FarEye vs Galatek

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. FarEye employs 500+ people, while Galatek has 1-50 employees.

FarEye has raised $100M in disclosed funding across 0 known rounds. Galatek's funding history is not publicly available.

FarEye holds the higher Awaira Score at 68/100, compared to Galatek's 30/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 38-point gap that reflects meaningful differences in scale or traction.

FarEye was founded by Kushal Nahata in 2013. Galatek was founded by Wei Huang in 2019. Visit each company's profile on Awaira for a full founder biography.

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. Galatek: Galatek develops AI customer engagement and personalisation tools for enterprise clients in retail, financial services, and telecommunications, applying machine learning to customer behavioural data to generate personalised content, product recommendations, and communication timing optimisation across digital customer touchpoints. The Singapore company targets enterprises in Southeast Asia seeking to improve customer retention and revenue per user through AI-driven personalisation at scale.\n\nThe company is early stage with seed-level funding from Singapore and regional venture investors. Galatek builds on the availability of rich digital behavioural data from Southeast Asian consumer platforms to train personalisation models that improve engagement metrics across email, app push notification, and in-product recommendation surfaces.\n\nGalatek operates in the customer engagement AI market alongside Braze, Klaviyo, and regional personalisation platforms. Southeast Asia digital consumer market, characterised by high mobile penetration, young demographics, and rapidly growing e-commerce adoption, creates favourable conditions for AI personalisation tools that can increase conversion and retention in competitive consumer-facing industries. The company early stage reflects the broader opportunity in bringing enterprise AI personalisation capabilities to Southeast Asian businesses that have not yet adopted the ML-driven engagement optimisation tools that have become standard at large Western technology companies.

FarEye was founded first in 2013, giving it 6 years of additional market experience. Galatek was founded later in 2019. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

FarEye has approximately 500+ employees, while Galatek has approximately 1-50. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, FarEye and Galatek 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.