AI for the Physical World

Turn the chaos of the real world into opportunities.

Deployable on cameras, vehicles, and robots

Enhances coordination between physical agents and human workers

Our Products

VLM (Vision Language Models)

A multimodal AI model that understands images and text together—ideal for tasks like describing scenes, answering visual questions, or interpreting complex environments.

VLA

VLA (Vision-Language-Action Models )

An advanced model that not only sees and understands but also acts—translating vision and language into real-world robotic behavior. 

Our Unique Competition Strength

Base Models

Our proprietary Vision-Language Models (VLMs) and Vision-Language-Action (VLA) models are built on massive commercial and industrial datasets, giving us a unique edge in real-world performance. Need real numbers.

Customization

We offer multimodal fine-tuning services tailored to your specific use cases, ensuring precise and effective deployment. 

Acceleration

Our patented edge accelerator enhances runtime performance—boosting frequency, reducing latency, and delivering faster, smarter results where it matters most.

Use Cases

Warehouse

Automation

Challenge: Warehouses are fast-paced, ever-changing environments where traditional vision systems struggle to adapt to new layouts, lighting conditions, or packaging variations.

How VLM/VLA Helps:

VLMs process visual input in context with natural language instructions to accurately identify and locate items using multimodal cues.

VLAs translate that understanding into real-world actions—picking up items, navigating around obstacles, and placing them in designated areas with minimal manual oversight.

Construction

Site Monitoring & Collaboration

Challenge: Construction sites are dynamic and unpredictable. Rule-based vision and control systems often break down amid daily layout changes, weather variations, and diverse object appearances.

How VLM/VLA Helps:

VLMs interpret real-time site footage, understand progress, and identify structures or anomalies using both visual and textual data.

VLAs enable robots to navigate rough or changing terrain, assess worksite status, or assist human workers—adapting autonomously to evolving conditions.

construction site
Surveillance

Surveillance

Security Automation

Challenge: Traditional surveillance systems detect motion or specific objects but lack contextual awareness, limiting their ability to understand behavior or take intelligent action.

How VLM/VLA Helps:

VLMs go beyond object detection to understand complex scenes, unusual activities, and context-sensitive risks (e.g., loitering in restricted zones).

VLAs enable real-time, autonomous responses—like alerting personnel, activating lights, or deploying mobile security units to investigate.

Benefits Compared to Legacy Ones

VLM vs. Traditional Deep Learning Models

VLM vs. Traditional Deep Learning Models​

VLA vs. Control algorithms

Proudly backed by the NVIDIA Inception Program, and Google Al for Startups for our cutting-edge innovation in Al-powered robotics