Freehand Debuts As New Company with Dedicated AI Teams for Supply Chain Spend Management
The company emerges from stealth with Fortune 500 customers already live, replacing manual workflows across Accounts Payable, Procurement, and Supplier Collaboration. Powered by an award-winning team, Freehand provides speed, accuracy, and cost efficiency across the entire supply chain spend for enterprises.
SAN FRANCISCO (February 9, 2026) – Freehand, a newly formed agentic AI studio for supply chain and finance teams, today announced its official launch at Manifest 2026, with a mission to deploy autonomous AI Teams that take overthe operational work humans have been doing by hand across procure-to-pay.
Founded by Nitin Jayakrishnan and Abhijeet Manohar and headquartered in San Francisco, Freehand’s AI Teams read unstructured documents, emails, and internal chats, reason across contracts and policies, make decisions, and execute them – directly inside ERP, Procurement, and finance systems, and with suppliers and customers. The product is already live at Fortune 500 enterprises, where early deployments have cut reconciliation and AP cycle times by 80-90% and reduced manual procurement & sourcing efforts by 30-50%.
Freehand is built by the team behind Pi, the production-proven AI Agent for freight & logistics that earned recognition from TIME Magazine (Best Invention of 2025), Gartner(Visionary), Fast Company (Next Big Thing in Tech), and the World Economic Forum (Technology Pioneer). Pi proved that agentic AI could handle the messiest, most exception-heavy workflows in enterprise operations - not in a demo, but in production, at scale, for the world's largest shippers.
Freehand is Pi’s natural evolution: a platform that extends that same model across every category of supply chain spend. Every large enterprise runs its supply chain & source to pay the same way: thousands of people writing emails to suppliers, cross-checking invoices, chasing exceptions, and keying data between systems that don't talk to each other. It's slow. It's expensive. And it hasn't fundamentally changed in 30 years.
"The dirty secret of enterprise operations is that companies spend tens of millions just to keep the lights on — armies of people and outsourced teams doing tactical work like matching invoices, chasing exceptions, negotiating contracts,and reconciling POs," aid Nitin Jayakrishnan, co-founder and CEO."That's not strategic spend. That's margin erosion. Freehand saves you this time and this money. Our AI Teams handle the operational grind with full decision context and audit trails, so the savings flow straight to the P&L, so your people can focus on work that actually moves the business."
At the core of Freehand’splatform is a proprietary context graph, a living map that connects every decision, action, and exception across an enterprise's supply chain. It stitches together unstructured communication (emails, Slack messages, Teams chats, documents, invoices) with structured system data (ERP, procurement, payment systems, supplier records) to build a complete picture of how and why every operational decision was made. Because Freehand operates on the fulldecision context, not just clean data feeds, AI Agents can:
- Read unstructured inputs in whatever format they arrive, from rate confirmations to exception emails.
- Reason across the real operational picture: contract terms, policies, historical decisions, and live system data
- Execute directly in enterprise systems and partner portals, with full traceability and audit logs
- Improve continuously, because every decision enriches the graph and sharpens future accuracy
Most automation breaks atthe edges, the exceptions, the judgment calls, the tribal knowledge that lives in someone's inbox. Freehand's context graph captures exactly that, turning it from execution risk into institutional intelligence. The result: manual processes become autonomous, with better accuracy and full auditability.
Supply chains are facing a compounding problem: rising complexity, tighter margins, and a shrinking pool of experienced operations talent. The old playbook of hiring more people, outsourcing to BPOs, and buying another point solution doesn't scale anymore. Supply chain spend is the next largest domino. Freehand brings that same inevitability here, deploying AI Teams across the complex, exception-heavy operations where the real money is.
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About Freehand:
Freehand, formerly Pando, is an agentic AI platform for supply chain and spend management. Its autonomous AI Teams replace manual operations across procurement, supplier management and finance ops for complex categories like Logistics, Direct Materials and MRO — reading unstructured data, reasoning across contracts and policies, and executing decisions directly in enterprise systems. Built by the award-winning team behind Pi and headquartered in San Francisco, Freehand delivers measurable cost savings, autonomous execution, and fully auditable outcomes without adding headcount or BPOs. The company has been recognized by Gartner, by TIME Magazine as Best Invention of 2025, by Fast Company as the Next Big Thing in Tech 2025, by the World Economic Forum as a Technology Pioneer, and by Deloitte as one of the fastest-growing technology companies.
