ZTE Co-Sight AI Agent Studio is a high-performance AI agent development and orchestration platform designed to solve the bottlenecks of high customization and long implementation cycles in industrial AI.
Introduction
The industrial world is moving beyond simple AI chatbots to autonomous agents that can think, plan, and act. ZTE Co-Sight AI Agent Studio is the engine driving this transition, providing a professional-grade workspace where enterprises can “manufacture” intelligent agents tailored to their specific operational needs. By leveraging ZTE’s deep expertise in computing-network co-design, Co-Sight eliminates the technical barriers of agent development through a modular, drag-and-drop factory model. Whether it’s an agent managing a 5G-Advanced network, an AI assistant for minute-level medical diagnostic reports, or an autonomous system optimizing urban rail transit, Co-Sight provides the infrastructure for a secure, reliable, and self-evolving AI workforce.
GAIA Benchmark Leader
DAG Parallel Processing
Visual Assembly Factory
Open A2A-T Protocol
Review
ZTE Co-Sight AI Agent Studio is a high-performance AI agent development and orchestration platform designed to solve the bottlenecks of high customization and long implementation cycles in industrial AI. Unveiled as a central pillar of ZTE’s “All in AI” strategy at MWC Barcelona 2026, Co-Sight has consistently ranked first in authoritative evaluations like GAIA (General AI Assistants) and HLE. It operates as an “AI Agent Factory,” utilizing a modular, low-code architecture that allows enterprises to assemble specialized agents for complex industrial tasks in minutes rather than months.
The platform stands out for its “AI creating AI” paradigm, featuring a visual assembly environment and a massive repository of modular components—including tools, knowledge bases, and industry-specific templates. By introducing the DAG (Directed Acyclic Graph) mechanism, Co-Sight enables multi-agent collaboration with automatic parallel processing, significantly boosting the execution efficiency of complex workflows. While it is a heavy-duty industrial solution meant for large-scale operators and enterprises, its ability to reduce AI hallucinations through a continuous trustworthiness feedback loop makes it the premier choice for mission-critical sectors like telecommunications, healthcare, and automotive design.
Features
Modular "Component Workshops"
Separate repositories for tools, knowledge (RAG), and models that can be plugged into any agent design.
Visual Assembly Environment
A low-code, drag-and-drop canvas that enables rapid customization of AI agents within minutes.
DAG Parallel Processing
Uses Directed Acyclic Graph mechanisms to identify task dependencies and execute concurrent nodes simultaneously for maximum
Trustworthiness Evaluation System
A continuous feedback loop that audits agent decision-making to minimize hallucinations and ensure industrial-grade reliability.
Three-Layer Open Protocol (A2A-T)
The industry's first open protocol for standardizing Human-Computer, Agent-to-Agent, and Knowledge collaboration.
Autonomous Learning
Enables agents to independently learn from operational experience and even "create their own tools" to solve new problems.
Best Suited for
Telecom Operators
Building L4+ autonomous networks that handle fault management and network optimization without human intervention.
Healthcare Providers
Generating standardized medical diagnostic reports with over 95% accuracy in minutes.
Industrial Manufacturers
Redefining sensing and decision-making on the factory floor for intelligent production scheduling.
Urban Transit Systems
Managing complex metro operations and government governance through unified visual intelligence.
Automotive Designers
Using AI agents to boost creativity and efficiency in the 3D modeling and vehicle design process.
Academic & Research Institutions
Popularizing AI general and specialized courses through integrated "AiCube" training solutions.
Strengths
Top-Tier Reasoning
Ecosystem Openness
Industrial Scale
Reduced Hallucinations
Weakness
High Entry Barrier
Complexity of Choice
Getting Started with ZTE Co-Sight: Step-by-Step Guide
Step 1: Enter the Modular Workshop
Log in to the Co-Sight Factory. Browse the Tool & Skill Workshop to select the specific plugins or APIs your agent will need to call.
Step 2: Build the Knowledge Base
In the Knowledge Workshop, upload your industry data to create a Retrieval-Augmented Generation (RAG) base that grounds your agent in facts.
Step 3: Assemble the Agent
Open the Visual Assembly Workshop. Drag your chosen tools, knowledge bases, and LLMs onto the canvas and orchestrate their workflow logic.
Step 4: Configure the Trustworthy Loop
Set the evaluation parameters for the trustworthiness system. This ensures the agent cross-checks its output before final execution.
Step 5: Deploy via Open Protocols
Use the one-click deployment tools to launch your application. Monitor performance in real-time using the built-in observability features.
Frequently Asked Questions
Q: What does "AI making AI" mean?
A: It refers to the platform’s ability to use a modular, automated framework where the AI system itself assists in the development and evolution of specialized agents.
Q: Can Co-Sight agents talk to other AI agents?
A: Yes. Co-Sight features the industry’s first three-layer open protocol (A2A-T), which standardizes communication between different agents and vendors.
Q: Is it only for 5G networks?
A: No. While it excels in telecom, it is used across Healthcare, Automotive Design, Urban Transit, and Education.
Pricing
ZTE Co-Sight is an enterprise-level SaaS/On-Premise solution. Pricing is custom-tailored based on the scale of deployment and specific industrial modules required.
| Service Component | Tier | Target | Key Benefit |
| Studio Enterprise | Standard | Large Firms | Full access to modular workshops and visual assembly. |
| Co-Sight Super Agent | Premium | Global Operators | High-concurrency support with A2A-T protocol and DAG. |
| AiCube (All-in-One) | Hardware-Cloud | Specialized Scenarios | Ready-to-deploy hardware+software for Education/Healthcare. |
Alternatives
Huawei iMaster NCE
A rival autonomous network solution with strong focus on self-healing and intent-driven networking.
Nokia AVA (AI Video Analytics/Assistant)
A specialized competitor in the telecom space focusing on customer experience and network efficiency.
Ericsson Cognitive Software
Leverages AI for predictive network optimization and energy management.
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