Missed after-hours inquiries
Visitors ask questions outside business hours and leave before the team can reply.
AI customer support agents and chatbots that answer from your own knowledge base.
We build branded AI chat systems trained on your offers, FAQs, pricing logic, and sales process so customers get fast answers without waiting for a team member.
AI Chatbots & Customer Support
$300-$800 setup
Scoped, built, and documented by our founder. You get a fixed scope and price before work starts.
- Website chat widget setup
- FAQ and knowledge-base training
- Lead capture and handoff rules
- Conversation testing and refinement
What we deliver
- Custom AI chatbot setup for your site
- Knowledge base training from your services, policies, and FAQs
- Lead capture and qualification flows
- Escalation rules for sales or support teams
- Conversion-driven prompts and conversation tuning
Outcomes clients want
- Capture more inbound leads outside business hours
- Reduce repetitive support questions
- Respond faster to high-intent buyers
- Turn website traffic into conversations
Service strategy
Support and lead handling problems we help fix
AI chatbots and customer support systems help businesses answer common questions, qualify buyers, and route urgent requests without making visitors wait for a person. The goal is not to pretend every conversation should be automated. The goal is to handle routine intent quickly and bring humans in at the right moment.
A useful chatbot knows the offer, service details, target markets, booking process, contact options, and handoff rules. Axenor AI builds chatbot experiences around business outcomes: more captured leads, faster answers, better support coverage, and cleaner follow-up.
Repetitive support questions
Staff keep answering the same service, pricing, location, booking, and policy questions manually.
Weak handoff context
When a lead reaches the team, the agent does not know what the customer asked or what they need next.
Build process
How we build AI chatbots
Every ai chatbots & customer support project starts with the business outcome, then the workflow, content, tools, prompts, and handoff rules are designed around that goal.
01
1. Define chatbot goals
We decide whether the bot should qualify leads, answer FAQs, support customers, book calls, or route requests.
02
2. Build the knowledge base
We organize your services, FAQs, policies, pricing logic, contact details, and objections into clear source material.
03
3. Design conversation flows
We create prompts, guardrails, lead capture questions, and human handoff rules for real customer situations.
04
4. Test real conversations
We test common questions, edge cases, low-fit requests, and handoff triggers before launch.
Business use cases
AI chatbot use cases
Website lead capture
Ask visitors what they need, collect contact details, summarize the chat, and send the lead to the team.
Customer support triage
Answer routine questions and route sensitive, urgent, or high-value conversations to a human.
Booking and audit requests
Collect project details, preferred contact method, budget context, and timeline before a call.
Next reading
Related Axenor AI resources
These pages help connect ai chatbots & customer support with the wider automation system your business may need next.
AI chatbots for lead generation and customer support
Read the full chatbot guide for lead capture, support triage, and human handoff.
AI chatbot vs human customer service
Compare what chatbots should handle and what should stay human.
AI chatbots for e-commerce stores
See how online stores can answer product questions, route support, and improve handoff.
AI chatbots for real estate agents
See how property teams can qualify buyers, route inquiries, and improve agent handoff.
AI chatbots for dental clinics
See how clinics can capture appointment requests, answer routine FAQs, and route urgent concerns safely.
Top benefits of AI chatbots for customer support
See how chatbots improve first response, triage, handoff, and support consistency.
How to train your AI chatbot on FAQs
Prepare FAQ content, chatbot boundaries, testing flows, and handoff rules before launch.
Cost of AI chatbots
Understand what affects chatbot pricing, scope, setup, handoff, and maintenance.
AI automation consulting
Plan the chatbot journey before building flows.
AI workflow automation
Connect chatbot leads to CRM, email, forms, and internal alerts.
Work of this kind we have built
Built by our founder. Client systems stay private, so these are the builds we can show in full.
Ask Haseeb AI
LiveA live retrieval-augmented (RAG) assistant that answers questions about our founder's work from his own documents, and says so when the answer is not in them. New files are picked up from Google Drive, split into passages, embedded, and stored in a vector database; every answer is written from the passages it retrieves.
- Automatic ingestion of PDF, Markdown, and HTML files from Google Drive
- Token-based chunking (about 350 tokens, with overlap)
- OpenAI embeddings in Pinecone, LangChain retrieval, FastAPI backend
- Deployed on a VPS with Gunicorn and Nginx
Built with Python, FastAPI, OpenAI, LangChain, Pinecone
What clients said about this kind of project
Published word for word, with the platform and date.
“Haseeb built an internal AI assistant for our team using our own documentation. The main thing we wanted was reliable answers instead of the usual generic AI responses. The RAG setup is working well and he also showed us how the system was structured so we can maintain it later.”
“Haseeb did exactly what we needed. The project was an AI agent for handling customer enquiries and pulling information from our internal knowledge base. The first version needed some tweaking but he was patient with the feedback and improved the responses a lot. The workflow is now running properly.”
AI Chatbots & Customer Support: common questions
Direct answers about how this service works, what it includes, and how it is priced.
Have a different question?
Ask it directly. You get an answer from the engineer who would build your system.
How is an AI chatbot project scoped?
- Scope depends on the number of questions, service pages, lead capture fields, escalation rules, integrations, and the level of testing needed before launch.
Can you build WhatsApp-style or multilingual bot flows?
- Yes. We can structure bot flows for customer support, lead capture, booking, and qualification, with human handoff rules for anything the bot should not answer.
Will the chatbot replace our team?
- No. The best setup handles routine questions instantly, captures intent, and sends qualified or sensitive conversations to a human when needed.
Can the chatbot capture leads and notify our team?
- Yes. A chatbot can ask qualifying questions, collect contact details, summarize the conversation, and route the lead to your preferred email, CRM, or messaging process.
What should the chatbot know before launch?
- It should understand your services, common objections, contact details, target markets, booking process, human handoff rules, and the questions customers ask before they are ready to speak with the team.