Services

Around the key aspects of enterprise AI deployment, CoT Network provides integrated services from strategy and scenarios to systems and continuous optimization.

AI Consulting & Scenario Diagnosis

Help the enterprise decide where AI should start and which scenarios are worth prioritizing — a clear, pragmatic, executable path to adoption.

AI application strategy and staged goals
Business and management process diagnosis
High-value, deployable scenario identification and prioritization
ROI logic and implementation roadmap
Organizational mechanism and capability-building advice

We focus not just on technology selection, but on a genuinely executable AI adoption path given the enterprise's real conditions.

AI Applications & Agent Delivery

Build genuinely usable, sustainably running AI applications and agents around knowledge, processes, roles, and business analysis.

Enterprise knowledge base and Q&A systems
Role-specific professional AI assistants
Agent workflow design and deployment
Model adaptation and scenario-specific applications
Integration with existing business systems

We emphasize production-grade delivery — the solution actually enters the business, gets used by teams, and keeps iterating, not a demo.

Data Governance & Knowledge Systems

Organize scattered documents, policies, cases, and operating data into a callable, understandable, traceable foundation that AI can use.

Unified ingestion and structuring of documents, policies, and cases
Knowledge system and retrieval index construction
Vector databases and document-parsing environments
Metric governance and quality validation
Knowledge-update and access-control mechanisms

AI reliability rests on a callable, understandable, traceable knowledge and data foundation.

Training, Co-creation & Companion Support

Help the organization build internal understanding, delivery mechanisms, and continuous-optimization capability — moving AI from pilot to organizational capability.

Leadership and business-team enablement
Scenario co-creation workshops
Internal delivery mechanisms and collaboration design
Impact evaluation, feedback, and iteration
Aligning milestone results with the long-term roadmap

An AI project's real value is released gradually after go-live, so we prioritize sustained progress over one-off delivery.

AI Hardware & Private Deployment

For teams with security, performance, and deployment requirements, we provide end-to-end support — from server selection and model deployment to private-environment setup and ongoing operations — so AI runs in a controlled, stable production environment.

AI compute planning and GPU server selection
Private deployment: own servers, intranet, private cloud, or on-prem data center
Model inference services, vector databases, and document-parsing environments
Agent platforms and business-application backend deployment
Long-term operations, security hardening, and model upgrades

From "can demo" to "can go live," AI needs software, models, data, and hardware working together. We help clients build a sustainable, scalable, maintainable AI capability foundation.

AI Infrastructure & Private Deployment

Beyond delivering AI applications, we help build the base environment where AI runs stably.

AI compute planning

Plan GPU servers, local compute, or cloud-edge collaboration based on scenario, model scale, concurrency, and budget.

Private deployment

Deploy AI applications, model services, and knowledge systems on the client's own servers, intranet, private cloud, or on-prem data center.

Model & application environment

Deploy key components: model inference services, vector databases, document parsing, agent platforms, and application backends.

Operations & optimization

Long-term operations and optimization around performance, stability, security, resource utilization, and model upgrades.

From "can demo" to "can go live," AI needs software, models, data, and hardware working together.