Turnkey autonomy
Machine vision and lidar, predictive route planning, precise motion control in live warehouse and factory environments.
ENGINEERING AI
Artificial Intelligence for Robots and Autonomous Transport Systems
We build autonomy where it pays off fastest: in warehouses, factories and on the last mile. Robots see, plan, drive and work in swarms — we make sure this is reliable and safe around people.
- AMR / AGV
- ROS 2
- SOTIF
- V2X
- MLOps
- secure OTA
fleet-deploy.log
$ fleet deploy --site moscow-dc --zone A
→ map loaded: 12 400 m²
→ robots online: 24/24
→ OTA v2.7.1: signature verified
→ safety case: 148/148 scenarios
✓ swarm nominal — 0 collisions, 14 days
Capabilities
What we do
Six engineering capabilities that add up to an autonomous fleet: perception, planning, platforms, dispatching, integration with facility infrastructure, and safety.
Robotic platforms
Last-mile delivery robots, autonomous warehouse carts (AMR/AGV), transport modules for in-plant logistics.
Swarm dispatching
A single control center for a transport system of hundreds of robots — task assignment, flow optimization, real-time collision-free traffic.
V2X and smart building
We connect robots to the facility ecosystem — automatic gates, freight elevators, conveyors, WMS/WCS/ERP systems.
Safety and validation (SOTIF)
Digital twins and simulation, scenario testing, functional safety standards for collaborative operation with humans.
Secure AI lifecycle
Model fine-tuning on field data, dataset management, safe OTA updates of firmware and neural networks across the whole fleet.
Method
How we deploy autonomy
We start with a bounded zone where autonomy pays back in 6–12 months, and only then scale it across the site.
Site audit and economics
We study existing flows, measure manual operations and calculate what autonomy actually pays for on this site. The output is a pilot zone and an expected payback period.
Pilot in one zone
We validate the system in simulation on a digital twin, then on the real area. Perception, routing and human-shared traffic are tested against nominal and edge-case scenarios.
Scaling to the fleet
We roll out dispatching, integrate with WMS/WCS/ERP, and enable model versioning and safe OTA updates across the fleet — validated against SOTIF.
Engineering approach
We start with a bounded zone: a specific warehouse, production area or delivery route where autonomy pays off in 6–12 months. We validate the system in simulation on a digital twin and on a test range, then scale to the entire fleet — with strict model versioning, dataset management and secure OTA updates across the transport system.
We work within the engineering standards that apply to autonomous platforms operating around people: ISO 3691-4 (driverless industrial trucks), ISO 21448 / SOTIF (safety of the intended functionality), IEC 62443 (industrial cybersecurity) and ISO 22737 for low-speed autonomous systems. For the AI loop we manage risk per NIST AI RMF and track threats per the OWASP Top 10 for LLM Applications wherever language models are part of the loop.
Contact
Tell us where you want to deploy robots
A warehouse, a production area, a distribution center or last-mile delivery. Describe the site and the task — we will come back with a realistic assessment of a pilot.
Write to us
We reply within one business day. NDA on request.