DDW AI HUB · PLATFORM

Infrastructure for Enterprise AI,
Packaged as Standard Components

Disconnected data, model lock-in, low adoption, runaway costs — the DDW platform turns the most common barriers to enterprise AI adoption into built-in platform capabilities, one by one. Plugins share the platform, so development never reinvents the wheel.

ARCHITECTURE

Eight Infrastructure Services, One Complete Capability Chain

The platform provides every shared service an AI application needs to run; plugins carry business logic only and never touch infrastructure.

01

LLM Gateway

Unified multi-model access: freely mix cloud models (GLM, Kimi, DeepSeek, and more) with local models (Ollama/vLLM). Three-tier failover keeps business running, and cost-aware routing automatically assigns each job to the most economical model — with swappable and downgradeable models throughout.

02

Plugin Management

Standard .ddwplugin package format (manifest + signature + lifecycle); install, remove, upgrade, and roll back are fully automated, and plugins collaborate through an event bus, fully decoupled.

03

Event Bus

Business actions automatically trigger downstream flows: order created → notify sales → draft contract → payment reminder. Wildcard subscriptions and retry on failure; no hard-coded calls between plugins.

04

IM Adapters

Omnichannel IM adapters: one unified messaging interface across DingTalk, Lark, and WeCom. Bots, message cards, and approval flows work out of the box — employees get work done inside the IM they already know, with zero learning curve.

05

DataConnector

Connects directly to existing ERP/MES/LIMS/QMS systems and supports 6 database engines including PostgreSQL, MySQL, SQLite, and Oracle. No re-engineering, no migration — data silos are bridged in place.

06

Security Baseline

Three layers of tamper protection, license verification, AI-crawler defense, supply-chain poisoning protection, and data privacy compliance. Enterprise data assets stay secure and under your control; in on-premises deployments, data never leaves your intranet.

07

Billing & Revenue Sharing

Four metering models — tokens, API calls, plugin activations, and business outcomes — with transparent, auditable channel revenue sharing, underpinning the pay-for-outcomes AI-RaaS model.

08

Theme Engine

Platform-wide style templates (standard / festive / muted) are switched from one admin console, so holidays and major events get fast responses. The website theme is delivered by the same platform and managed site-wide.

DESIGN PRINCIPLES

Three Design Principles

The platform is not a pile of features — it is designed around the real barriers to enterprise AI adoption.

Principle 01

No Lock-In

No lock-in to any LLM, database, or IM — existing investments stay valid, and future choices stay open.

Principle 02

Pluggable

Every plugin is a minimal usable unit; a customer's business scenario equals an assembled combination of plugins. A small customer may pick 5 plugins, a large one 27 — scale to fit.

Principle 03

Outcome-Driven

From delivering tools to delivering outcomes: CNC yield assurance and ESG compliance assurance are paid by business results, tying cost to impact.

DEPLOYMENT

Four Deployment Options, Scaled to Fit

Make full use of your existing computing resources. CPU-only AI is perfectly usable early on; invest in GPU capacity only after the gains are proven — you set the pace of investment.

Deployment ModeBest ForDetails
StandaloneMicro businesses, pilot trialsSingle-machine deployment, ready right after install
CloudSMB production environmentsHosted on cloud servers; no on-site data center needed
HybridData-sensitive enterprisesCore data stays on-premises, general compute in the cloud
FDE ServiceCustomers with custom requirementsEnvironment checks, deployment, custom development, and guided operations
Explore DDW Implementation Services →

Browse the Plugins First, Then Talk Deployment

The platform's capabilities are ready; what determines value is the business plugins. Visit the marketplace and see which scenarios fit you.