AI chatbot development services cover everything needed to plan, build, connect and run a chatbot that understands plain language. At AngleBrackets that means picking the right use cases, designing conversations, connecting a large language model to your own content, linking it to tools like your CRM or help desk, testing it for accuracy and safety, and improving it after launch.

An AI chatbot is software that understands questions typed in normal language and replies like a person would. Unlike older menu bots, it uses a large language model to understand intent, and when built well it answers from your own business data rather than guessing.

A focused custom chatbot for one main use case usually costs $6,000 to $15,000. Advanced chatbots with several channels, actions and integrations usually cost $15,000 to $45,000. Dedicated AI chatbot developers start from $3,500 a month per engineer. That is well below the $30,000+ many agencies quote for an LLM chatbot, because we start with one use case and reuse proven building blocks. LLM usage fees are billed separately by the model provider, and we help you keep them low.

Most custom AI chatbots go live in 4 to 8 weeks. Enterprise bots with many channels, languages and system actions take about 8 to 16 weeks. A simple proof of concept on your own content can be ready in 1 to 2 weeks.

We work in four steps: discover and scope your top questions and actions, design conversations and prepare your knowledge base, build, integrate and test the bot on real questions, then launch to a small share of traffic and roll out fully. Every launch includes 2 weeks of free post-launch support.

A no-code builder is fine for a few simple FAQs on one channel. A custom AI chatbot makes sense when you need answers from large or changing content, actions in your own systems, several channels or languages, strict data privacy, or control over costs. We are happy to tell you honestly if a builder is enough for you.

ChatGPT is a great general assistant, but it doesn't know your policies, products or customers and can't act inside your systems. A custom chatbot can use the same models, such as GPT or Claude, but answers only from your content, follows your rules and connects to your tools. That's usually the better fit for customer-facing work.

Yes. We connect the chatbot to your help center, PDFs, policies, product catalog and databases using retrieval augmented generation (RAG), so it searches your content first and answers from it. When your content changes, the bot's answers change too.

We ground answers in your content, show sources, set the bot to say "I don't know" and hand off when it isn't sure, and test it on 200+ real questions before launch. After launch we review failed answers every week and fix the content or prompts behind them.

Yes. You decide when a person should take over, for example angry customers, refunds or sensitive topics. The bot passes the chat to your help desk, live chat or Slack with the full conversation, so your team doesn't ask the customer to repeat anything.

Yes. One chatbot can run on your website, inside your app, on WhatsApp Business, Facebook Messenger, Instagram, Slack and Microsoft Teams. We can also add a voice version for phone calls through our Voice AI work.

Yes. Modern language models handle many languages, including English, Arabic, Urdu, Spanish, French and German. The bot can reply in the customer's language even if your knowledge base is written in only one.

We build with privacy first: personal data is masked, conversations are stored in your chosen region, access is role-based, and your content isn't used to train public models. Our builds follow GDPR principles and are HIPAA-ready for healthcare clients when the right hosting and agreements are in place.

Yes. We regularly connect chatbots to HubSpot, Salesforce, Zendesk, Intercom, Shopify, Google Calendar, Calendly and custom APIs, so the bot can create leads, open tickets, check orders and book meetings.

You own the code, prompts, knowledge base and data. Every launch includes 2 weeks of free post-launch support to fix issues and tune answers on real conversations. After that, you can choose a monthly support and improvement plan or run it in-house.