The modern “Demand Web” requires logistics to move with the agility of data, yet most fulfillment centers are stuck running on legacy workflows and partial fixes. The paradox is clear: warehouses have an existential need to boost productivity, but current automation leaders have largely ignored the 20,000+ constrained, existing brownfield facilities across the U.S.
Incumbent Automated Storage and Retrieval Systems (ASRS) solutions demand costly, disruptive greenfield rebuilds and infrastructure overhaul, making them inaccessible to existing facilities. Meanwhile, Autonomous Mobile Robots (AMRs) offer flexibility but are fundamentally throughput-limited, struggling to exceed ~100 picks per hour and failing to improve storage density.
Cartesian Kinetics breaks this cycle: Cartesian approaches automation as an intelligence problem, not a hardware problem. Its system augments existing racks and workflows, layering Physical AI (P-AI) that perceives the floor in real time, optimizes every movement, and drives predictable throughput without requiring operators to rebuild their warehouses.
The Real Problem: Warehouses are Dynamic, Not Static
Traditional automation assumes a stable, predictable environment, but real warehouses are dynamic. SKU profiles change, inventory shifts, demand fluctuates, bottlenecks form, machines slow down, and workflows are reconfigured as business needs evolve. Legacy systems struggle because their workflows are rigid and updating them takes months.
P-AI is the core enabler. It doesn’t just execute tasks; it reads the environment, weighs constraints, and autonomously selects optimal actions as conditions evolve.
Cartesian’s stack mirrors the architecture of modern embodied AI agents:
- Perception through sensors and positional awareness
- Cognition through task allocation, orchestration, optimization, and digital twins
- Actuation through robotic systems that adjust to real-world variability.
This is what allows the system to continuously improve and respond, rather than wait for human reprogramming.
The Wedge: A Retrofit System That Actually Aligns With How Warehouses Operate
The primary advantage of Cartesian Kinetics is that the hardware serves only as the entry point, while the software stack transforms Carte+ into a P-AI native system. P-AI systems integrate cognitive intelligence with physical actions, allowing them to flexibly and safely respond to diverse and unpredictable real-world environments. This intelligence-centric approach is what makes retrofit viable at scale, because the system adapts to the warehouse rather than forcing the warehouse to adapt to it.
Carte+ was engineered for brownfield reality. It is an Omni Rack Robotics system that is fully retrofit-native, attaching directly onto existing racks without any need to rip or replace infrastructure. It can be installed aisle by aisle, with full deployment completed in just 8 to 12 weeks. The full-stack architecture (CarteCloud, CarteEdge, CartePLC) then drives the outcomes, using orchestration algorithms and advanced path planning to deliver a 3 to 5x throughput lift, achieve 300+ picks per hour, cut labor costs by half, and generate payback in a little over two years.
Digital Twin (eCarte+)
At the core of the P-AI architecture is the Digital twin (eCarte+) a high-fidelity, physics-based simulation built using Emulate3D that models the entire warehouse before a single robot is deployed. It learns SKU flows, tests routing and operational scenarios, and generates precise hardware and software configurations directly from a customer’s order patterns. By running real order profiles in a human-in-the-loop environment, eCarte+ lets operators evaluate productivity, throughput, and turnaround times upfront, effectively validating ROI before deployment. This “virtual commissioning” sharply reduces engineering cycles, lowers integration risk, and allows customers to plan placements, labor, and throughput with confidence long before installation begins.
The Orchestration Layer
The Carte+ system’s multilayered architecture functions as the “warehouse brain”, coordinating the entire fulfillment process through a modular stack built to support customers at any stage of automation maturity. Its core algorithms, including orchestration and path planning, synchronize racks, robots, conveyors, and human operators as one adaptive system, optimizing SKU placement, minimizing travel distance, and increasing tote presentation rates. The orchestration layer spans WMS for planning, WES for real-time execution, and WCS for hardware control, unifying every subsystem into a single high-throughput, continuously adaptive engine.
The X-Y-Z Framework: How Cartesian Turns P-AI Into a Strategic Moat
Fun fact: the name Cartesian Kinetics comes from Cartesian (coordinate systems) and Kinetics (the study of motion). Fittingly, the team’s P-AI strategy is built along 3 orthogonal vectors, a simple X-Y-Z framework that mirrors the way their system perceives and controls physical space.