Founded by Nitin Jayakrishnan and Abhijeet Manohar and headquartered in San Francisco, Freehand’s AI Teams read unstructured documents, emails, and internal chats, reason across contracts and policies, make decisions, and execute them – directly inside ERP, Procurement, and finance systems, and with suppliers and customers. The product is already live at Fortune 500 enterprises, where early deployments have cut reconciliation and AP cycle times by 80-90% and reduced manual procurement & sourcing efforts by 30-50%.
Freehand is built by the team behind Pi, the production-proven AI Agent for freight & logistics that earned recognition from TIME Magazine (Best Invention of 2025), Gartner(Visionary), Fast Company (Next Big Thing in Tech), and the World Economic Forum (Technology Pioneer). Pi proved that agentic AI could handle the messiest, most exception-heavy workflows in enterprise operations - not in a demo, but in production, at scale, for the world's largest shippers.
Freehand is Pi’s natural evolution: a platform that extends that same model across every category of supply chain spend. Every large enterprise runs its supply chain & source to pay the same way: thousands of people writing emails to suppliers, cross-checking invoices, chasing exceptions, and keying data between systems that don't talk to each other. It's slow. It's expensive. And it hasn't fundamentally changed in 30 years.
"The dirty secret of enterprise operations is that companies spend tens of millions just to keep the lights on — armies of people and outsourced teams doing tactical work like matching invoices, chasing exceptions, negotiating contracts,and reconciling POs," aid Nitin Jayakrishnan, co-founder and CEO."That's not strategic spend. That's margin erosion. Freehand saves you this time and this money. Our AI Teams handle the operational grind with full decision context and audit trails, so the savings flow straight to the P&L, so your people can focus on work that actually moves the business."
At the core of Freehand’splatform is a proprietary context graph, a living map that connects every decision, action, and exception across an enterprise's supply chain. It stitches together unstructured communication (emails, Slack messages, Teams chats, documents, invoices) with structured system data (ERP, procurement, payment systems, supplier records) to build a complete picture of how and why every operational decision was made. Because Freehand operates on the fulldecision context, not just clean data feeds, AI Agents can:
- Read unstructured inputs in whatever format they arrive, from rate confirmations to exception emails.
- Reason across the real operational picture: contract terms, policies, historical decisions, and live system data
- Execute directly in enterprise systems and partner portals, with full traceability and audit logs
- Improve continuously, because every decision enriches the graph and sharpens future accuracy
Most automation breaks atthe edges, the exceptions, the judgment calls, the tribal knowledge that lives in someone's inbox. Freehand's context graph captures exactly that, turning it from execution risk into institutional intelligence. The result: manual processes become autonomous, with better accuracy and full auditability.
Supply chains are facing a compounding problem: rising complexity, tighter margins, and a shrinking pool of experienced operations talent. The old playbook of hiring more people, outsourcing to BPOs, and buying another point solution doesn't scale anymore. Supply chain spend is the next largest domino. Freehand brings that same inevitability here, deploying AI Teams across the complex, exception-heavy operations where the real money is.
--
About Freehand:
Freehand, formerly Pando, is an agentic AI platform for supply chain and spend management. Its autonomous AI Teams replace manual operations across procurement, supplier management and finance ops for complex categories like Logistics, Direct Materials and MRO — reading unstructured data, reasoning across contracts and policies, and executing decisions directly in enterprise systems. Built by the award-winning team behind Pi and headquartered in San Francisco, Freehand delivers measurable cost savings, autonomous execution, and fully auditable outcomes without adding headcount or BPOs. The company has been recognized by Gartner, by TIME Magazine as Best Invention of 2025, by Fast Company as the Next Big Thing in Tech 2025, by the World Economic Forum as a Technology Pioneer, and by Deloitte as one of the fastest-growing technology companies.