Processes span many systems
A single task has staff querying, judging, entering and confirming across several platforms, making the automation boundary complex.
Cross-industry solution · AI Agents & Workflow Automation
AI that doesn't just answer,
but takes part in execution
Combining AI, business rules, workflows, system tools and human review to turn repetitive cross-system, cross-role tasks into orchestrated, observable and interruptible execution.
Scenario ArchitectureCross-industry solution
Managed objectsBusiness tasksRules & knowledgeSystems & tools
Solution coreAgent workflowTask understandingTool invocationHuman approval
Business resultsAutomated executionControlled processTraceable results
Typical challenges
Repetitive tasks can be automated,
but rarely by a model alone.
For enterprises with heavy cross-system lookups, content processing, rule-based judgment, data entry and coordination work, looking to adopt agents safely.
Rules and exceptions coexist
Standard flows can be codified, but real work carries many conditions, exceptions and human judgment points.
Runtime results are hard to control
Without permissions, tool boundaries, human approval, runtime logs and failure handling, agents rarely reach production.
Solution architecture
From business objects to underlying data,
a complete operating chain.
Real projects combine these layers according to existing systems, data conditions and delivery boundaries — replacing your current platform in one step is never required.
Task entry layer
Receives user requests, system events, scheduled jobs or business process triggers.
Understanding and orchestration layer
Task decomposition, context retrieval, rule evaluation and execution path selection.
Tools and collaboration layer
Calls APIs, business systems, knowledge bases and automation tools, with human approval points.
Runtime governance layer
Manages permissions, evaluation, logs, exceptions, cost, versioning and continuous tuning.
Key capabilities
Built around the core business chain,
as composable solution capabilities.
Functionality, data, interfaces and processes are designed around the target scenario and connect to your existing technical environment.
Task interpretation and decomposition
Identifies the goal, required information, execution steps and risk conditions.
Tool and system invocation
Queries data, processes content and performs system operations through controlled interfaces.
Human approval checkpoints
Introduces human review at significant judgments, sensitive operations and exceptions.
Runtime monitoring and tuning
Tracks success rate, quality, cost, failure causes and user feedback.
Management outcomes
More than delivering a system —
improving how work actually runs.
Outcome metrics are defined further against your business goals; this page shows the management changes the solution typically aims for.
Fewer repetitive operations
High-frequency lookup, compilation, entry and routing tasks move to automated flows.
A process that stays controlled
Tool permissions, rule boundaries and human approval are configured by business risk.
Connected cross-system work
The agent acts as an execution layer linking knowledge, data and existing systems.
A continuous improvement loop
Runtime records and result evaluation keep refining the process and model configuration.
Project consultation
Clarify the business problem first,
then decide how the system should be built.
Tell us the business problem to solve, your existing systems and the outcome you expect — we usually reply within 1 business day.