WhatsApp Pilot
一天之内,让 WhatsApp 助手接上你的数据。
回应客户、判定需求、触发你的自动化流程,该转人工时就转人工。就在你客户已经在用的那个渠道上。
在线试用它依据贵司文档回答客户与团队的问题,引导用户走完流程,对请求进行分流,并在应当移交时交给人工——上下文已经整理好。
It is almost never the model at fault. It is what it is wired into, and what it is allowed to say.
Wired into a twenty-line FAQ written two years ago, it answers beside the point by the third question. The user then hunts for the “talk to a human” link, and support has gained a ticket rather than avoided one.
With no explicit rule for what to do when it does not know, an assistant produces a plausible, wrong answer. Once is enough for the team to lose confidence and switch it off.
When it escalates, it forwards the raw conversation. The human agent starts again from scratch, and the assistant has lengthened the delay instead of shortening it.
The path is the same for an external customer and an internal colleague: only the corpus and the rights change.
The assistant identifies the real intent behind the wording, detects the language, and recognises the cases that must go straight to a human — complaints, emergencies, sensitive subjects — without attempting an answer.
It queries your documentation, procedures, product catalogue and, where needed, your systems via API: the status of an order, a case, a contract. The search respects the rights of the person asking.
If the information exists, it answers and cites its source. If it does not, it says so — that is a rule defined with you, not a configuration accident. A traceable “I don't know” beats an invented answer.
On requests that call for an action, it asks the missing questions one at a time, checks what it receives, and walks through the official procedure in the order it must be followed.
When a human takes over, the assistant hands across a case file: the request restated, what it verified, the relevant documents and what remains to be decided. The human picks up where the assistant stopped.
The perimeter is decided with you, subject by subject. Anything outside it goes to a human.
Repetitive requests — hours, procedures, status, conditions, how-to — absorbed without human involvement, with the source cited.
Finds the technical sheet, the contract clause, the current version of a procedure, even in a large and badly organised corpus.
Walks through a procedure in order, checks each step, and only moves on once the previous one is confirmed.
Status of an order, ticket, case or contract, fetched live via API, with the user's rights.
Identifies the subject, the urgency and the relevant team, and gathers the missing information before handing over.
Answers in the language of the question, from a corpus that may be written in another.
One assistant, one knowledge base, several entry points. You are not maintaining five assistants.
Called from your existing application or software.
Embedded in your site or application, without leaving the page.
WhatsApp and compatible messaging environments.
Dedicated interface, with team and rights management.
Embedded directly in the tool your teams already use.
Support handles two thousand requests a month, a large majority of them already documented questions.
An assistant wired into the knowledge base and the order-tracking API, as a widget on the site and on WhatsApp, with informed escalation to the team.
Tier-1 requests are absorbed. The team handles the cases that deserve a human, with the file already prepared.
HR and IT questions arrive by email, chat and in person. The same answers get rewritten every week.
An assistant wired into internal procedures, the collective agreement and the IT knowledge base, with isolation by department: an employee only sees what concerns them.
Recurring questions get an immediate, sourced answer, available outside office hours.
Website visitors ask precise technical questions the contact form does not answer.
An assistant wired into the product documentation, able to qualify the need and then offer a meeting once the request is mature.
Technical questions get an immediate answer, and the sales rep receives an already-qualified contact.
Set at scoping, measured on your real conversations, not on a hand-picked test set.
of tier-1 requests handled by a human, on the covered perimeter
availability, including outside your team's working hours
of answers carrying their source, verifiable in one click
这些量级来自我们在可比范围内于试点阶段的实测。在贵司语料上,它们会在规模化之前实测,而不是事先承诺。
这些产品已经构建完成。部分可在线访问,其余可按需演示。
一天之内,让 WhatsApp 助手接上你的数据。
回应客户、判定需求、触发你的自动化流程,该转人工时就转人工。就在你客户已经在用的那个渠道上。
在线试用Your content: documentation, procedures, catalogue, contracts, and where needed your systems via API. Nothing else. It does not answer from general knowledge about your sector.
The cases where it must say “I don't know” are defined with you, subject by subject. Every answer cites its source. And the error rate is measured at pilot on your real conversations.
It inherits the rights of the person asking. An external customer sees only the public corpus; an employee, what their role allows. The isolation is your systems', not a layer bolted on beside them.
It answers in the language of the question, even if your documentation is written in another. That matters when a French corpus has to serve English- or Arabic-speaking users.
The assistant passes the request restated, what it verified, the relevant documents and what remains to be decided. That is the difference between a useful assistant and one more filter.
It depends mostly on the state of your documentation. On a clean corpus and a well-defined perimeter, the pilot runs within weeks. On a scattered corpus, the cleanup is the real project.
An assistant will not compensate for missing or wrong documentation. If your procedures are written down nowhere, there is nothing to query — we then start by building the document layer, and we say so at scoping. Nor do we configure an assistant to handle complaints, disputes or sensitive subjects: those conversations go to a human, by explicit rule.
Thirty minutes is enough to work out which share of your support can be automated, and above all which share should not be.