complex segment of the supply chain, accounting for over 50% of total logistics costs for e-commerce operations. FarEye's AI platform addresses this cost and complexity challenge at scale, and its enterprise customer penetration across geographies demonstrates the global applicability of its delivery intelligence capabilities.

ABEJA was founded first in 2012, giving it 1 year of additional market experience. FarEye was founded later in 2013. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

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

Yes, ABEJA and FarEye 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.