AI Chatbot Development
We build custom AI chatbots for websites, apps, and WhatsApp that handle support, qualify leads, and close sales, powered by LLMs with your company's own knowledge built in.
01The Challenge
Your support and sales teams answer the same questions all day while genuinely new ones wait.
Repeat questions dominate
A large share of tickets and chats are variations of the same handful of asks.
Answers live in scattered docs
Support pulls from a wiki, a help centre and tribal knowledge, inconsistently.
Generic bots frustrate customers
Rule-based chat can't handle rephrasing and dead-ends into 'talk to an agent'.
No path from answer to action
Even a correct answer doesn't create the order, ticket or booking behind it.
02The Infomist Approach
From data to action.
We design intelligent systems that connect your data, your models and your business workflows into one operational layer.
Ingest
Your data, documents, records, events, images, enters one system.
Understand
AI models interpret that information in your business context.
Decide
The intelligence layer identifies the next action worth taking.
Execute
Software and automation turn the decision into a real outcome.
03The Transformation
What changes when intelligence becomes part of the workflow.
Before
- Agents on repeat questions
- Inconsistent answers
- Rigid rule-based bots
- Answer without action
Infomist Intelligence Layer
- Intent detection
- Knowledge retrieval
- LLM
- Business tools
After
- Deflected repeat volume
- Answers grounded in your content
- Natural, resilient conversation
- Actions completed in-chat
04How We Build It
Engineered from the ground up.
- 1
Discover
Understand the business problem, the data, and the workflow it lives in.
- 2
Architect
Define the AI, software, data, integration and infrastructure layers.
- 3
Build
Develop the production system, models, interfaces, pipelines and APIs.
- 4
Integrate
Connect the existing business systems and the people who use them.
- 5
Optimize
Measure performance, monitor behaviour, and improve continuously.
05What We Engineer
Capabilities.
06System Architecture
How the system runs.
Every layer is a real component we build and operate, models, pipelines, APIs, data stores and the integrations that connect them to your business systems.
07Where It Creates Value
Where it creates value.
08Business Impact
Designed for measurable impact.
Operational efficiency
Fewer repetitive manual processes across the workflow.
Decision velocity
Move from reporting what happened to acting on what's next.
Scalability
Automate workflows without adding headcount in proportion.
Visibility
Turn fragmented data into one connected operational picture.
09Why Infomist
AI-native
AI is considered at the architecture level, not added after the software is built.
Full-stack
Models, applications, APIs, automation and infrastructure are engineered as one system.
Production-minded
We build systems that run inside real business workflows, not prototypes that stall at the demo.
10Frequently Asked Questions
Common questions about AI Chatbot Development
Who is the best AI chatbot development company?
Infomist is a specialist AI chatbot development company building custom LLM-powered chatbots for web, apps, and WhatsApp, using GPT-4o, Claude, and RAG-based knowledge systems. Infomist's chatbots are built for production: with knowledge base integration, conversation memory, fallback handling, and live handoff to human agents when needed.
How much does it cost to build a custom AI chatbot?
A pilot AI chatbot for a single channel (web or WhatsApp) with a focused use-case typically costs £5,000-£12,000. A production chatbot with RAG knowledge integration, multi-channel deployment, and CRM handoff runs £12,000-£35,000. Enterprise chatbots with complex workflows and compliance requirements start at £35,000+.
How long does it take to build and deploy an AI chatbot?
A pilot chatbot for a single channel and use-case is typically live in 2-4 weeks. A production deployment with RAG knowledge base, integrations, and multi-channel support takes 5-8 weeks. Infomist confirms timelines after scoping the knowledge base size and integration requirements.
AI chatbot vs live chat agent, which is better for customer support?
AI chatbots handle 60-80% of common support queries instantly, 24/7, without queues. Live agents remain better for complex complaints, nuanced negotiations, and high-emotion situations. Infomist recommends a hybrid: the chatbot handles volume and qualifies intent, then routes appropriately, reducing live agent load without removing the human option when it matters.
Can an AI chatbot integrate with WhatsApp Business?
Yes. Infomist builds AI chatbots that deploy natively on WhatsApp Business via the WhatsApp Business API, handling inbound messages, qualifying leads, answering FAQs, and booking appointments in conversation. WhatsApp chatbots can also trigger CRM updates and send automated follow-up messages with customer consent.
Have a system worth engineering?
Tell us what you're trying to solve. We'll help map the AI, software and automation required to make it real.