Embodied AI

Klerix Labs

The on-board intelligence platform for autonomous machines.

Seed Embodied AI $2M raised March 2026 klerixlabs.com
Overview

What Klerix Labs does.

Klerix Labs gives warehouse and factory robots an on-board AI brain: perception, reasoning, and safe control, trained in simulation and shipped as a ruggedized compute module that runs on the machine itself. A warehouse or factory arm can handle a shifted pallet, a new SKU or a change in lighting without an engineer reprogramming the cell.

Skills are trained in a digital twin, proven against safety evals, then run at the edge under an independent safety monitor that records a replayable trace of every motion. Pricing follows work completed rather than seats, so Klerix competes against a labour budget instead of a software budget, and every deployment produces labelled real-world interaction traces that train the next skill model.

At a glance
DetailValue
StageSeed
CategoryEmbodied AI
FundedMarch 2026
Raised$2M
Investor10xC
Websiteklerixlabs.com
Legal nameKlerix Labs Ltd.
Also known asKlerix
Registered officeLondon, United Kingdom
Team5
ProgramsNVIDIA Inception
CustomersBelmont Foods, Halberd Manufacturing, Sentry 3PL, Aurelio
ModelOutcome pricing per task completed, entered through a 60-day paid pilot on one work cell.
Measured byTasks completed per shift, unsafe-motion incidents, fleet uptime, cells expanded per customer.
99.97%
Production uptime
0
Unsafe-motion incidents, 11+ months
14 days
Cell scan to live skill, median
$2.4M
Annualized savings, Belmont Foods
An inspection station on a production line
The buyer Industrial operators in Europe and the Gulf, paying in hard currency
Products

Five products, one simulation-to-edge-to-fleet loop.

A work cell is captured in Mirror, the skill ships to Cortex with Aegis watching every motion, Anchor signs and secures it, and Helm supervises the fleet.

01

Cortex

The on-robot runtime for perception, planning, and sub-second control.

02

Aegis

An independent safety monitor that writes a replayable trace of every motion and decision, built for ISO 13849 and IEC 61508 evidence.

03

Mirror

Simulation and skill studio: work cells captured as digital twins, skills trained on synthetic data and validated against safety evals before any real motion.

04

Helm

Fleet analytics, drift detection, and teleoperation.

05

Anchor

Robot identity, signed skill bundles, and the secure edge-to-cloud link.

Why we invested

The thesis behind Klerix Labs.

The physical work that moves goods through a warehouse still runs on two bad options. Fixed automation is fast and rigid: a caged cell pinned to one part and one layout, where any change in SKU means weeks of re-integration. Manual labour is flexible and scarce, priced at $18 to $30 an hour with turnover above 60 percent. Neither option absorbs a floor that changes weekly.

Klerix sells the missing middle. The robot keeps its flexibility because the intelligence sits on the machine, and the operator keeps their audit trail because a separate safety monitor checks every motion before it executes. Pricing follows throughput rather than seats, so the customer pays for tasks completed instead of licences purchased.

This fits our test cleanly. The buyer is a European or Gulf industrial operator paying in hard currency, so the revenue does not depend on the local market. The build advantage is real: an engineering team fluent in the NVIDIA robotics stack, from Isaac Sim training through TensorRT optimisation to Jetson deployment, staffed at Pakistani cost against American and German competitors. The wedge is narrow enough to close, since the first sale is one work cell rather than a whole floor.

The evidence so far supports it. Deployed fleets hold 99.97% uptime with zero unsafe-motion incidents across 11+ months, a new cell goes from scan to live skill in 14 days, and reference deployments span food, manufacturing, 3PL and automotive floors.

Containers stacked at a logistics terminal
Five products One simulation to edge to fleet loop
Team

The people building it.

Two co-founders who met the same problem from opposite sides: the models were good enough, but nothing carried them safely onto a machine that moves.

Luis Selvera

Luis Selvera

Co-Founder & CEO

AI and ML engineer. Led enterprise forecasting and production LLM-agent systems (LangGraph, Azure AI, RAG) at CPS Energy, cutting forecast error by 27%. Sets product direction across the five-product stack and runs the pilot-first commercial motion.

  • Previously CPS Energy
  • Studied MS Computer Science, University of Texas at San Antonio
  • Profile LinkedIn
Varsha Lambi

Varsha Lambi

Co-Founder & CTO

ML and computer-vision engineer. Built real-time CNN detection and pose-estimation systems at Dori AI reaching 95% accuracy while running 90% faster. Owns the architecture across Cortex, the on-robot runtime, and Mirror, the simulation studio.

  • Previously Dori AI
  • Studied M.Eng, Rutgers University
  • Profile LinkedIn

Founding engineers

  • Shariq Ali Founding AI Engineer, Generative AI · MSc AI, University of Essex
  • Laiba Nisar AI Engineer, Agentic AI · BS Data Science, UMT
  • Sharon Reddy ML Systems Engineer · previously PNC, Accenture · MS CS, Kennesaw State

Open roles

  • Robotics Perception Engineer Engineering · Isaac ROS, Jetson
  • Field Deployment Engineer Applied · one week per quarter on a customer line
  • Sim & Synthetic Data Engineer Engineering · Isaac Sim, Omniverse
  • Controls & Safety Lead Operations · ISO 13849, IEC 61508

Roles are listed on klerixlabs.com/careers.

Field notes

From the Klerix blog.

Round

The 10xC seed.

10xC invested US$2M in March 2026 for 12.5% of Klerix Labs Ltd. at a $16M post-money valuation. Use of funds: embodied-AI R&D, field deployment and forward-deployed engineers, go-to-market, and functional-safety certification (ISO 13849, IEC 61508).

Company details are taken from Klerix Labs' own materials. Round terms are indicative until publicly announced.

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