Overview
Unified workbench
Tasks, conversations, knowledge and agents in one entrance.
Platform · AI-OS
The enterprise AI operating system.
Models / data / agents / apps, one foundation.
AI-OS is Global DT's flagship platform. Model access, knowledge accumulation, agent collaboration, orchestration and cloud ops — packaged as configurable product capabilities so enterprises stop assembling AI scenarios from scratch.
Modules · 11 surfaces
Not a chat box. A full enterprise AI capability set.
Every module is both a workbench and a capability other modules can call — AI-OS is a platform, not a demo.
Tasks
Task orchestration
Plan / Action / Reflection — replayable, interruptible agent tasks.
Collaboration
Multi-agent collab
Conversation flow between people, agents and agent-to-agent with audit.
Development
App & extension dev
Build new agents, tools and modules inside AI-OS, sharing identity and permissions.
Mido
Mido assistant
Cross-platform assistant with long tasks, durable runs and session replay.
HR
Org & HR
Employee directory, performance, recruitment flow, resume analyzer agents.
Agents
Agent catalog
Register and govern internal / external agents — every call audited and quota-bound.
Knowledge
Knowledge space
Docs, graph, vectors, retrieval — one sync from source to question-answering.
Automation
Operational automation
Weekly reports, compliance, monitoring, inspections — agentized and event-triggered.
Governance
Governance & audit
API keys, quotas, model permissions, audit logs, sensitive-term & permission policy.
Cloud Ops
Cloud & ops
GPU, model gateway, private cloud, nodes, backup, observability — infrastructure as product.
Architecture · 4-layer stack
Stacked, individually accessible, fully replaceable.
AI-OS is not an unforced black box. Apps / Agents / Data / Models layers communicate via explicit interfaces — enter from any layer.
Layer 1
Apps · Application layer
Workbenches, consoles, industry workspaces, public portals
- AI-OS Portal
- AiDo assistant
- Industry workspace
- Shuke Chain
Layer 2
Agents · Agent layer
Callable, governable digital workers
- Plan / Action / Reflection
- Tool calling / protocol adapt
- Session replay
- Permissions & audit
Layer 3
Data · Data & knowledge
Docs, vectors, graph, indicators
- Knowledge space
- Vector index
- Graph relations
- Eval & feedback loop
Layer 4
Models · Model & compute
Standardized model and compute supply
- Model gateway
- Private models
- GPU scheduling
- API key & quota
MCP Bridge · Connectivity
Wrap legacy systems into agent-callable tools.
MCP (Model Context Protocol) is the industry standard for agents calling external tools. Global DT offers MCP server customization — bring your existing systems into AI-OS without surgery.
Why MCP? The hardest part of any enterprise AI project isn't the model — it's plumbing AI into the pile of legacy systems sitting inside the company. SOAP-era ERP, cloud-native CRM, ticketing behind a VPN, databases with only a GUI. Every customer used to demand glue code rebuilt from zero, eating months of engineering. MCP standardizes "agent calling external tool": each tool is an MCP server exposing a consistent schema, params, calls and returns; the agent doesn't care whether REST, gRPC, SOAP or a direct database sits behind.
What Global DT does: We deliver MCP server customization for each key system you run — our team reads the ERP, CRM, OA, ticketing, document management and internal APIs, then writes an MCP server for each and registers them into the AI-OS tool catalog. Every MCP tool ships with explicit permission declarations (read / write / delete / trigger) and quotas; agent calls are bound by whitelist, quota and audit. Legacy systems gain AI-OS governance without code change.
This is the most reliable bridge from legacy business to intelligent automation — your siloed manual moves in ticket dispatch, contract approval, inventory scheduling and government filings become end-to-end agent-driven workflows. Paired with the private cloud, the first AI step for legacy systems can finally be done in a week.
Legacy systems → MCP server
ERP, CRM, OA, ticketing, legacy databases — clients change nothing; Global DT wraps each into an MCP server with a standard schema.
Agents call across systems
Any AI-OS agent consumes these tools via MCP — cross-vendor, cross-language, cross-segment. IT assets shift from data silos to agent-callable tools.
Legacy × automation
Ticket dispatch, contract approval, inventory scheduling, gov filings — manual moves now end-to-end agent-driven workflows.
Whitelist + quota + audit
Each MCP tool ships with explicit permission declarations and quotas; agent calls are bound by whitelist, quota and audit.
Onboarding · Path to production
Three steps. Land AI-OS in your enterprise.
No year-long PoC required. We start from the highest-value scenario and run discovery → pilot → scale together.
- 01
Discovery & alignment
Inventory existing systems, compliance edges and first-batch use cases. Deliver a 1-2 week viable path.
- 02
Onboard & pilot
Connect AI-OS to enterprise identity, knowledge and SaaS. Land 3-5 core agents and set baseline metrics.
- 03
Scale & govern
Expand by department and business line. Land permissions, audit, model quotas, private deployment and operations together.
Get started
Turn AI into your company's digital foundation.
Email business@hqshuke.com or book a session below. We start from the single scenario that matters most to you.