Autonomous Fleet Intelligence

Precision Fleet Operations
for Autonomous Robots

Powered by Fleet OS

The AI operating layer that lets anyone deploy, orchestrate, and manage heterogeneous robot fleets using natural language. Full stack — on-robot SLAM to cloud orchestration.

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Minutes
Mission creation vs. months
Any Robot
Single platform
Zero
Expertise required to operate
Full Stack
No vendor lock-in

The Gap

The Robot Fleet Gap

CURRENT STATE
Fragmented & Manual
Each robot brand requires a separate, incompatible platform
Months of engineering time to deploy a new robot type
Specialist robotics engineers required for every operation
Vendor lock-in — switching costs are prohibitive
No unified visibility across mixed robot fleets
FLEET OS
Unified & AI-Driven
One platform to orchestrate any robot from any manufacturer
Deploy a new mission in minutes using natural language
Anyone can operate a robot fleet — no coding required
Open architecture — swap robots without re-engineering
Live 3D digital twin with unified fleet dashboard

Our Approach

Three-Layer Fleet Stack

01

AI Mission Creation

Describe a mission in plain language and Fleet OS generates, validates, and dispatches robot tasks automatically. No programming. No robotics expertise. Anyone on your team can deploy a fleet.

Natural language commands Zero robotics expertise Minutes to deploy AI-native design
02

Fleet Orchestration

Heterogeneous robot management across manufacturers and form factors. Modular controller architecture validated across multiple OEMs. Real-time coordination, task scheduling, and fault recovery.

Multi-robot coordination Heterogeneous architecture Real-time scheduling Modular controllers
03

3D Digital Twin

Self-building spatial maps powered by on-robot SLAM. Live environment reconstruction for situational awareness, mission replay, and continuous learning. Cloud-synced for remote operations.

On-robot SLAM Self-building digital twins Cloud-synced state Continuous learning

Engineering Foundation

Engineering Foundation

T-01
AI + Orchestration
LLM-driven mission planning and natural language robot control. Autonomous task generation, validation, and dispatch. Continuous learning from fleet data across all deployments.
T-02
Fleet Operations
Multi-robot orchestration layer validated across 3+ independent robotics manufacturers. Modular controller architecture enables any robot to be onboarded without platform re-engineering.
T-03
On-Robot Autonomy
Proprietary SLAM stack for GPS-denied environments. Real-time localization and mapping without infrastructure dependencies. Proven in underground mining — one of the most demanding environments on earth.
T-04
Simulator
High-fidelity simulation environment for mission rehearsal, edge-case testing, and operator training. Self-building digital twins feed simulation automatically from real-world robot data.
Self-building digital twins
Heterogeneous architecture
AI-native design
Data flywheel

Strategic Alliance

Strategic Partners

Fortune Global 500 Strategic Partner
Global
Fortune Global 500 — leading mining services company with worldwide reach
3+
Robot OEM partners — validated across independent manufacturers
Live
Beachhead deployment in underground mining — highest-demand proving ground
Partnership Highlights
Multi-year technology partnership with Fortune Global 500 strategic partner
Fleet OS software embedded into partner product line
Validated across 3+ robot OEM manufacturers — hardware-agnostic proven
Underground mining beachhead — expanding to surface, logistics, construction
Asia-Pacific, Americas, and EMEA pipeline via partner network
Robot OEM Partners
OEM Partner 1 — Ground Robot
OEM Partner 2 — Aerial Platform
OEM Partner 3 — Industrial UGV

Engineering Leadership

Engineering Leadership

Founder & Chief Executive Officer
Dr. Chanoh Park
Education PhD Robotics, CSIRO (Australia)
Recognition DARPA SubT Challenge — 2nd place worldwide. IEEE Transactions on Robotics, published.
Expertise 13+ years in SLAM and spatial AI. Korea's #1 SLAM expert.
Industry Built BlastVision at GroundProbe — 6-country commercial launch. EasyRobotics — Hyundai & Kia factory deployments.
Network Rio Tinto · Orica · BHP
PhD CSIRO DARPA SubT 2nd IEEE TRO SLAM 13yr+
Chief Technology Officer
Samuel Lee
Education MS Computer Science, Georgia Tech (USA). BS, Sabancı University (Turkey).
Role Fleet OS architect. Full-stack systems engineer.
Expertise Heterogeneous robot platform designer. Built fleet management systems deployed across multiple OEM hardware stacks.
Industry Floatic · Motion2AI
Research TU Delft research collaboration
MS Georgia Tech Fleet OS Arch. TU Delft Full-Stack
Advisors
AI Researcher — Major semiconductor & national research institution
Robotics Veteran — Leading heavy industries conglomerate
Get Started

Start with Fleet OS

Talk to our engineering team. We'll assess your use case and show you how Fleet OS can deploy, orchestrate, and manage your robot fleet — in minutes, not months.

Contact Us
samuel.lee@rovifylab.com