AI Chatbot and LLM Integration
Adding AI to a product is easy to demo and hard to make dependable. I build LLM-powered features and chatbots that answer from your own documents, with retrieval, prompts and guardrails designed so the answers stay accurate and useful.
I work on the whole feature, not just the model call: the data pipeline, the interface, the API, and the fallbacks for when the model is wrong or unavailable. I have built AI assistants and chatbots into SaaS products used for customer messaging.
Scope
What is included
Everything below is handled by one person, so nothing gets lost between teams.
- 01
Chatbots that answer from your documents, help centre or database (RAG)
- 02
AI features inside your existing web app
- 03
Prompt design, retrieval tuning and answer evaluation
- 04
Guardrails, fallbacks and human handover
- 05
Workflow automation and AI agents that call your tools
- 06
Cost and latency control, with usage logging
- 07
Integration with WhatsApp, websites and internal tools
Specialisations
Choose a focus
Dedicated pages for the most common ai chatbot & llm integration projects.
Fit
Who this is for
If one of these sounds like you, we will probably work well together.
- 1
Businesses that want a support chatbot grounded in their own content
- 2
Product teams adding an AI assistant or summarisation feature
- 3
Operations teams automating repetitive, text-heavy work
Process
How a project runs
- 01
Brief
We talk through your goals, audience and scope so we both know what success looks like.
- 02
Proposal
You get a clear scope, timeline and price before any work starts. No surprises later.
- 03
Build
I build in short cycles and share working previews, so you can steer as it takes shape.
- 04
Launch & Support
I deploy, test on real devices, and stay available after launch for fixes and improvements.
Reviews
What clients say
Had a great experience with their web development services. They understood my requirements perfectly and delivered exactly what I needed. Highly recommended!
Cindy CurtisGoogle review Really liked working with them. Easy to communicate with, understood what I needed, and did a great job with the management system. Highly recommended!
Saba NaazGoogle review Great team to work with. Recommended!
Varun MandalGoogle review
FAQ
Frequently asked questions
Common questions about ai chatbot & llm integration.
RAG stands for retrieval-augmented generation. The chatbot first searches your own documents for relevant passages and then uses them to write the answer. This keeps replies grounded in your content instead of the model guessing.
No system is perfect, but a well-built one reduces it a lot. I limit answers to retrieved content, add instructions for when it does not know, and set up evaluation so you can see how it performs.
I design the integration so only the data needed is sent to the model provider, and I choose settings and providers that fit your privacy requirements. We cover this in the brief before building.
A focused chatbot over your documents can often be working in 2 to 4 weeks. Larger systems with several data sources and agents take longer.
Have a project in mind?
Tell me what you want to build. I reply with questions, a rough timeline and the next steps.
Replies within 1 to 2 business days.
Keep exploring
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