X-Axis: Expanding Footprint (From Robotics to Orchestration)
The X-axis represents how the system grows inside a warehouse, moving from powering a single workflow to orchestrating nearly every task on the floor.
By decoupling from hardware and evolving into a Warehouse OS, Cartesian can go from touching <10% of workflows to influencing 90%+ of all movement: picking, putaway, replenishment, batching, routing, charging, and dispatch.
This expansion is powered by Learning Orchestration (CarteCloud), AI models that constantly rebalance work across racks, robots, conveyors, and people. This creates:
- deeper penetration within each facility
- stickiness as the AI learns the nuances of that warehouse
- natural expansion from “robot system” to “warehouse intelligence layer”
Y-Axis: Performance Uplift (Real-Time Optimization at Scale)
The Y-axis measures how well the system performs once deployed.
Through its edge and cloud stack (CarteEdge + CarteCloud), Cartesian makes sub-second micro-decisions across destination allocation, pathing, dynamic charging, and SKU mix optimization.Warehouses behave like living systems, shifting constantly, and real-time inference is what keeps throughput stable. In industrial settings, this approach has consistently reduced downtime and improved cycle times. Cartesian brings that same level of precision to the warehouse floor.
Z-Axis: Operational Certainty (Reliability as a Moat)
The toughest part of automation is not deployment. It is keeping a robotic fleet running consistently, day after day, with minimal downtime.
Cartesian focuses heavily on this layer. The system uses AI-powered predictive maintenance and edge-based fault prediction to identify issues early and prevent disruptions. This is what turns automation from useful to mission-critical. At this point, customers stop viewing Cartesian as a robotics vendor and start depending on them as part of their core operations.
Why This Team?
What stood out to us at Cartesian Kinetics is how naturally the team fits the problem. Each leader has spent years in robotics, supply chain, or enterprise automation, not just studying the challenges but grappling with them first-hand. That depth of experience, paired with the clarity of lessons learned, is what gives us conviction in their ability to build a category-defining company.
Jayendran Balasubramanian leads Cartesian. An IIT Bombay graduate who later completed his MS at Stanford with a focus on Mechatronics. He brings a rare blend of academic depth and hands-on robotics experience. He previously built automation at Nextfirst and experimented with last-mile delivery at Taykit. What stands out is his clarity, speed of thought, and ability to move seamlessly from system-level engineering detail to high-level strategic decision making.
Veena Radhakrishna, brings years across Intel, IBM, and Nextfirst, translating complex robotics workflows into scalable, production-grade software.
Sarjoun Skaff has deployed robots across 600 Walmart stores and raised over $100 Mn at Bossa Nova, giving him a front-row view into what scaling robotics really takes. Initially introduced to Cartesian as an evaluator, he chose to join full-time, a strong signal of his conviction in both the opportunity and the leadership.
Rounding out the team, Kimberly Barr brings nearly two decades of enterprise automation sales and partnerships, navigating the exact multi-stakeholder environments Cartesian is selling into.
Our Bet
At Kae, our conviction stems from:
- The Product Wedge: What stood out to us was how Cartesian approached deployment and control from first principles. The product is designed to work with operational reality rather than ideal conditions, delivering meaningful performance gains without forcing customers into disruptive change. That ability to drive outcomes while fitting seamlessly into existing workflows gives the solution a clear adoption advantage and a credible path to becoming deeply embedded in day to day operations.
- An Underserved Market at an Inflection Point: We see Cartesian operating at the edge of a large market undergoing transformation. Brownfield warehouses, long ignored by traditional automation, represent an underpenetrated opportunity where technological and operational pressures are converging. Cartesian’s retrofit-native model does not just compete within the market, it expands it by making automation viable for thousands of facilities previously locked out.
- The Team: The team brings rare operating muscle memory from deploying robotics at scale, building enterprise-grade systems, and navigating complex warehouse environments.They know what breaks, what scales, and what customers trust, and they are building Cartesian Kinetics with those lessons baked in
Warehouse automation is entering a new phase. As operational complexity rises and labor, space, and throughput constraints tighten, the next wave of winners will be systems that adapt to reality rather than impose rigidity. Cartesian Kinetics sits at that inflection point, unlocking a vast, underserved segment of the market through an intelligence-led, retrofit-first approach. We are excited to partner with the team as they build the core automation layer that helps warehouses evolve, not break, under pressure.
