Keewise
AI That Gets Service Done
A next-generation AI customer service and sales platform. It unifies a Knowledge Hub, autonomous agent execution, workflow orchestration, business tool invocation, human-in-the-loop (HITL) collaboration, omnichannel access, and security governance—evolving AI from "answering questions" to truly "completing services".
Customer service is moving from human-driven
to AI Agent-driven
Over the past decade, enterprises used AI to assist service teams. Over the next decade, AI will truly join business processes—moving from answering questions to executing tasks.
The AI Copilot Era
AI as a "fancy search box"
- Smart Q&A
- Knowledge retrieval
- FAQ bots
The AI Agent Era
AI enters enterprise workflows
- Calls business systems
- Executes real tasks
- Works with human agents and other agents
The AI Workforce Era
A digital employee system
- 24/7 autonomous task execution
- Human-AI hybrid teams
- Enterprise-grade AI labor
What enterprises truly need is not a smarter chatbot, but an AI agent that actually gets tasks done.
Traditional service operations can no longer carry today's business
These six pain points can cost enterprises more each year than their entire rep payroll.
Knowledge Scattered Everywhere
Know-how lives in wikis, spreadsheets, and group chats—3 reps give 3 different rebate policies.
Bots That Only Relay
The customer asks to change the delivery address; the bot can only say "please hold for an agent".
Rigid Flows That Stall
"Keep the order, just change the address"—the bot freezes, unable to carry context over.
Human-AI Handoff Gaps
Transfers drop and records vanish; some agents drown while others idle.
No Security Governance
Without unified guardrails, every single reply can turn into a compliance risk.
Wasted Conversation Data
QA samples only 5%; 95% of issues go unseen and business signals sink.
Same request: "I want a refund."
Two completely different outcomes
FAQ mode explains how to refund; Agent mode simply does it for you.
Traditional Bot
I want a refund- Core logic
- Vector search + ranking
- Reply style
- Returns knowledge-base text
- System calls
- Not supported
- Solves
- Information only
Keewise
I want a refund- Core logic
- Reasoning + tool orchestration
- Reply style
- Decomposes and executes tasks
- System calls
- Supported
- Solves
- Business execution · full loop
From understanding to execution—an all-in-one AI service loop
Click a module on the left to see how it works in real operations.
Across real business scenarios, see how AI gets things done
Rules change 3x a day; AI keeps pace
Inconsistent promo-rule answers used to draw 12 complaints an hour.
- Live on all channels in 30 s
- Agents and bots share one knowledge base
Cross-system tasks done in one sentence
Agents used to toggle 4 backends, averaging 8 minutes per task.
- Autonomously calls 4 business systems
- High-risk actions trigger confirmation
Three tasks handled in one sentence
Legacy IVR gets stuck; human transfers average 2 min 30 s on hold.
- Parses refund / address change / reshipment at once
- Natural TTS replies—no human needed
24 hours ahead of the complaint
Legacy after-the-fact QA covers only 5% of conversations.
- Alerts when "slow claims" talk spikes 312%
- Auto-locates the eastern China region and dispatches ops
The above is an illustrative scenario with anonymized client data; actual metrics are subject to acceptance testing.
Sales-driven service: not just done, but done right
Same platform capabilities, one different goal — from "fast answers, tasks done" to "spot-on recommendations and higher conversion".
"$70 gift for my mom — which one?"
A human assistant handles one customer at a time; at peak hours most inquiries go unanswered.
- Understands budget, purpose and preferences — recommends 2–3 fits
- Explains bundles and offers automatically; one click to add to cart
Catch the ones asking price and stock
High-intent inquiries hide among casual ones; slow human triage loses them.
- Auto-detects price / lead-time / stock questions as buying signals
- Auto-sends coupons or places the order; instant handoff to sales when needed
When the exchange is done, suggest the refill
After-sales is when customers are most open to suggestions—yet agents have no bandwidth for the second sale.
- At exchange / reshipment close, auto-recommends refills, accessories, trade-ins
- Proactive replenishment reminders turn service moments into sales moments
The above is an illustrative scenario; actual results are subject to business acceptance testing.
After go-live, here's what changes
Not abstract "efficiency gains", but measurable jumps in core metrics that business owners can verify.
AI Resolution Rate
Share of tasks AI fully completesAvg. First Response Time
The wait effectively disappearsHuman Agent Productivity
Equal to +30% headcountNew-Hire Ramp-Up Time
Training costs drop sharplyOverall Customer Satisfaction
Standardized yet personalService QA Coverage
From 5% sampling to real-time 100%Not a projection model: the real outcome of an 800-rep team
A fully deployed, live customer result, converted at a fully-loaded cost of $7,000 per rep per year.
Rep Headcount Optimization
Real running result — AI takes over standardized work
Annual Cost per Rep
Industry blended-cost basis
Reps Freed Up
People shift to high-value work: complex disputes, key relationships
AI Resolution Rate
Standardized inquiries and transactions handled by AI
500+ reps freed × $7,000 fully-loaded annual cost; people moved to complex disputes and key-account work.
A real customer deployment result; actual outcomes vary with team size and business mix.
More than delivering a system—
outcome guarantees written into the contract
Lightweight Start · SaaS
Deep Customization · Private Deployment
Go-Live Guarantees · In the Contract
Start with a 2-week POC,
turn fear into ROI
A 30-minute 1-on-1 solution demo to see how WuCiYuan brings AI workers safely into your workflows. Every step is verifiable, pausable, and reversible.
