Code Hunterz

Chatbot and LLM Apps

We build chatbots and other LLM applications grounded in your help center, product data, or internal docs, with a path to a person.

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The problem

A widget with no sources will sound sure and be wrong. Support then spends the afternoon undoing it. The fix is not a friendlier prompt. It is approved content and a refusal policy.

We define the topics the assistant may answer, the content it may cite, and the topics that always go to a person. Staff tools and customer tools are different products and we do not blur them.

What you get

Grounded assistant

Answers drawn from a corpus you can edit, not from the open web by default.

Sources

A link or citation when showing where an answer came from helps the reader.

Handoff

A clear exit to email, a ticket, or a person for anything outside policy.

Evaluation set

Questions you care about, with the expected behavior, so later changes can be checked.

How the work runs

  1. 01

    Collect the corpus

    Help articles, policies, or product facts. Stale pages are removed before launch.

  2. 02

    Write the boundaries

    What it must not answer: pricing exceptions, legal, medical, account-specific secrets.

  3. 03

    Build the interface

    The chat or embedded assistant matches the product, including the empty and error states.

  4. 04

    Score it

    We review misses with you and adjust retrieval and copy before a wide release.

Stack

  • LLM APIs
  • Retrieval over your documents
  • Your site or app as the host
  • Analytics on unanswered questions

Who it is for

  • Support teams with a documented help center
  • Product companies adding an in-app assistant
  • Internal teams that want answers from their own wiki

Reviews

What clients say about the work

“Collaborating with Code Hunterz on our complex website development project was a seamless experience. Their developers showcased exceptional technical skills and a deep understanding of our requirements. They made a fantastic website that streamlined our operations and enhanced efficiency. We look forward to working with them again.”

John Smith

Director

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Questions

Will it know everything on our website?

Only the pages we include. Navigation chrome, outdated posts, and drafts should not be in the corpus, and we will help you exclude them.

Can it take actions, or only talk?

The first version answers. Actions such as changing an order are a separate agent project with tighter controls.

How do we update answers?

Update the source document. The assistant should follow the corpus, not a hidden prompt that drifts from your policy.

What languages?

We ship the language your content and customers actually use. We do not promise every language from one English help center.

AI Agents

Narrow agents that follow a tool list and a stop condition, with a person when the job should not continue.

AI Integration

Model-backed features added to software you already run, with your data and your permissions.

UI/UX Design

Flows, interface systems, and prototypes that engineering can build, including empty and error states.

Inquiry

Start a chatbots and llm apps project

Describe the job and the timeline. We reply to the email address you enter. You can also reach us through the contact form.