AI ASSISTANTS & CHATBOTS
AI Assistants That Help Customers and Teams Get Useful Answers Faster
Customer-facing chatbots and internal AI assistants built around your business information, workflows and escalation rules — not just a generic chat box connected to a model.
Assistants are quoted by scope. The right solution depends on who uses it, what information it can access, what actions it can take, when a human must step in and how much usage the system needs to support.
Typical Assistant Projects
- Website chatbots
- Customer support assistants
- Internal knowledge assistants
- Sales / lead assistants
- FAQ assistants
- Product guidance assistants
- Staff research helpers
- Assistants connected to business systems
Different Assistants Solve Different Problems
A useful assistant should be designed around a specific audience and job. The same chatbot pattern should not be forced onto every use case.
Customer Support Assistants
Answer common questions, surface relevant help content and route harder cases to a person.
Internal Knowledge Assistants
Help staff search, summarise and work with internal documents, policies or operational information.
Sales & Lead Assistants
Collect enquiry details, qualify basic intent and route leads into the right follow-up workflow.
Product Guidance Assistants
Help users understand products, services, plans or next steps through conversational guidance.
Where the Assistant Gets Its Information
An assistant is only as useful as the information and access around it. We define what sources it can use and what it should never expose.
Website Content
Public pages, service information, FAQs, policies or product information can provide part of the knowledge base.
Documents
PDFs, manuals, guides, policies and other controlled business documents can be used where appropriate.
Knowledge Base
Help-center content or structured internal documentation can be connected to the assistant.
Business Systems
APIs, CRM, databases or other systems may provide live information where access is appropriate.
Structured Data
Products, records, plans, statuses or other structured data can support more precise responses.
Human Guidance
Rules, escalation instructions and business context help shape how the assistant should behave.
Useful Assistants Need Clear Boundaries
Before implementation, we define what the assistant is allowed to answer, what information it can access and when it should stop guessing.
- Topics it can answer
- Sources it can use
- User or role restrictions
- Actions it can trigger
- Questions that require escalation
- Cases where it should say it does not know
- Information it must not reveal
Human Handoff Matters
A chatbot should not trap users in an endless automated loop. When the assistant cannot resolve the issue, the workflow should make it easy to hand off the conversation, collect contact details or route the request appropriately.
For internal assistants, uncertain or sensitive outputs can also require human review before downstream action.
Common AI Assistant Capabilities
The final assistant only needs the capabilities that support its real purpose. More tools and integrations are not automatically better.
Knowledge Retrieval
Find relevant information from approved sources before generating an answer.
Conversation Memory
Use appropriate session context so the assistant can follow the current conversation.
Lead Capture
Collect structured contact or enquiry details when the workflow requires it.
Human Escalation
Route unresolved or sensitive cases to email, support staff, CRM or another system.
Action Tools
Trigger approved actions such as creating a ticket, checking a status or updating a record when safely designed.
Role-Aware Access
Restrict internal information or actions according to authenticated users or roles where required.
Feedback Signals
Capture useful feedback or unresolved cases for later improvement.
Logging
Keep enough operational history to troubleshoot assistant behavior and workflow issues.
Multilingual Support
Support more than one language where the selected model, content and workflow justify it.
What We Pay Attention To
A convincing demo is not enough. The assistant needs reliable information, clear limits and a workflow that still works when the model is uncertain.
Grounded Answers
Responses should rely on approved information rather than inventing unsupported business facts.
Clear Uncertainty
The assistant should be able to say when it does not know instead of confidently fabricating.
Access Control
Private information should only be available to the right users and workflows.
Escalation Paths
Important or unresolved cases need a clear route to a human or another process.
Prompt & Tool Boundaries
Instructions and connected actions should limit what the assistant can do.
Usage Costs
Model calls, retrieval, vector storage and other services should make economic sense for the expected volume.
What Determines the AI Assistant Quote?
