SYCTRA

一个了解贵司流程的助手,而不是从网上找来的泛泛之言。

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。

  • 答案基于贵司内容
  • 移交时附带上下文
  • 网页组件、API、WhatsApp 或内部集成

Why chatbots have a bad reputation

It is almost never the model at fault. It is what it is wired into, and what it is allowed to say.

01

It does not know your content

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.

02

It invents rather than admits

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.

03

It cannot hand over

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.

From the question to the answer, or to a human

The path is the same for an external customer and an internal colleague: only the corpus and the rights change.

01 / 05

Understanding the request

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.

What it takes on

The perimeter is decided with you, subject by subject. Anything outside it goes to a human.

Tier-1 questions

Repetitive requests — hours, procedures, status, conditions, how-to — absorbed without human involvement, with the source cited.

Product and document search

Finds the technical sheet, the contract clause, the current version of a procedure, even in a large and badly organised corpus.

Step-by-step guidance

Walks through a procedure in order, checks each step, and only moves on once the previous one is confirmed.

Querying your systems

Status of an order, ticket, case or contract, fetched live via API, with the user's rights.

Request qualification

Identifies the subject, the urgency and the relevant team, and gathers the missing information before handing over.

Multilingual

Answers in the language of the question, from a corpus that may be written in another.

Wherever your users are

One assistant, one knowledge base, several entry points. You are not maintaining five assistants.

API

Called from your existing application or software.

Widget

Embedded in your site or application, without leaving the page.

Messaging

WhatsApp and compatible messaging environments.

Platform

Dedicated interface, with team and rights management.

Business software

Embedded directly in the tool your teams already use.

Internal or external, the same engine

01 · 背景

Support handles two thousand requests a month, a large majority of them already documented questions.

02 · 我们实施的内容

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.

03 · 结果

Tier-1 requests are absorbed. The team handles the cases that deserve a human, with the file already prepared.

What we measure at pilot

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
-60 %

of tier-1 requests handled by a human, on the covered perimeter

availability, including outside your team's working hours
24/7

availability, including outside your team's working hours

of answers carrying their source, verifiable in one click
100 %

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。

现在就能看到运行的产品

这些产品已经构建完成。部分可在线访问,其余可按需演示。

在线演示

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

常见问题

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.

本方案不做什么

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.

Which questions do you answer again every week?

Thirty minutes is enough to work out which share of your support can be automated, and above all which share should not be.