Enterprise Persian chatbots
Most questions reaching an organisation's support desk are repeats, and the answer is already written down somewhere — nobody can find it. A chatbot earns its place when it returns that written answer, not when it invents one.
Where it helps
- Answering recurring citizen or customer questions outside office hours
- An internal guide for staff on the organisation's own rules and procedures
- First-pass triage of requests before they reach a specialist
- Reducing repeat calls so specialists can concentrate on the complex cases
How it is built
- 1
Assemble the knowledge source
Documents, guides and the history of real questions. A chatbot's answer quality never exceeds the quality of this source.
- 2
Build with a clear boundary
The model answers only from the approved source and refers what it does not know to a human. That boundary is defined at the start, not after the first wrong answer.
- 3
Release gradually and monitor
Start with a narrow scope and watch the answers. Every unanswered question is added to the knowledge source, so the system improves with use.
Frequently asked questions
Where do the answers come from?
From the organisation's own knowledge: guides, regulations, FAQs and internal documents. The model retrieves text from those sources and grounds its answer in them, not in its own general memory.
What if it does not know?
It says so and refers to a human. This is the single most important design decision: a chatbot that invents something for every question loses the user's trust after a few wrong answers and gets abandoned.
What is needed to start?
A body of documents and a set of real user questions. If the organisation has ticket or call history, that is the best input, because it shows what people actually ask rather than what we assume they ask.
What platforms does it run on?
The website, and where needed internal messaging or an existing support system. The conversation layer is separate from the knowledge source, so adding a platform does not mean rebuilding.
What happens to user data?
Retention scope is decided before the build and is part of the design, not something addressed afterwards. For many uses, storing conversation text is not necessary at all.
Further reading
A chatbot for your organisation
Looking at your users' real questions shows how much load a chatbot would actually take off — and if the answer is not much, we say so.