Built in China. Connected to business worldwide.

Jice Tech starts with business goals, validates the right scenarios, delivers working products and operates them over time—so AI enters real workflows, connects systems and produces measurable outcomes.

01Knowledge
02Tasks
03Governance
Enterprise Agents
AI Transformation Advisory
Productized Delivery
Cross-market Delivery

JICE ENTERPRISE AI STACK · SYSTEM READY

Enterprise AI operating system

Moving from an operating goal to agent action takes more than a model call. Jice brings data, systems, governance and operations into one observable six-layer structure.

JICE / AI OPERATING CORERUN · 0720-AI
01
VALUE

Business scenarios

Define agent responsibilities from operating metrics and role-level tasks.

02
CONTEXT

Knowledge & data

Connect structured data, documents and live operating context.

03
ORCHESTRATE

Agent orchestration

Decompose work, route models and coordinate specialized agents.

04
ACTION

System connections

Safely operate CRM, ERP, collaboration platforms and proprietary tools.

05
GOVERN

Governance & evaluation

Embed access, audit, quality and cost constraints into runtime.

06
EVOLVE

Continuous operations

Improve prompts, knowledge, tools and task scope from production feedback.

Operating goalScenario designKnowledge retrievalModel reasoningTool executionHuman approvalOutcome feedback

Three products spanning intelligent decisions to growth execution

Deploy each product independently or combine them across intelligent collaboration, marketing operations and brand growth.

ThinkNow Agent Platform

ThinkNowA trusted foundation for enterprise agents to work together

ThinkNow turns foundation-model capabilities into enterprise agents that teams can orchestrate, govern and improve over time. It connects knowledge and business systems so every role can use AI within explicit permissions and quality standards.

Explore product
Hisale Marketing Spend Management

HisaleConnect every marketing expense to an operating outcome

Hisale replaces fragmented spreadsheets with consistent spend definitions and traceable workflows so finance, marketing and management work from the same data—from budget commitment to campaign outcome.

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BootMall DTC Commerce Suite

BootMallLaunch a global commerce presence your brand owns

BootMall helps brands move beyond marketplace templates and launch storefronts built for brand expression, search growth and local buying behavior. Modular capabilities support fast launch and market-by-market expansion.

Explore product

INDUSTRY COVERAGE / OPERATING CONTEXT

Useful AI begins with understanding how each industry operates

We begin with roles, workflows, data maturity and regional constraints—not a generic feature checklist.

01Multi-market growth

Cross-border retail

Unify product, content, service and marketing data across markets so local teams move faster while headquarters retains operational visibility.

02Knowledge efficiency

Smart manufacturing

Connect equipment documentation, process knowledge and quality workflows to agents for faster search, diagnosis and training.

03Method reuse

Professional services

Turn expert methods and project material into reusable organizational assets across research, proposals, delivery and review.

04Localized operations

Regional brands

Build localized growth infrastructure around language, channels and payment behavior to validate new markets efficiently.

05Workflow alignment

B2B services

Connect leads, proposals, contracts and customer success so sales collaboration moves from individual habit to standard operations.

06Scaled operations

Platform operations

Orchestrate review, inspection, attribution and exception handling to improve consistency at operating scale.

Build an AI capability that keeps improving after launch

Validate one high-value scenario, then use real feedback to expand what agents can safely own.

  1. 01

    Discover

    Start with operating goals and workflow friction to identify the highest-value scenarios.

  2. 02

    Validate

    Use working prototypes to validate business value, data readiness and organizational readiness.

  3. 03

    Integrate

    Connect knowledge, systems and permissions so agents become part of production workflows.

  4. 04

    Operate

    Continuously evaluate outcomes, govern risk and expand task boundaries responsibly.

Start with an industry problem. Deliver an outcome teams can sustain.

Cases are anonymized; target outcomes are shown as solution estimates.

Cross-border Consumer Brand

Unifying marketing spend across six markets in one operating view

Hisale unified budgets, delivery evidence and attribution so marketing, finance and management could work from the same spend language.

30–45%Target reduction in monthly settlement cycle90%+Target real-time budget visibility1Unified cross-market spend language

“What gave us confidence was that every answer returned to its source, and the agent knew when to stop and ask a person.”

Digital transformation lead, manufacturing company · Project interview summary
View all client work

Production AI requires product, engineering and organizational alignment

Jice brings business advisory, product design, engineering integration and cross-market operations into one delivery system.

Business-engineering alignment

Advisory, product and engineering define the problem together so business goals remain connected to delivery.

Open, composable architecture

Support multiple models, data sources and existing systems while preserving room to evolve.

Governance throughout

Design permissions, auditability, data boundaries and quality evaluation from the prototype stage.

Bilingual cross-market delivery

Combine efficient delivery with sensitivity to language, channels and compliance across markets.

Agent Operations · 8 min

How enterprise agents move from demos into real operations

The real dividing line is not how clever the model sounds, but whether task boundaries, data permissions and operating mechanisms work together.

Read insight

FAQ / DELIVERY DECISIONS

What enterprise teams ask before getting started

Every engagement has different boundaries, but a mature delivery path makes key decisions clear before work begins.

01How long does a typical engagement take?

We typically spend 2–4 weeks on scenario discovery and a working prototype, followed by 6–12 weeks for the first production scenario. Timing depends on data readiness, system access and governance requirements.

02Do you support private or dedicated-cloud deployment?

Yes. We support public cloud, dedicated cloud and on-premises combinations, shaped by data sensitivity, concurrency, operating capability and budget.

03Are solutions tied to one model provider?

No. Models can be routed by task quality, latency, cost and regional availability, with substitution and fallback designed in.

04How is enterprise data protected?

We design least privilege, data classification, transport and storage security, action approval, audit trails and masking as layered controls, followed by a production risk review.

05Where should we begin if the use case is not clear?

Start with a workshop focused on operating goals. Together we map frequent, costly, risky or high-growth workflows and produce a prioritized opportunity list and validation plan.

06Can you support cross-market operations?

Yes. Our team works in Chinese and English, accounting for differences in language, data availability, channels, payments and infrastructure while validating with in-market teams.

Clarify your first high-value scenario

Start with a conversation focused on your business goal

Share your business goal, current stage and constraints. We will assess scenario value and data readiness, then recommend a practical next step.