Chatbot Development

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home / ai_agents / chatbot_development.ts
/** Chatbot development — conversational tools built on real LLMs, not decision trees */

Chatbot development, built on real language models.

The old "chatbot" — a rigid decision tree that breaks the moment someone phrases a question differently — isn't what we build. Modern LLM-powered chat is genuinely useful for support, lead qualification, and internal knowledge lookup, when it's scoped to what it can reliably do.

Serving Ponte Vedra, St. Johns County, Jacksonville & the North Florida / South Georgia region
What we build

Chatbots, applied.

Customer support chat

Answering common questions accurately, and knowing when to hand off to a human.

Lead qualification chat

Gathering the right information from a website visitor before a sales conversation.

Internal knowledge chat

Letting your team ask questions against your own docs instead of searching manually.

Guardrails against bad answers

Scoped to what it actually knows, with fallbacks so it doesn't confidently make things up.

Stack

Tools we pair it with

Claude APIOpenAI APIVector databasesPython
FAQ

Common questions

Will it just make things up if it doesn't know an answer?
We build with guardrails specifically to prevent this — scoping the bot to your actual data and giving it a clear path to say "I don't know" or hand off to a human, rather than guessing.
Can it access our own documentation or product data?
Yes — this is usually the point. We connect it to your actual knowledge base rather than relying on general training data.
How is this different from your AI Agents service?
A chatbot answers and converses; an agent can take action on your systems. Some projects need both — we'll help figure out which one your use case actually calls for.
$ project.start()

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