With $85M funding, Augment develops ChatGPT-like AI trained on logistics workflows – Tech Funding News
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San Francisco-based AI startup Augment has raised $85 million in Series A funding, bringing its total capital raised to $110 million in just five months.
The round was led by Redpoint Ventures, with participation from 8VC, Shopify Ventures, Autotech Ventures, and several other investors in logistics and artificial intelligence.
Augment plans to use the funding to enhance Augie’s capabilities, its primary AI teammate for logistics, strengthen integrations with freight systems, and expand its team to serve shippers, brokers, and fleets better.
Currently, Augie supports over $35 billion in freight under management (FUM) across dozens of leading shippers and brokerages, transforming how logistics teams operate from order to cash.
Harish Abbott, who led Augment, has developed Augie, an AI platform (a remote virtual teammate) designed to assist logistics teams by automating tasks across the order-to-cash cycle.
“The logistics industry moves trillions of dollars of goods across supply chains every year, yet much of it still runs on emails, phone calls, and fragmented systems. Operators are buried under manual tasks, margins are razor-thin, and the pressure to do more with less is relentless,” says Abbott.
Unlike traditional voice bots or single-function automation tools, Augie is positioned as an AI teammate that understands the end-to-end context of freight operations.
It can interact across systems and communication channels, handling processes such as quoting, billing, tendering, delivery, and collections.
“Yes, Augie can email, call, message, and even send a Telegram if it has to. But honestly, it would rather not. To Augie, every email or call is a defect. Its real goal? Quietly getting the job done, so operators don’t have to think about it at all,” Abbott explains.
The company is developing Augie to automate various aspects of the freight industry. They are focusing on:
Augment is also developing a knowledge base that combines structured and unstructured data, enabling it to adapt to specific operations and provide real-time answers to logistics-related questions.
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