At Manifest 2026, one theme is impossible to ignore. The conversation across supply chain, procurement and finance has shifted from visibility and analytics towards autonomy and execution. Few companies embody that shift more directly than Freehand, whose co-founder Nitin Jayakrishnan is focused on redefining how enterprise work gets done…
Freehand builds AI agents for procure-to-pay processes across complex spend categories, working primarily with large global enterprises across manufacturing, distribution, retail and services. The company’s aim is not simply automation, but a fundamental redesign of how operational teams function, combining human teams with AI “employees” to reshape procurement, logistics and finance.
Speaking at Manifest, Freehand co-founder Nitin Jayakrishnan argues that many enterprises are still structured for a world that no longer exists. “And the response has been the same for 30 years,” he explains. “More people, more outsourced teams, more BPOs. That playbook doesn’t scale anymore.”
Which is where Freehand can help. A newly launched, agentic AI platform designed for supply chain and spend management, emerging from stealth in February 2026, Freehand replaces manual, BPO-heavy workflows. It acts as an AI-powered alternative to traditional Business Process Outsourcing (BPO) by automating complex, high-friction tasks like freight audit, payment processing, and procurement.
Living with permanent disruption
Supply chains are no longer temporarily volatile. Instability has become structural. “There used to be a time when enterprises thought of supply chain costs as unpredictable,” Jayakrishnan tells us. “It’s now been going on for so long… five, six years… almost every quarter you’ve had either a large global pandemic or a war or a trade war or a tariff or a compliance issue.”
Because of this, the largest organisations are no longer planning for predictability. They are planning for agility. They need to sense change continuously and react immediately. Yet many still struggle to do so. According to Jayakrishnan, the problem is not a lack of data, but the wrong kind of data.
Enterprise systems record transactions, but they do not capture context. They document what happened, not why decisions were made. “They capture the ‘what’, but they don’t capture how you got there,” he explains. “The ‘why’ of how decisions are taken is not captured in software. It’s captured in emails, in phone calls, in documents, in spreadsheets.”
Without this context, organisations cannot respond effectively to disruption. Even if they could see everything, acting quickly would still be difficult without autonomous decision-making. “You can’t depend on hundreds of thousands of teams and people to decide and act in real time,” he says. “That takes months, not minutes…”
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