01Repeated routine questions
The same answers asked every day.
Map supported questions and prepare approved answers before expanding to edge cases.
Discuss this situationText conversations for customers and teams
Give customers or staff a clearer way to ask questions and find useful information. A custom AI chatbot starts with approved knowledge, defined conversation goals and a clear path to human help.
01Starting points
Common chatbot problems
When text conversations need clearer boundaries
Chatbots own text channels. Voice Agents own spoken conversations. Bots should not be sold as infallible.
02Visitors cannot find relevant information
Knowledge that never reaches the conversation.
A chatbot can retrieve from approved documents when scope supports it — permissions and freshness must be defined.
Discuss this situation03Lead intake misses context
Forms and chats that lose the essentials.
Lead qualification chatbots should collect agreed fields and escalate when the ask is outside scope.
Discuss this situation04Existing bot answers outside its scope
Confident answers without approved grounding.
Define supported questions, test cases and fallback when information is missing or uncertain.
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04 situations
Need spoken conversations?
See the Voice Agent page for spoken intake and handoff. Deep RAG systems are detailed under Custom AI Solutions.
02AI services
Chatbot scope
Website chat does not automatically include WhatsApp, Slack, Instagram, authenticated account data or CRM updates. Channels and tools are confirmed during scoping.
Goals, boundaries and escalation.
Decide which questions are supported and what happens when they are not.
- Supported intents
- Out-of-scope rules
- Handoff triggers
- Channel assumptions
Approved information the bot may use.
Prepare documents or content sources, update responsibilities and permission boundaries.
- Approved sources
- Update ownership
- Permission notes
- Missing-info behaviour
Interface, retrieval and integrations in scope.
Build the chatbot experience and any scoped tool calls. Taking a message differs from live queue transfer.
- Chat interface
- Retrieval when scoped
- Tool integrations in scope
- Fallback paths
Representative conversations before launch.
Test supported questions and escalation quality. Ticket reduction is not automatic proof of good support.
- Test conversation set
- Escalation checks
- Documentation
- Handover
Automation after the chat
If the bot should create tasks or update records, Business Automation owns those workflow actions.
03How we work
Chatbot process
Define questions and boundaries → prepare approved knowledge → build and test conversations → review and hand over.
What the bot should and should not answer.
Agree conversation goals, channels and escalation rules.
Define
- Goals
- Supported questions
- Handoff rules
Outcome
Clear conversation boundaries.
No “answers everything” claim
Fallback and review paths are part of a responsible chatbot scope.
04Why Buildaze
How success is assessed
Use a defined test set and escalation quality — not vanity reply counts.
Define the set before judging quality.
Measure how the bot handles the questions you agreed to support.
Ready to discuss a chatbot?
Share the channel, the top questions and who handles escalations today.
BoundariesKnowledgeTestHandoff
Not infallible by design.
05Questions
A chatbot can be designed to retrieve from approved documents where the scope supports it. Permissions, document quality and updating responsibilities need to be defined.
06Related services
07Contact
Tell us what you want AI to help with
Share who will use the solution, the task they need to complete and which systems or documents are involved. Do not send confidential credentials through the form.