AI and data · Chatbots
AI chatbot development company for assistants that answer correctly and know when to hand off
We build customer support, sales and internal chatbots on GPT, Claude and Gemini, grounded in your own content and connected to your helpdesk, CRM and product, so they resolve real questions instead of repeating the FAQ.
Short answer
A modern AI chatbot combines a large language model with retrieval over your documents and connections to your systems, so it can answer specific questions and complete simple tasks. Innovation Insight builds custom AI chatbots from $10k for a website support bot over four weeks to $60k for a multi-channel assistant with account actions, helpdesk handoff and analytics, with monthly model costs estimated up front.
Reviewed by Zain Khalid Malik, CTO & Co-founder · Updated
Chatbots worth building in 2026
The scripted chatbots of a few years ago followed decision trees and frustrated users the moment a question fell outside the script. Chatbots built on large language models understand free text, but on their own they invent answers. The ones that work in production combine three things: a capable model, retrieval over your approved content so answers are grounded and cited, and tools that let the bot look up an order, book a slot or open a ticket. We build all three, and we design the moment the bot hands over to a person as carefully as the conversation itself.
What we build
| Chatbot type | What it does | Typical integrations |
|---|---|---|
| Customer support bot | Answers product, billing and policy questions, checks order or account status, escalates with context | Zendesk, Intercom, Freshdesk, HubSpot, Shopify |
| Sales and lead qualification bot | Answers pre-sales questions, qualifies visitors, books meetings | HubSpot, Salesforce, Calendly, your pricing data |
| Internal knowledge assistant | Answers HR, IT and policy questions from wikis and documents, respects permissions | Confluence, Notion, Google Drive, SharePoint, Slack |
| In-product assistant | Helps users navigate and use your SaaS, explains their own data | Your application API, analytics, docs |
| Voice and messaging bots | The same assistant on WhatsApp, SMS or phone | Twilio, WhatsApp Business API, speech-to-text |
How we make it answer correctly
- Retrieval over approved content: help centre, docs, policies and past tickets, refreshed automatically, with citations shown to the user.
- An evaluation set of real customer questions, built in the first sprint and run on every change, so accuracy is measured rather than hoped for.
- Clear refusal and handoff rules: when the bot is unsure, when the customer is upset, or when the request is sensitive, it passes the full conversation to a person.
- Guardrails against prompt injection, off-topic use and sharing personal data, tested with adversarial prompts before launch.
- Analytics on containment rate, handoff reasons, unanswered questions and cost per conversation, reviewed monthly to close content gaps.
Choosing the model
We are model-agnostic and choose per use case. GPT and Claude models lead on reasoning and tone for customer-facing bots. Smaller, cheaper models handle classification and routing. Open models such as Llama or Mistral can run inside your own cloud when data must not leave it. Most production bots use two or three models together, with the expensive model reserved for hard questions, which keeps monthly costs predictable.
What it costs
| Scope | What is included | Build cost | Timeline |
|---|---|---|---|
| Website support bot | One content source, citations, handoff to email or helpdesk, basic analytics | $10k to $18k | 4 to 6 weeks |
| Support bot with account actions | Helpdesk and CRM integration, order and account lookups, authentication, evaluation set | $18k to $35k | 6 to 10 weeks |
| Multi-channel assistant | Web, WhatsApp or voice, several systems, multilingual, admin console, full analytics | $35k to $60k | 10 to 14 weeks |
Running costs are mostly model fees. A support bot handling a few thousand conversations a month usually costs tens to low hundreds of dollars in model usage. We give you a monthly estimate with the proposal and build caching and model routing in so costs stay flat as volume grows.
Delivery process
- Discovery (1 week): collect 100 or more real questions from tickets and chats, agree what the bot may and may not do, pick channels.
- Content and retrieval (sprint 1): connect sources, measure whether the right passages come back for real questions.
- Conversation and tools (sprint 2): prompts, tone, account actions, handoff, guardrails.
- Pilot (2 to 4 weeks): launch to a share of traffic or one channel, review transcripts daily, tune.
- Scale and improve: full rollout, monthly reviews of unanswered questions, cost and satisfaction.
Related work
We built Chat Your History, an AI personal historian that interviews people by chat, SMS and phone and turns the conversations into memoir chapters with GPT-4, and Treasure Island AI, a mobile consultation app that guides founders through a structured innovation method with AI brainstorming. Both are in our case studies, alongside retrieval work for contract analysis and document processing.
Sources and further reading
Next step
Tell us what you're building and get a written estimate.
A senior engineer replies within one business day. NDA on request.
Products we've shipped, and what happened next.
Case studies written from the technical documentation of each project: the stack, the scale and the outcome.
Questions we get asked a lot.
Will the chatbot make things up?
It is designed not to. Answers are grounded in your approved content with citations, the bot refuses or hands off when retrieval confidence is low, and an evaluation set measures accuracy on every change.
Can it take actions, not just answer questions?
Yes. With authentication it can check order status, update account details, book appointments or open tickets, using the same permissions your support agents have.
Does it work with our helpdesk?
We integrate with Zendesk, Intercom, Freshdesk, HubSpot and Salesforce, and can build custom handoff to any system with an API. The human agent sees the full conversation.
Can it speak languages other than English?
Yes. Current models handle most major languages well. We test answer quality in each language you need and can keep the source content in English.
Where is our data processed?
You choose: managed APIs with zero-retention agreements, models hosted in your Azure or AWS account, or open models in your own VPC. We document the data flow for your privacy review.
How quickly can we launch?
A website support bot is usually live for a pilot group in four weeks. Bots with account actions and multiple channels take six to fourteen weeks.