Freehand Raises $75M Series B for AI Supply Chain Automation

Enterprise AI startup Freehand has raised $75 million（約120億円） in Series B funding, with Battery Ventures and NewRoad Capital Partners co-leading the round and Nexus Venture Partners and former U.S. Commerce Secretary Penny Pritzker participating. The San Francisco-based company, which has now raised $100 million（約160億円） total, declined to reveal its valuation but CEO and co-founder Nitin Jayakrishnan described it as "a significant step up" from the company's March 2024 Series A of $25 million（約40億円）.

Freehand was founded in February 2024 by Jayakrishnan and Abhijeet Manohar, two enterprise logistics veterans who previously co-founded Pando, a SaaS transportation management system and procure-to-pay system of record for large enterprise logistics. In early 2024, as AI transformation accelerated, the two stepped away from operational roles at Pando to launch Freehand as an independent entity focused entirely on agentic AI. Pando continued under a newly appointed executive team before being sold to a strategic buyer in early 2026, marking a complete shareholder exit for the founders. Their experience building enterprise supply chain software convinced them that existing back-office paradigms were ready for disruption. "We had been in this fairly archaic dinosaur of an industry for the last six to eight years," Jayakrishnan told Crunchbase News. "Instead of trying to catch them up to a technology paradigm that was sunsetting, we thought we could leapfrog them into a technology paradigm that was just rising."

Unlike spend management platforms such as Ramp, which focus on corporate cards, employee travel expenses, and bill payments, Freehand targets complex supply chain operations. Its AI agents manage non-standard spending across logistics, raw materials, parts, and labor by reading contracts, policies, emails, and internal data to verify bills, track operational milestones, and handle vendor negotiations—all operating inside existing company systems. For large, global businesses, the challenge is significant: keeping track of supplier bills across complex shipping routes like the Red Sea and the Strait of Hormuz, with detailed contracts and large invoices that historically required substantial back-office teams to verify. "When eventually rubber hits the road, when you get an invoice from a supplier saying, 'Hey, you owe me $16.948 million（約27億円） for everything that I've done for you in the last six months,' there aren't a lot of proof points to figure out whether you know if that number is right or wrong," Jayakrishnan explained. When billing discrepancies arise, Freehand's AI agents negotiate adjustments directly with suppliers while maintaining relationships: "Taking those business calls, which have historically been done through tribal knowledge… and truly automating the process to the point of no human intervention is effectively what Freehand does."

Freehand counts some 50 customers, including Meta, Johnson & Johnson, Pfizer, and Cardinal Health. Its platform autonomously processes billions in payments across 60 to 70 countries and hundreds of currencies without human supervision. Benefits documented by the company include recovering 5% to 10% of total spend across a number of categories, completing complex operational workflows 5x to 7x faster, and reducing overall procure-to-pay cycle times by more than 70%. "We are, for a lot of companies, their first global rollout of AI deployments at scale that impacts daily transactions and daily operations at global scale," Jayakrishnan said. The timing of this funding round comes as tariffs, taxes, and immigration policy strain the outsourcing model that has run supply chains for decades. Supply chain and logistics startups are experiencing a fundraising surge, with 2026 on pace to deliver the strongest year since 2022, raising $6.2 billion（約9900億円） in the first half of this year across 350 deals. Dharmesh Thakker, general partner at Battery Ventures, noted that while supply chain and logistics management is massive, it "still runs on manual labor and repetitive workflows that are begging to be automated." He pointed out that technology spending in the sector is just over $20 billion（約3.2兆円）, "which tells us AI has enormous room to drive efficiency, starting with the most mission-critical but repetitive workflows like freight audits and payments." Thakker said his firm found Freehand to stand out on founder market-fit, focus on the largest Fortune 500 shippers rather than intermediaries, and clear, measurable business outcomes.

Freehand's $75 million（約120億円） Series B arrives at a pivotal moment for enterprise supply chains. The startup's founders, Nitin Jayakrishnan and Abhijeet Manohar, spent six to eight years building Pando, a SaaS transportation management and procure-to-pay system for large enterprise logistics, before selling it to a strategic buyer in early 2026. That experience convinced them that traditional back-office paradigms were ripe for disruption—specifically that instead of forcing aging supply chain operators to catch up with sunsetting technologies, they could help them leap directly into agentic AI. Their timing aligns with macroeconomic shifts: tariffs, geopolitical tensions, and disrupted trade routes are straining the decades-old outsourcing model that previously ran global supply chains, making the case for internal automation stronger.

The investment also reflects broader momentum in the supply chain technology sector. Supply chain and logistics startups are on pace for their strongest fundraising year since 2022, with $6.2 billion（約9900億円） raised in the first half of 2026 alone across 350 deals. Yet despite the sector's scale—supply chain and logistics is described as massive—technology spending there is just over $20 billion（約3.2兆円）, a rounding error relative to the potential for AI-driven efficiency. Battery Ventures partner Dharmesh Thakker noted that Freehand stands out for founder market-fit, focus on Fortune 500 shippers rather than intermediaries, and measurable business outcomes—a critical distinction in an AI funding landscape often dominated by founders with limited industry expertise.

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