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Enterprise AI Agent Delivery

Let AI Agents WorkYou Make Decisions

Turn repetitive work into deployable, manageable, evolving AI digital employees.

Works with leading AI and enterprise platforms
  • WeCom
  • Lark
  • Coze
  • Dify
  • Anthropic
  • Claude
  • ChatGPT
  • Kimi
  • Qwen

Three Barriers to AI Adoption

The challenge is turning AI into reliable, sustainable business operations.

AI, but No Clear Path

  • You cannot justify an in-house AI team, and no-code tutorials still fail to produce a workflow that runs in the real business.

Demo Works, Production Fails

  • Once real customers and orders are involved, wrong answers and missed requests become costly. Without human fallback, the project stays a pilot.

Live, but Hard to Maintain

  • A model, prompt, or business change can break the workflow. Without continuous monitoring and maintenance, the AI quickly becomes unusable.

Three AI Paths. Who Owns the Outcome?

DIY builds skills. Outsourcing builds tools. TranFu delivers results.

Comparison of three AI implementation approaches
Key differenceBuild it yourselfOutsource a toolTranFu delivery
OutputSkills and prototypesA tool or systemA production AI employee
Tech skillsYes, ongoingYes, to scope and reviewNo—just business decisions
Error ownerYouYou after launchTranFu, until metrics are met
PricingTime plus toolsOne-off project feeDiagnose, build, and manage
After launchYou maintain itPaid or limited supportWe keep improving it

Four Steps: Prove, Then Scale

Start with the smallest complete loop, then expand.

  1. Diagnose

    30 minutes

    Map the workflow, set human boundaries, and define measurable success.

  2. Thin Slice

    1–2 weeks

    Run the smallest real end-to-end path to expose design risks.

  3. Launch

    2–3 weeks

    Verify against agreed metrics. If we miss, we keep tuning at no charge.

  4. Improve

    Ongoing

    Turn every live issue into a lasting improvement as needs change.

Find Your AI Starting Point in 60 Seconds

Three steps to get a workflow plan, AI employee design, ROI, pricing, and timeline.

Usage
New in 7 days48
Industries8
  1. Professional Services24%
  2. Education / Training19%
  3. Manufacturing / Supply Chain14%
  4. Software / SaaS5%
  5. Food / Local Services3%
  6. Healthcare / Wellness2%
  7. Other2%
1Business
2Workflow
3Goals

Analyzing your workflow…

Three Stages, Clear Pricing

Diagnose first, then decide. The fee is credited to delivery.

Diagnostic

See if this workflow is worth automating

¥2,000 – 5,000
Fully credited to delivery
Book Diagnostic

What You Get

  • On-site or remote workflow review
  • AI boundaries and success metrics
  • Structured diagnostic report
  • Digital employee design and quote
  • Clear human fallback points
Recommended

Standard

Turn one workflow into a live AI employee

¥20,000 – 80,000
Build, launch, and verification
Book a Call

What You Get

  • One production-ready AI employee
  • Real channels and data connected
  • Thin-slice validation before scale
  • Metric-based verification and tuning
  • Training and 30-day warranty

Custom + Managed

Run and improve multiple workflows long term

¥80,000 +¥5,000–20,000/mo
Build fee plus monthly retainer
Book a Call

What You Get

  • Cross-team workflow orchestration
  • Dedicated delivery owner
  • Every live issue drives improvement
  • Monthly outcome reviews
  • Priority support and model upgrades

Indicative pricing for mainland China. The final quote follows the diagnostic—we do not price a workflow before understanding it.

Let Digital Employees Handle Repetitive Work

Clear, repeatable, traceable workflows can usually become AI Agents.

Content

Content at Scale

Produce product copy, posts, support scripts, and SOPs in your brand voice, with human review.

Data

Daily / Weekly Reports

Collect, clean, analyze, and send multi-source data on schedule.

Operations

Ticket Routing

Identify, extract, route, or close tickets automatically.

People

Candidate Screening

Screen resumes, handle initial outreach, and schedule interviews so HR can focus on better decisions.

Supply Chain

Inventory Alerts

Watch stock, replenishment, and reconciliation anomalies.

Custom

More · Built for You

If it repeats and follows a pattern, start with a diagnostic.

Three Real-World AI Agents in Action

See what each agent handles, when people take over, and the measurable impact.

Retail · Support Agent

  • Before:Slow replies and missed follow-ups.
  • Delivered:WeChat and store systems answer routine questions automatically.
  • Boundary:Pricing and escalated complaints go to staff.
ResultAround 70% of routine inquiries handled automatically

Education · Lead Agent

  • Before:High lead volume caused slow, missed follow-ups.
  • Delivered:Automated lead scoring, outreach, follow-ups, and alerts.
  • Boundary:Advisors handle pricing and final enrollment.
ResultAbout 2 hours saved per day

Services · Reporting Agent

  • Before:Weekly reports took one person-day to prepare.
  • Delivered:Automated data collection, cleanup, reporting, and delivery.
  • Boundary:People review anomalies and make decisions.
ResultWeekly reporting reduced from 8 hours to 1 hour

What We Say Up Front

Estimates are not promises. These rules keep every delivery honest.

  1. ROI Is an Estimate

    Savings come from your inputs. We show the assumptions and never guarantee returns.

  2. We Mark AI’s Limits

    Some steps still need people. We define those boundaries before anything breaks.

  3. No Inflated Automation

    No ‘fully automated’ claims. We state what AI handles and where people step in.

  4. Prove Before Scaling

    Start with the smallest real path. Scale only after it meets the metric.

A 30-Minute CallClarify scope, cost, and feasibility

  1. Current State

    Find the most repetitive, time-consuming step.

  2. Feasibility

    Check the Agent fit and investment.

  3. Next Step

    Decide if it is worth doing and how.

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