Qeasy Cloud
Get Started
Enterprise AI Agents in Production

AI Agents That Do Real Work in Real Businesses

Qeasy does not build demo-grade AI showcases. Backed by our data integration platform and agent runtime, Qeasy AI agents already run in production inside large-scale e-commerce finance reconciliation and supply-chain replenishment — traceable, auditable and rollbackable.

Production scenarios

Two Product Lines, Running in Production Today

Every scenario follows the same delivery pattern: fact data as the foundation, agents acting on a governed pipeline, humans confirming only what matters.

E-commerce finance · In production

Qeasy AI Agent Smart Reconciliation

The pain

Every platform's statement format is different. Finance teams repeat 'manual exports + row-by-row Excel checks' every month, hunting discrepancy causes by hand and allocating shared expenses by gut feel.

The agent solution

A general assistant plus three domain agents — bill parsing, reconciliation and expense allocation — form the agent matrix. Business users state requirements in natural language; agents reconnoiter, write and sandbox-test autonomously, while every business side effect still goes through the existing 'script + job queue' pipeline — rollbackable and auditable.

The value

Three-way matching across platform statements ↔ supply-chain orders ↔ internal accounting runs automatically, with variance amounts and reasons persisted per row and full lineage. For concrete capability metrics and platform coverage, see the /reconciliation page.

Explore reconciliation
Supply chain · In production

Qeasy AI Agent Smart Replenishment

The pain

Replenishment relies on manual exports and Excel formulas. Sales, inventory and in-transit data sit in separate systems; every decision lacks a stated basis, and mistakes cannot be traced back.

The agent solution

Three registered agents — a general assistant, a fetch script engineer and a compute script engineer — work together. Sales, inventory, in-transit and product master data converge into one fact foundation; agents guide business users through fetching, formula computation, plan adjustment and replenishment order generation, with a business-language confirmation before every write action.

The value

Every replenishment suggestion is backed by data, formulas and reports, traceable row by row through adjustment history and lineage. Two pipelines are live — 2C self-operated weekly replenishment and office-supply omnichannel replenishment; see the /replenishment page for details.

Explore replenishment
Capability foundation

Behind the Agents: Qeasy's Enterprise-Grade Foundation

AI agents are not castles in the air — connectivity, orchestration and data decide how far an agent can go in real business.

Integration platform connectivity

The Qeasy data integration platform ships 500+ prebuilt connectors — Kingdee, Yonyou, SAP, Jushuitan, Jikeyun, Mabang and more across ERP, e-commerce and supply chain — putting real business data within the agent's reach.

API orchestration with governed execution

Every agent write action goes through the existing 'script + async queue + state machine' pipeline: dual-layer sandbox isolation, business-language confirmation before triggers, full tool-call auditing and rollbackable versions.

Fact data and knowledge bases

Heterogeneous business data is normalized into a finance-grade fact-data layer; a knowledge base with hybrid vector + keyword retrieval distills platform rules and business calibers into cognition agents can reason over.

Adoption path

From Scenario to Production in Four Steps

01

Scenario diagnosis

Together with your business team, we pick high-frequency, well-ruled, data-available scenarios and define the agent's capability boundaries and confirmation gates.

02

Data integration

We connect the relevant business systems via 500+ connectors and API orchestration, building the fact-data foundation the scenario needs.

03

Agent orchestration

Domain agents and knowledge bases are configured, write actions are wired to existing scripts and execution pipelines, and everything is sandbox-tested before a staged rollout.

04

Production operations

Full auditing and execution observability accompany the launch; scripts, calibers and agent skills keep evolving with business feedback.

FAQ

About Enterprise AI Agent Adoption

Where are Qeasy AI agents already in production?

Two product lines run in production today: e-commerce financial reconciliation (/reconciliation) and supply-chain smart replenishment (/replenishment). Capability metrics, platform coverage and pipeline details follow the respective product pages.

Will agents bypass systems and mutate business data directly?

No. Every business side effect goes through the existing 'script + job queue' pipeline: scripts run in a dual-layer sandbox, execution requires one business-language confirmation, all tool calls are persisted to audit tables, and version history is rollbackable.

Can our own ERP or e-commerce systems be integrated?

Yes. The Qeasy data integration platform has accumulated connectivity to 500+ mainstream systems — Kingdee, Yonyou, SAP, Jushuitan, Jikeyun, Mabang and more. Each project confirms scope around business goals, API contracts and data calibers.

How do we evaluate whether our scenario fits an agent deployment?

Good candidates share three traits: high-frequency repetition, describable rules and available data. Reach us via /contact — our consultants will run a scenario diagnosis based on the experience from our two production product lines.

Put AI Agents to Work in Your Business

Tell us your scenario. Drawing on our production reconciliation and replenishment experience, our consultants will design an auditable, rollbackable path to production for your agents.

Enterprise AI Agents in Production - Smart Reconciliation & Replenishment | Qeasy Cloud