Harbor AI
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ENTERPRISE AI

Understand the work.
Then decide where AI fits.

Start with a business problem. Consider workflows, data, systems and people's responsibilities together. Find a testable starting point through projects, introductory training or technical workshops.

Find your starting pointExplore our work

Business understanding / Product creation / AI engineering

START WITH YOUR FOUNDATION

Different foundations.
Different starting points.

Start with one task. Different teams in the same company may begin in different places.

01 / MAKE THE WORK CLEAR

Business and digital foundations are still taking shape

  • Information lives in chats, spreadsheets and personal files
  • Rules depend on experience and repeated clarification
  • Inputs, ownership or completion criteria are unclear

Make the work understandable to AI.

  1. Map one task
  2. Organize rules and information
  3. Test one small use case

Takeaways: a workflow map, information checklist, first use case and acceptance criteria.

Start with scoping and training →

02 / CONNECT TO EXISTING WORK

Systems, data and an implementation team are in place

  • ERP, OA or CRM already supports daily work
  • Key workflows, data sources and permissions are defined
  • IT or AI colleagues can help implement the solution

Bring AI into work that is already defined.

  1. Confirm data and interfaces
  2. Define permissions and human review
  3. Validate before integration

Takeaways: an integration plan, permission boundaries, validation notes and an improvement list.

Explore enterprise AI projects →

BUSINESS SCENARIOS / ILLUSTRATIVE EXAMPLES

See how AI can join a specific task.

Expand a scenario to see inputs, AI work, human review and outputs. Integration scope is agreed for each project.

Marketing & salesTurn an inquiry into a quotation draft for follow-up
Inputs
Customer emails, product catalog and pricing rules
AI contribution
Extract requirements, match candidate products and flag missing information
Human review
Sales staff confirm specifications, prices and commercial terms
Outputs
A quotation draft with sources and items awaiting confirmation

Check first: consistent product codes and ownership of missing information.

Product & R&DTrace technical answers to a version and a source
Inputs
Specifications, project documents and past issue records
AI contribution
Retrieve relevant passages, compare differences and attach sources
Human review
Engineers confirm version applicability and technical conclusions
Outputs
A sourced summary and a list of questions to verify

Check first: identifiable versions and a way to exclude outdated information.

Procurement & supply chainTurn delivery-date changes into clear follow-up tasks
Inputs
Purchase orders, supplier updates and delivery schedules
AI contribution
Compare commitments with updates and propose follow-up actions
Human review
Procurement staff confirm changes and external communications
Outputs
An auditable exception list and follow-up drafts

Check first: current order status and a named owner for each alert.

Production & qualityFind relevant experience in past exception records
Inputs
Inspection records, SOPs, past issues and corrective actions
AI contribution
Locate similar records and summarize approaches with sources
Human review
Quality or production owners confirm applicability and action
Outputs
Recommendations with references for resolving an issue

Check first: whether past experience aligns with the current SOP.

Finance & operationsTurn metric changes into a review checklist
Inputs
Authorized reports, metric definitions and transaction details
AI contribution
Compare changes, link underlying records and organize possible explanations
Human review
Finance or business owners verify definitions and causes
Outputs
An operating summary with calculation definitions and source records

Check first: metric definitions, data dates and access permissions.

Company knowledgeGive recurring business questions traceable answers
Inputs
Policies, processes, product documents and training materials
AI contribution
Retrieve authorized information and answer with sources
Human review
Content owners confirm versions; complex questions go to the right person
Outputs
Traceable answers and a list of knowledge gaps

Check first: who maintains the content and who handles unanswered questions.

UNDERSTAND THE WORK

Five perspectives. One actionable checklist.

Connect each gap to an owner and a next step.

Business

What should improve?

Task scope and acceptance criteria

Workflow

Where does work repeat, wait or need judgment?

A workflow map and human-review points

Data

Can information be obtained accurately and consistently?

Data sources and preparation needs

Systems

Which interfaces and actions can be enabled?

Integration points and permissions

People

Who uses, maintains and handles exceptions?

Ownership and review arrangements

The result: priority use cases, missing foundations and a small-scale validation plan.

AI AT WORK / ILLUSTRATIVE ROLE

An AI worker starts with
a clear working agreement.

An order-processing assistant shows how responsibilities, tools and human judgment fit together.

Illustrative example

Order-processing assistant

Organize order information into an auditable draft for a person to confirm.

  1. Email / Excel / PDF
  2. Extract & validate
  3. Draft for review
  4. Human approval
  5. Authorized ERP write
Information & knowledge
Original orders, product codes and field rules, with sources retained.
Responsibilities & SOP
Extract, validate and draft; do not decide commercial terms independently.
Tools & permissions
Use agreed data and interfaces; confirm authorization before a formal write.
Collaboration & exceptions
Pause for missing fields, uncertain matches or failed actions; hand over to a named person.
Acceptance & records
Check agreed samples for fields, sources and exception handling; record results.

WAYS TO WORK TOGETHER

Projects and training, grounded in real work.

Build an application together, or help your team establish a practical way of working.

Enterprise AI projects

Turn a defined need into an application that can be tried and tested.

From a need to a usable application

What you take away

  • Problem and scope agreement
  • Application prototype and workflow
  • Validation notes and handover guide

Introductory AI training

Start with a daily task and bring practical methods back to work.

For business and functional teams

What you take away

  • A shortlist of suitable use cases
  • Reusable task templates
  • Practice and review notes

TECHNICAL WORKSHOP

Already have an AI team?
Start with your current challenge.

Bring an active project, your current architecture and a specific obstacle. Locate the issue, compare options and plan validation together.

Architecture review

Retrieval is inconsistent, tool boundaries are unclear or the workflow is growing too complex.

Outputs: an issue list, key constraints and prioritized improvements.

Focused validation

Test a clear hypothesis about retrieval, tool use, permissions or a long-running task.

Outputs: a test plan, samples and criteria; a small runnable validation within the agreed scope.

Technical co-creation

Work with the internal team on responsibilities, trade-offs and the next implementation stage.

Outputs: a technical roadmap, actionable improvements and a review plan.

  1. Bring the current design and issue
  2. Break it down and compare options
  3. Validate the key hypothesis
  4. Agree the next actions

Prepare: an architecture sketch, shareable samples, current constraints and the result you want to improve.

ENTERPRISE PRACTICE

Inside enterprise workflows

Case study in preparation

Order information processing

Details will be added later.

Case study in preparation

Enterprise AI Workspace

Details will be added later.

SELECTED WORK

See our approach through selected work.

Overseas Lead Generation →

From business inputs to target-customer research.

Miaopu · AI Product Pages →

From product information to a complete content set.

Global UGC Video →

Content built around product-use scenarios.

AI Marketing Video Workspace →

Organizing company materials for video.

A PRACTICAL NEXT STEP

You don't need a complete plan.
Start with one real task.

Bring a specific task, the information you use and the result you want to improve. That is enough to start a useful conversation.

Explore our workMore about Harbor AI →