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AI Startup Freehand Raises $75 Million Led by Battery Ventures, NewRoad, Nexus
The startup says early customers recovered 5% to 10% of spend and completed workflows five to seven times faster.
- San Francisco-based startup Freehand announced today that it raised $75 million in seed funding to automate accounts payable processes for large enterprises using artificial intelligence agents.
- Enterprises traditionally rely on large teams to manually process invoices, leaving them vulnerable to fraud and overspending. Nitin Jayakrishnan, Freehand's co-founder and CEO, explains these decisions require understanding the "rich context" of supplier contracts and communications.
- Deployments at Meta and Unilever have seen workflows speed up by seven times, with agents handling 99% of decisions and reducing spending by as much as 10% through fraud detection and negotiations, according to the company.
- Battery Ventures and NewRoad Capital Partners co-led the funding round, with participation from Nexus Venture Partners and PSP Growth, the fund led by former US Commerce Secretary Penny Pritzker, positioning Freehand in a competitive agentic market alongside Pivot.
- Freehand utilizes a "Category Context Graph" to integrate unstructured email data with structured ERP system information. As tariff pressures strain traditional supply-chain outsourcing, the company plans to expand automation beyond invoice processing into broader supply-chain infrastructure.
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Freehand raises $75M to put AI agents in charge of supply-chain spend
The startup, whose agents negotiate and pay across procurement for the likes of Unilever and Pfizer, is betting enterprises want software that acts, not software that suggests. Freehand, a startup whose AI agents take over the grunt work of managing what large companies spend on their supply chains, has raised $75 million. The round is […] This story continues at The Next Web
·Amsterdam, Netherlands (Kingdom of the)
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Total News Sources11
Leaning Left2Leaning Right4Center4Last UpdatedBias Distribution40% Center, 40% Right
Bias Distribution
- 40% of the sources are Center, 40% of the sources lean Right
40% Right
L 20%
C 40%
R 40%
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