Shipsy vs Glean

Glean has a disclosed valuation of $4.6B, while Shipsy's valuation is not publicly available, making a direct size comparison difficult. Glean employs 500 people.

Glean has raised more in total funding at $600M, compared to Shipsy's $25M — a gap of $575M. Combined, the two companies have completed 5 known funding rounds.

Glean holds the higher Awaira Score at 82/100, compared to Shipsy's 60/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 22-point gap that reflects meaningful differences in scale or traction.

Shipsy was founded by Soham Chokshi in 2016. Glean was founded by Arvind Jain in 2019. Visit each company's profile on Awaira for a full founder biography.

Shipsy: Shipsy is an AI-powered logistics and freight management platform that enables shippers, 3PLs, and freight forwarders to manage multi-modal shipment execution, carrier selection, rate benchmarking, and real-time tracking across road, rail, air, and ocean freight in a unified dashboard. The platform uses AI to optimize carrier allocation, predict delivery delays, and automate customs documentation for cross-border shipments.\n\nThe company raised approximately $25M in Series B funding from investors including Z47 and Sequoia India, and has built a customer base of large enterprises and logistics companies across India, the Middle East, and Southeast Asia managing significant daily freight volumes. Shipsy's rate engine provides real-time freight rate benchmarking that helps procurement teams validate carrier pricing against market rates.\n\nGlobal trade complexity and supply chain disruption have increased demand for intelligent freight management platforms that provide visibility and optimization across fragmented multi-carrier logistics networks. Shipsy's multi-modal coverage and AI-driven optimization position it as a comprehensive logistics intelligence tool for enterprises managing complex international and domestic freight operations. Glean: Glean is an enterprise AI search and discovery platform founded in 2019 that helps organizations extract actionable insights from internal data. The company operates in the enterprise AI category, providing AI-powered search capabilities across fragmented corporate information systems including documents, emails, chat messages, and databases. Glean's core technology uses machine learning to understand context and intent, enabling employees to find relevant information and answers across previously disconnected data sources. The platform serves large enterprises seeking to improve productivity and knowledge accessibility. Glean competes in the growing enterprise search and generative AI market alongside companies like Perplexity and traditional search providers adapting to AI. The company has raised $600 million across multiple funding rounds, reaching a valuation of $4.6 billion as of its Series E stage. This funding positions Glean among well-capitalized AI startups addressing enterprise information retrieval challenges. The company targets mid-to-large organizations where data silos and information discovery present operational inefficiencies. Glean's growth trajectory reflects broader enterprise adoption of AI-powered search solutions as organizations increasingly prioritize knowledge worker productivity and unified information access across their technology stacks. Glean specializes in enterprise-specific AI search that unifies fragmented internal data sources rather than external web indexing.

Shipsy was founded first in 2016, giving it 3 years of additional market experience. Glean 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.

Shipsy has approximately 100-500 employees, while Glean 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, Shipsy and Glean 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.