AI chatbots
AI chatbots that resolve, not just reply.
We build AI chatbots for customer support, sales and internal help that look up orders, fix billing, book appointments and answer from your knowledge base, then hand the hard cases to your team with the context attached.
Start a projectBeyond the FAQ bot
Old chatbots matched keywords to canned answers and frustrated customers. Modern AI chatbots understand the request, check your systems, act within your policies and know when to stop. That is the difference between deflecting tickets and resolving them.
Overview
What a modern AI chatbot can do for your business
Customers expect instant, accurate answers on your website, in your app and on WhatsApp, at any hour. A modern AI chatbot built on large language models understands questions in natural language, finds the answer in your approved content, and, when connected to your systems, completes the task: tracking an order, updating an address, booking an appointment or processing a return within policy.
We design every chatbot around the conversations your team actually handles. We study past tickets and chats, automate the intents with the highest volume and clearest rules first, and design graceful handoffs for everything else. Your brand voice, compliance rules and escalation paths are built in, and the chatbot is measured on resolution rate and customer satisfaction, not just on how many conversations it deflects.
What we build
AI chatbot development services
Every chatbot is built on your content and systems, with the guardrails your brand and compliance team need.
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01
Customer support chatbots
Answer, look up and act: order status, returns, billing and account changes, resolved end to end inside policy.
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02
WhatsApp chatbots
AI assistants on the WhatsApp Business Platform for support, bookings and order updates, in English, Hindi and Gujarati.
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03
Website and lead chatbots
Qualify visitors, answer product questions from your docs and book meetings straight into your calendar and CRM.
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04
Helpdesk integrations
Chatbots inside Zendesk, Freshdesk, Intercom or your own helpdesk that draft replies and close simple tickets.
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05
Internal HR and IT assistants
Answer policy, leave and IT questions from your handbooks, and raise requests in your systems.
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06
Voice assistants
Speech-enabled assistants for inbound calls that handle routine requests and transfer with a summary.
Process
How we build your AI chatbot
Fixed fee per phase, a measured exit gate at the end of each, and working software from the first weeks. See every playbook week by week.
- 01
Discover
Review real conversations and tickets, pick the intents worth automating and agree the success metric.
Week 1
- 02
Build
Knowledge base, system integrations, policies and the conversation design, in your brand voice.
Weeks 2 to 4
- 03
Test in shadow
The chatbot drafts answers your team approves, so accuracy is proven before customers see it.
Weeks 5 to 6
- 04
Go live and improve
Staged rollout, weekly reviews of failed conversations, and continuous tuning.
Week 7 onward
Use cases
AI chatbot use cases by industry
E-commerce and D2C
Order tracking, returns, size and product questions, and abandoned-cart follow ups on WhatsApp.
SaaS
Account and billing help, how-to answers from your docs and smart escalation to the right team.
Banking and fintech
Balance and transaction queries, card controls and KYC status, with strict authentication and audit.
Healthcare
Appointment booking, report status and pre-visit instructions, with privacy built in.
Education
Admissions questions, fee payments and student support across web and WhatsApp.
Real estate
Lead qualification, site visit booking and project information around the clock.
- Connected to your systems, so the chatbot can actually do things, not only talk.
- Policies enforced in code: refunds, discounts and data access follow your rules every time.
- Clear handoff with a summary, so customers never repeat themselves to a person.
- Multilingual by design, including Hindi and Gujarati where your customers need it.
- Measured on resolution and satisfaction, reviewed weekly, improved continuously.
What we build with
Chosen for your problem, never for a partnership.
AI and data
- OpenAI
- Anthropic
- Google Gemini
- Llama and Mistral
- LangGraph
- pgvector
- Databricks
- Snowflake
Product
- TypeScript
- React
- Next.js
- React Native
- Flutter
- Python
- Go
- Node.js
- Postgres
Platform
- AWS
- Google Cloud
- Azure
- Kubernetes
- Terraform
- GitHub Actions
Questions
Frequently asked questions
Still unsure? Ask us directly, a senior engineer replies within one business day.
How is an AI chatbot project scoped and priced?
Scope depends mainly on integrations, channels and languages. A knowledge-base chatbot is the simplest; a chatbot that takes actions in your systems needs more integration and testing. We start with a short proof on your real conversations, then agree a fixed fee for each phase in writing.
Can you build an AI chatbot for WhatsApp Business?
Yes. We build on the official WhatsApp Business Platform, so your chatbot can support customers, send updates and take bookings where they already are. Our guide on building a WhatsApp AI chatbot for customer support walks through the steps.
Will the chatbot give wrong answers?
We reduce that risk by grounding answers in your approved content, refusing to guess when confidence is low, enforcing policies in code and reviewing failed conversations every week.
Can it hand over to a human agent?
Yes. When a request is outside policy or confidence is low, the chatbot creates a ticket or transfers the chat with a summary of the conversation.
Which languages are supported?
English, Hindi, Gujarati and most major languages. We test each language with real conversations before launch.
How long does it take to launch?
A focused chatbot can go live in six to eight weeks, including a shadow period where your team approves answers before customers see them.
Can the chatbot learn from our existing tickets?
Yes. We use past tickets and chats to find the most common requests, write and test answers, and build an evaluation set, while removing personal data in line with your policies.
What happens if our product or policies change?
Content updates flow into the chatbot's knowledge base without retraining, and policy rules are changed in configuration, then checked by the regression suite before going live.