Fixed Price on Day One
After the discovery call, we send a written proposal with a fixed price, timeline, and full scope. Nothing is billed beyond what was agreed. No scope creep charges for requirements confirmed upfront.
AI Chatbot Development Services
An AI chatbot that actually understands your customers.
We build AI chatbots powered by GPT-4 and Claude — trained on your specific products, policies, and support history. Not a template. Not a flow chart. A chatbot that reads context, remembers what was said three messages ago, and gives answers your customers actually find useful. Deployed on your website, WhatsApp, or Telegram in 2–4 weeks.
Live in 2–4 weeks · Fixed price · 50% advance — 50% on delivery
Service overview
Your current chatbot is probably doing more damage than good.
A rule-based chatbot that cannot answer a question confidently sends customers to your competitors. An AI chatbot trained properly on your business sends them to your checkout — or your calendar. The difference is not the technology. It is whether the chatbot actually knows your business well enough to be useful.
Before
What a poorly built chatbot does
Matches keywords instead of understanding intent — misses obvious questions
Gives generic answers that send customers back to the search bar
Breaks when customers ask anything outside the scripted flow
Transfers to a human agent for questions it should have handled itself
Has no memory — asks customers to repeat information already provided
After
What a well-built AI chatbot does
Understands the intent behind a question, not just the words used
Gives specific, accurate answers trained on your actual product and policies
Handles follow-up questions with full conversation context intact
Escalates to a human only when the query genuinely requires one
Operates at 2am on a Sunday with the same quality as 9am on a Monday
What you get
What every AI chatbot we build includes
A chatbot is only as good as the data it is trained on and the architecture it runs on. Here is what makes the difference between a chatbot your customers trust and one they abandon after the first message.
Trained on your business data
We build a RAG (Retrieval Augmented Generation) pipeline that connects the AI model to your specific documentation — product descriptions, FAQs, pricing, policies, support history, and any other content you provide. The chatbot answers from your data, not from general internet knowledge. When your return policy changes, you update the document — the chatbot updates automatically.
Multi-channel deployment
One chatbot, every channel your customers use. We deploy the same AI engine across your website widget, WhatsApp Business API, and Telegram — with a unified conversation memory so a customer who switches from website chat to WhatsApp does not have to start over. Each channel is optimised for its interface: concise on mobile, more detailed on desktop.
Contextual conversation memory
Most rule-based bots treat every message as a fresh query. Our AI chatbots maintain full conversation context — they remember what was asked, what was answered, and what the customer's underlying goal appears to be. This makes follow-up questions work naturally: 'What about the premium version?' gets a useful answer because the AI knows what was being discussed.
Smart human escalation
The chatbot knows when to stop. When a customer is frustrated, when a query involves a complaint, or when a question falls outside the chatbot's confidence threshold — it transfers smoothly to your team with the full conversation context. Your agent picks up exactly where the AI left off, without making the customer repeat themselves.
Conversation analytics dashboard
A private dashboard showing: total conversations, resolution rate, most common topics, escalation triggers, and unanswered questions. The unanswered questions list is particularly valuable — it shows you exactly what your customers need to know that you have not yet documented. Most of our clients use it to improve their support content, not just their chatbot.
15 days of post-launch monitoring
The first two weeks after a chatbot launches are when edge cases emerge. A customer phrases a question in a way you did not anticipate. A product update makes a previous answer inaccurate. We monitor conversation quality during the 15-day support period and tune the prompts, update the knowledge base, and fix any escalation failures — before your customers notice them.
How we work together
What's included in every AI chatbot development engagement
Every project starts with a free discovery call. We define scope, confirm a fixed price in writing, and start only when you are ready.
Milestone-Based Delivery
Your project is split into clear milestones with defined deliverables. You review and approve each stage before the next begins. 50% advance to start. 50% on final delivery. No hidden instalments.
