1. Could you walk us through how Pi agents function in real-time, especially when dealing with unpredictable variables?
Pi agents operate autonomously across the end-to-end freight management cycle, from procurement through planning to payment, adapting in real time to unpredictable variables. Powered by Pando’s proprietary Logistics Language Model (LLM), Pi interprets contextual signals and executes decisions based on historical patterns and real time data.
For example, if a shipment is delayed due to port congestion, a Pi agent can rebook, renegotiate rates and reroute the shipment within seconds – no human intervention needed.
2. How does your LLM interpret multimodal logistics data, and how critical is domain-specific language understanding in driving better outcomes?
Supply chain data is sticky, multimodal and context-rich. Pando’s LLM is uniquely trained on millions of logistics-specific interactions, invoices, contracts and shipment navigating. It understands not just generic language, but the nuance of logistics terminology and workflow, whether its decoding terms, rate cards or customs paperwork. This is essential because without it, you end up with generic AI that can’t operate with the precision and accountability that enterprise logistics demands.
3. Many AI solutions struggle to scale. What makes Pi agents ready, and how have you ensured rapid time-to-value for such complex environments?
Pi agents are not experimental, they’re enterprise-grade agents built on a closed-loop architecture that continuously learn and improve from every transaction. What sets them apart from traditional siloed, rule-based systems is their modular design and native integration with major ERP, WMS and TMS systems. That means enterprises don’t need to rip and replace, they can deploy Pi agents in weeks, not years allowing human teams to focus on strategy and innovation. Within the first 90 days of deployment, customers have already seen rapid and measurable results including:
- 8-12% reduction in freight costs, driven by AI-led procurement and real-time optimization
- 18–21% improvement in customer service levels, via enhanced visibility and on-time performance
- 20–24% reduction in carbon emissions, by eliminating empty miles and optimizing modal choices
- 90% reduction in audit processing time and 80% faster discrepancy resolution
- $1.5M in annual savings for a single customer by automating invoice validation and freight booking
4. How does your AI infrastructure handle data privacy, compliance, and cross-border regulations especially in multinational supply chains?
We designed our AI infrastructure to be compliance-first. That means there are enterprise guardrails built to safeguard data flows within and across the extended ecosystem. There are also humans in the loop with access controls to ensure compliance checks and accuracy in decisions.
5. As disruption becomes the new normal, how can AI-powered logistics offer not just resilience, but strategic advantage for global enterprises?
AI enables enterprises to go from reactive to predictive. Pi agents don’t simply respond to disruption, they anticipate then mitigate it. This gives companies a strategic edge – faster customer deliveries, dynamic rate optimization and real-time supply chain visibility. When a competitor is still firefighting a disruption, a company powered by Pi agents has already rerouted, informed key stakeholders and protected margins. This gives not only resilience, but a competitive advantage to shippers.
6. We’re entering an era where AI agents may outpace traditional software in flexibility and ROI. How do you see this trend evolving over the next 3–5 years?
We strongly believe AI agents will become the main interface for managing logistics operations, replacing static dashboards, manual workflows and siloed software. Over the next 3-5 years, agents will be able to autonomously manage entire logistics functions across procurement, routing, invoicing and sustainability reporting. Companies wont be buying software modules, they’ll be subscribing to agents that deliver real outcomes. Flexibility and speed will become the new ROI for enterprise customers that embrace this shift, unlocking major advantages in supply chain and logistics performance.
- About Nitin Jayakrishnan
- About Pando
Nitin Jayakrishnan is the CEO and Co-founder of Pando, an AI-powered logistics technology company, helping Fortune 500 manufacturers and retailers worldwide manage their supply chains with AI. Nitin’s dedication to customer problem-solving and his ability to evolve and adapt quickly has allowed Pando to raise funds from marquee Silicon Valley investors including Iron Pillar, Uncorrelated Ventures, Nexus Venture Partners, Chiratae Ventures and Next47.
Prior to Pando, Nitin Jayakrishnan co-founded and served as the Chief Product Officer of iDelivery, a digital freight marketplace that offered transportation services to its clients. Nitin led the company to drive efficiencies in India’s $150 billion trucking market and played a key role in securing the ‘Internet of Things Prize’ at Yale for iDelivery’s innovative approach to modernizing logistics.
As a recognized thought leader, Nitin was named to the Forbes 30 Under 30 list, highlighting his achievements in the intersection of AI and logistics. Nitin holds degrees in Finance, Economics and Technology Management from NYU Stern School of Business, Singapore Management University and the University of Warwick.
Pando offers AI agents for logistics, enabling manufacturers, distributors, and retailers to automate their logistics operations to build agility, control freight spend, and reduce carbon footprint. Trusted by Fortune 500 enterprises with global customers across North America, Europe, and Asia Pacific regions, Pando is pioneering the future of autonomous logistics with cutting-edge AI capabilities.
In today’s complex supply chain landscape, logistics leaders are caught between rising costs, service demands, and operational complexities. Logistics teams are weighed down by hundreds of manual & cumbersome tactical decisions with very little time to focus on strategic priorities. They are always under pressure to ‘do more with less’ with the inability to drive operational agility given the unpredictability and disruptions across the global supply chain landscape.
Pando’s AI agents enable manufacturers, distributors, and retailers to replace manual, error-prone logistics tasks with intelligent automation to unlock unprecedented efficiency and cost savings by replacing the need for hiring additional staff or deploying more software. Pando redefines both logistics and talent strategies, accelerating the shift toward a world where Human Ingenuity and Artificial Intelligence work together to drive complex business processes. Pando’s AI agents act as extended team members, enabling logistics teams to delegate important yet repetitive decisions to these agents, who execute them with unmatched accuracy. Pando supercharges global logistics teams with its cutting-edge AI capabilities, enabling them to focus on strategic priorities and create a competitive edge.
Pando is recognized by Gartner for its transportation management capabilities, by the World Economic Forum (WEF) as a Technology Pioneer, by G2 as a Market Leader in Freight Management, and named one of the fastest-growing technology companies by Deloitte.
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