AI Chatbot Development
Custom AI chatbots that do work, not just chat. Anthropic Claude or OpenAI under the hood, your domain knowledge in front.
Custom AI chatbot development at Sitio Labs starts with a single question: what is the chatbot allowed to do? We design retrieval, tool-use, and guardrails before we write a prompt. The output is a conversational interface that handles real workflows — bookings, lookups, ticket triage, internal Q&A — not a demo that breaks the moment a user goes off-script.
What we mean by AI chatbot development
A custom AI chatbot is not a button on a website that says “chat with AI.” It is a domain-trained, tool-using, evaluated assistant that takes natural language and produces specific outcomes — a booking, an answer pulled from your wiki, a refund processed against your billing system. The most common reason chatbots fail in production is that they were treated as content (write some prompts, ship the widget) instead of as software (define the contract, instrument it, evaluate it). Sitio Labs treats AI chatbot development as a software discipline.
How we build custom AI chatbots
Discovery comes first: which 3–5 user intents account for 80% of traffic, what data the bot can read, what actions it is allowed to take. Then we choose the model — Anthropic Claude for long-context reasoning, OpenAI GPT-4o for tool-use breadth, open-source Llama via Replicate when data residency requires it. We build retrieval over your knowledge base with hybrid keyword-plus-vector search and reranking. We instrument every conversation with structured logs and a per-intent eval set so you can see when the bot regresses. The chatbot ships when the eval pass-rate is above 90%, not when the demo works once.
Where AI chatbots actually pay off
High-volume, narrow-scope workflows. Internal IT helpdesks where the answer is in a Confluence page. Customer support tier-1 deflection on FAQ and account questions. Sales-qualifying bots that book a meeting after three structured questions. Booking flows where the conversation is faster than the form. Where chatbots fail: open-ended creative tasks, emotional support, anything where being slightly wrong costs more than being slightly slow. We will tell you in discovery if a chatbot is the wrong tool. We have walked away from chatbot briefs before.
Why hire Sitio Labs for AI chatbot development
Two reasons. First, our Zerocode practice ships native iOS and Android apps from a single prompt — meaning the same engineers who fine-tune your chatbot can also embed it in a real mobile product on the same engagement. Second, we are model-agnostic. Anthropic, OpenAI, Replicate, your own fine-tune — the choice is a constraint problem, not a vendor preference. We are not paid to push any single provider, and we will show you the cost-per-conversation projection before you commit.
- ·Custom AI chatbot — web, mobile, or in-app widget
- ·Retrieval-augmented generation (RAG) over your data
- ·Tool-use and function calling (calendars, CRMs, databases)
- ·Conversation logging, evals, and analytics dashboard
- ·Anthropic Claude, OpenAI GPT, or open-source model — chosen for your latency/cost/residency
- ·Hand-off to your team via Git repo + runbook
From₹5,00,000Scoped per project. Final fee in the SOW.
Timeline3–5 weeks
What changes the price- Number of artifacts in the SOW
- Speed (rush deliveries cost 25% more)
- Number of stakeholders involved
- Whether the brief is signed or still being shaped
What does an AI chatbot development engagement actually include?
Discovery, model selection, retrieval setup over your data, tool integrations (calendar, CRM, database), conversation logging, an evaluation harness, and a deployed chatbot — web widget, mobile, or in-app — handed off via Git repo. Everything you need to run the bot without us.
How much does custom AI chatbot development cost?
From ₹5,00,000 for a focused single-intent chatbot, scaling with the number of integrations and the size of your retrieval corpus. We send a fixed quote after discovery — no time-and-materials surprises.
Which AI model do you use — Claude, GPT, or something else?
It depends on the workload. Anthropic Claude for long-context document reasoning. OpenAI GPT-4o for breadth of tool-use. Open-source models via Replicate or self-hosted when data residency or cost demands it. We benchmark before we commit.
Do you handle WhatsApp, Slack, and other chat platforms?
Yes. WhatsApp Business API, Slack apps, Microsoft Teams, in-app web widgets, and SMS via Twilio. The bot logic stays in one place; the surfaces are integrations.
What if our chatbot needs to act, not just answer?
That is the default. We build with tool-use and function calling so the chatbot can read from your database, write to your CRM, trigger workflows, and confirm bookings. A chat interface that only talks is a worse FAQ page.
Discuss this engagement.
Discovery is free. We will write you a brief, even if you do not engage us.
Book a discovery call ↗