Dedicated Communication
You get a direct WhatsApp line and weekly progress updates throughout the build. No ticketing systems. No account managers between you and the team. You always know what is being built and when.
15-Day Post-Launch Support
Every project includes 15 days of post-launch support at no extra charge. Bug fixes, integration issues, and minor adjustments within scope are handled during this window. You are not left to figure it out alone.
Get your fixed-price proposal
Free. No commitment. Sent within 24 hours.
How it works
How we build a chatbot your customers actually trust
The technical build is the easy part. The hard part is understanding your customers well enough to train the AI to answer their real questions. Our process starts there.
1
Knowledge mapping
We map your customers' questions before writing a prompt.
Before any technical work, we spend time understanding what your customers actually need to know. We review your existing FAQs, support tickets, and common enquiry patterns. We identify the 20 questions that account for 80% of your support volume. This mapping session defines what the chatbot must know, which shapes everything — from the knowledge base to the conversation flows to the escalation triggers.
2
Scope and payment
Scope confirmed. 50% advance received. Build begins.
The scope document confirms: the knowledge base content, the channels the chatbot will be deployed on, the CRM and helpdesk integrations required, and the escalation logic. You approve it in writing, pay the 50% advance, and development begins within 48 hours.
3
Build and training
System prompt architecture, RAG pipeline, channel integration.
We build the system prompt — the instructions that give the chatbot its personality, scope, and escalation rules — then build the RAG pipeline that connects it to your knowledge base. We integrate the selected channels and test every conversation flow against the mapped questions. You receive a staging environment link to interact with the chatbot before it touches any real customer.
4
Testing
We red-team it before it meets a real customer.
Before deployment, we run the chatbot through adversarial testing — asking it questions it was not trained for, trying to confuse it with ambiguous phrasing, testing every escalation trigger. We verify that it never makes up information it does not have, never pretends to be a human when asked directly, and always reaches a helpful outcome — either an answer or a smooth escalation.
5
Deployment
Live on your channels. Analytics tracking. Handed over completely.
We deploy to your website via a lightweight script tag — no page load impact. WhatsApp and Telegram bots go live through their respective APIs. The analytics dashboard is configured and shared. You pay the final 50% on confirmation that the chatbot is operating correctly. The 15-day monitoring period begins immediately — we watch for edge cases your customers find that our testing missed.
Technology stack
The technology inside your AI chatbot
We choose the AI model and infrastructure based on your use case — not the most expensive option. Here is the standard stack for most chatbot builds.
AI Models
GPT-4oClaude 3.5 SonnetGemini ProLlama 3Mistral
RAG & Retrieval
LangChainPineconeLlamaIndexWeaviateChromaSupabase pgvector
Channels
WhatsApp Business APITelegram Bot APIIntercomSlackFacebook Messenger
Integrations
HubSpotZendeskFreshdeskZoho CRMSalesforceIntercom
Frequently asked questions
What businesses ask before building an AI chatbot
Clear answers on timeline, payment, integrations, support, and delivery expectations.
A rule-based chatbot follows a decision tree. You define every possible question and every possible answer in advance. When a customer asks something that does not fit the predefined options — which happens constantly — the bot either gives a wrong answer or says it does not understand. An AI chatbot works differently. It uses a large language model to understand the intent behind a customer's question, even when the phrasing is unusual or the question is compound. It generates a response based on its training data and conversation context rather than matching against a fixed list of responses. The practical difference is significant: rule-based bots work for narrow, predictable use cases. AI chatbots work across the full breadth of real customer conversations.
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Your customers are asking questions right now.
Every unanswered question after business hours is a customer your competitor might capture.
Tell us about your business and the questions your customers ask most. We will scope the right chatbot for your use case, price it clearly, and have it live within the month. If a simpler solution fits better than an AI chatbot, we will tell you that too.
Fixed-price proposal within 24 hours · 50% advance · 50% on delivery · NDA available on request