AI chatbot · Customer service · Internal knowledge search
Customers have questions.
Your knowledge helps answer them.
We build AI chatbots using approved company information. They can answer common questions and gather the details your team needs. They pass complex cases and questions they cannot answer to your team.
What the workflow can look like
A question comes in.
The right next step.
01
Understand the question and context
02
Use an approved source
03
Offer an answer or a handover
Example workflow · Scope agreed with you
Understand the problem. Design a solution that fits.
Repeated questions take time. Unclear answers undermine trust.
A chatbot should make support easier to reach. We focus on questions it can answer from reliable information and give people an easy way to reach your team.
Make knowledge easier to use
Organize service information, instructions and approved documents. We agree which sources to use, how to update them and who owns the content.
Qualify enquiries
Ask a few relevant questions to understand the request. Send the agreed information to a form, CRM or ticketing system.
Customer support and internal help
Help customers with common questions or make internal information easier for staff to find. Permissions separate public and internal content.
Defined in advance
Good answers start with up-to-date information.
Before launch, we test common questions, conflicting sources and cases where the bot has no reliable answer. It should flag uncertainty and direct people to the agreed contact channel. We plan approvals, data access and ongoing costs.
Example workflow
See what this changes in practice.
A customer asks about a step in a product manual. The assistant finds the approved passage and links to the source. If the passage does not answer the question, support takes over with the conversation context. This is an example workflow.
Working with Dreamseven
From the first conversation
to a result you can verify.
01
Collect common questions
Review common requests and existing information.
02
Organize the knowledge base
Define the sources, roles and ownership.
03
Test the answers
Test common questions and cases beyond the chatbot’s knowledge.
04
Launch and improve
Review feedback and keep content current.
Good to know
Your questions.
Clear answers.
Suitable next steps
Can the chatbot make things up?
AI can give incorrect answers. We limit which sources it uses, test common failure cases and plan how to hand questions to your team. These steps reduce the risk, and some risk remains.
Can you integrate the chatbot into an existing website?
In many cases, yes. We review integration, design, data flows and your website’s technical requirements.
Can the chatbot access customer data?
Only with suitable authentication, approved interfaces and clearly defined permissions. Internal customer data stays restricted unless you explicitly grant access.
Can the team take over a conversation?
We design the handover around your support process. Depending on your systems, that could mean creating a ticket, arranging a callback or handing over to live chat.
Who keeps the knowledge base up to date?
We agree who is responsible during the project. Your team can maintain approved sources. We can also help with ongoing quality checks and improvements.
A clear next step
Discuss your chatbot use case.
Tell us your goal and where things stand. We will agree the scope, the access we need and the next steps.