A cross-disciplinary team for AI, robotics, communications, hardware, and product.
The company story is strongest when it shows the mix required to build reliable embodied systems: perception, control, edge computing, networks, and deployment strategy.
Dr. Zelin Li
Founder / AI & Vision
Leads OpenClaw agent integration, VLA/VLM workflows, visual perception, and skill planning.
City University of Hong Kong
Zhuoheng Ran
FPGA / Edge Engineer
Builds acceleration and edge-computing foundations for robot-side deployments.
City University of Hong Kong
Dr. Hao Guo
Hardware Architect
Connects chip design, sensors, control boards, and embedded hardware decisions.
City University of Hong Kong
Ms. Yajun Wang
Product & Finance
Shapes product strategy, deployment priorities, finance, and partnership motion.
CMHK / Product Strategy
Dr. Xinran Zhao
Communication Architect
Designs low-latency networking, ad-hoc communication, and robot connectivity.
City University of Hong Kong
Prof. Huiming Chen
Scientific Advisor
Guides cloud-edge collaboration, reliability thinking, and research direction.
USTB
Dr. Chenwei Wang
AI Scientist
Supports computer vision, fuzzy perception, imaging algorithms, and embodied AI research.
Hong Kong Polytechnic University
Academic and ecosystem background
Hong Kong Polytechnic UniversityUSTBA product portal backed by developer infrastructure.
ISACAI brings the company website, API portal, skill schema, rosbridge integration patterns, demo workflows, and bilingual product documentation into one connected platform surface.
Internal API Portal
A companion API website for internal development, robot-agent integration, skill interfaces, and team-side documentation.
http://isacai.space
Company product website
Public narrative layer
Explains ISACAI, VLAClaw, product positioning, safety philosophy, roadmap, team, and cooperation paths.
Developer API website
Internal platform layer
Supports internal developers with API-oriented documentation and a clearer path from robot capability to agent integration.
Skill schema and examples
Execution contract
Defines how action groups, motion commands, sensor reads, and interaction behaviors become validated robot skills.
rosbridge integration design
Robot connectivity layer
Documents WebSocket JSON patterns for ROS2 topic subscription, command publishing, and future service calls.
Demo workflow library
Deployment workflow
Frames voice greeting, visual interaction, safe patrol, and developer integration as repeatable demo workflows.
Bilingual product materials
Product communication layer
Makes the platform understandable to labs, robot teams, education customers, OEM partners, and Hong Kong / mainland collaborators.
Reliability-first roadmap from voice MVP to multi-robot orchestration.
The roadmap is intentionally staged: build safe single-robot skills first, then add perception, recovery, navigation, and multi-embodiment orchestration.
Voice Command MVP
Skill Registry and Developer API
Multimodal Perception
Workflow Automation
Multi-Robot and Multi-Embodiment
Engineering notes that make the platform feel reproducible.
The company portal carries product documentation, engineering notes, demo logs, and research observations, with space for future articles, cases, and release updates.
How rosbridge makes ROS2 robots accessible to AI agents
A practical guide to WebSocket JSON, topic subscription, and service calls.
Turning sit_wave.d6a into an OpenClaw skill
How authored action groups become semantic, validated robot capabilities.
Why VLA robots need skill-level control instead of direct joint prediction
A reliability-first argument for bounded robot skill orchestration.
Platform questions, answered.
Key answers about VLAClaw, ROS2 integration, Skill Server boundaries, developer access, and deployment workflows.
Is VLAClaw a robot controller?
VLAClaw is an intelligent upper-computer and skill orchestration layer. Robot-side ROS2 nodes remain responsible for real-time motion and hardware control.
Does the AI directly output motor commands?
The model outputs skill choices and bounded parameters. Skill Server validates the command before ROS2 executes the underlying action.
Do developers need to install ROS2 on the host?
Not for the primary integration path. The host can connect through rosbridge WebSocket and JSON messages while the robot runs ROS2.
What can be evaluated first?
Teams can review the architecture, Skill API, rosbridge examples, action-group mapping, developer workflows, and demo runbooks, then connect the same contracts to robot-side ROS2 systems.
Which robots are easiest to support?
ROS2-enabled quadruped robots are the first target. Any robot with stable command interfaces, sensor topics, and emergency stop behavior is a candidate for integration.