A simple public FAQ assistant and a private multi-system staff assistant are completely different projects. We quote the real assistant workflow and access requirements.
Knowledge Sources
The number, quality and complexity of websites, documents, databases or systems the assistant must use.
User Access
Public assistant, authenticated users, staff-only access or multiple permission levels affect scope.
Actions & Tools
Creating tickets, updating records, checking statuses or performing other actions adds workflow complexity.
Integrations
CRM, support systems, email, databases, APIs and other business tools may require custom connection work.
Conversation Volume
Expected usage affects architecture, provider costs, rate limits and operational planning.
Review & Safety Logic
Escalation, moderation, restricted topics and human review can add important implementation work.
Define the Assistant Before Building It
The written scope should clarify users, knowledge sources, allowed topics, tools/actions, escalation rules, integrations, access boundaries, expected volume and quoted cost.
Starting With a New Assistant?
We can help define the first useful assistant around one audience, one knowledge set and a clear support or workflow goal.
Already Have a Chatbot?
Existing assistants may need better retrieval, improved prompts, stronger escalation, safer access, new integrations or lower operating cost. We review what already exists before recommending changes.
A Written-First AI Assistant Workflow
Sample questions, documents, website links, screenshots, test conversations, progress updates and approvals can all be handled asynchronously in writing. Meetings are optional.
01
Define the Assistant
Explain who will use it, what questions or tasks it should handle and what success looks like.
02
Prepare Knowledge & Rules
We define approved sources, access boundaries, escalation logic and any actions or integrations.
03
Build & Connect
The assistant, retrieval layer and required integrations are implemented around the agreed scope.
04
Test Real Questions
We test normal questions, missing information, ambiguous requests, restricted topics and handoff behavior.
05
Launch & Improve
The assistant goes live, with later tuning, new sources and workflow improvements handled as new scope or support.
Provider & Data Boundaries Are Confirmed
Model provider, retrieval/storage services, API credentials, data sources, access controls, deployment and third-party costs are defined according to the project.
Assistants Need Ongoing Tuning
Business information changes, models change and real conversations reveal gaps. SiteLumo can continue improving prompts, knowledge sources, escalation rules and integrations after launch.
AI Assistant & Chatbot Questions
What is the difference between a chatbot and an AI assistant?
A chatbot is the conversational interface. An AI assistant may also retrieve business information, use tools, perform approved actions or support a broader workflow behind the conversation.
Can the assistant answer questions from my website or documents?
Yes, where the sources are suitable and approved for use. The retrieval setup depends on the content and access requirements.
Can it connect to my CRM or support system?
Potentially. CRM, helpdesk, email, databases and other systems can be connected where APIs or suitable integration methods are available.
Can it hand a conversation to a real person?
Yes. Human escalation can be part of the workflow when the assistant cannot resolve the request or the case requires a person.
Can it access private internal information?
Potentially, but authenticated access, permissions and data boundaries must be designed carefully. Private information should not be exposed through a public assistant.
Will the assistant always be correct?
No AI model can guarantee perfect answers. The system should use approved sources, clear uncertainty handling, escalation and human review where appropriate.
Which AI model will you use?
The model depends on the task, cost, availability, context requirements and privacy needs. We choose after understanding the use case rather than committing every project to one provider.
Are there ongoing AI costs?
Usually yes. Model providers, retrieval/storage services or other APIs may charge usage fees. These are separate from SiteLumo project fees.
Do we need meetings?
No. SiteLumo uses a written-first workflow. Sample questions, documents and test conversations can handle most project communication.
What should I send for a quote?
Describe who will use the assistant, what it should help with, where the information currently lives, whether it needs private access or integrations, and examples of questions it should handle.
Have an Assistant or Chatbot Use Case?
Tell us who will use it, what information it should know, what questions it should handle and whether it needs to connect to other systems. We’ll reply in writing with the next questions needed to define the scope.