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AI Development & Integration

AI Chatbots & Agents

Custom AI chatbot and agent development using your approved knowledge, with website integration, defined actions, human handoff, and response testing.

AI Chatbots & Agents

Overview

An AI chatbot can help visitors find information, explain a service, or collect the details needed for a human reply. An AI agent can also carry out a defined action through a connected system. Our AI chatbot and agent development service focuses on a specific job, the information the assistant is allowed to use, and the circumstances in which it should ask for help.

We organise approved knowledge such as service information, product documentation, support articles, and internal procedures into a usable source for answers. The assistant is designed around the questions your audience asks, including incomplete requests, ambiguous wording, and information that is missing from the source material. Referencing approved content improves relevance, but responses still need evaluation because AI can make mistakes.

Depending on the agreed scope, the assistant can sit on a website, support an internal team, or connect to an approved messaging channel. Actions such as creating an enquiry or checking a record require explicit access rules and carefully defined inputs. Higher-impact steps can require human confirmation, and conversations that need judgement can move to a person with the useful context preserved.

We test the assistant with representative questions and difficult examples before launch. The project also considers what conversation data is stored, who can review it, provider usage costs, and how the knowledge will stay current. A useful rollout starts with a manageable purpose and a review process, allowing the assistant to improve as you learn where it helps and where human support remains essential.

Why it helps

  • Help visitors find relevant answers when your team is unavailable.
  • Collect structured enquiry details before a staff member follows up.
  • Make approved information easier to search across documents and support content.
  • Give staff a clear handoff when an answer is uncertain or a request needs human judgement.

What's included

  • Conversation scope, approved knowledge sources, and an initial question library.
  • A chatbot interface for the agreed website or internal environment.
  • Knowledge retrieval and response instructions tailored to your business.
  • Scoped system actions, human handoff, and access controls where required.
  • Response evaluation, usage visibility, and a process for refreshing source content.

How we work

  1. 01 Scope: select the assistant's purpose, audience, knowledge, and allowed actions.
  2. 02 Prepare: organise source material and define escalation and data-handling rules.
  3. 03 Build and evaluate: connect the interface and test normal, ambiguous, and unsupported questions.
  4. 04 Launch and review: release to the agreed audience and use reviewed conversations to guide improvements.

Case study

Illustrative case study: a product support assistant

The challenge: A software team receives repeated setup questions, but answers are spread across several help articles.

The approach: Connect an assistant to approved setup documentation and let visitors describe the step they are struggling with. Where the documentation does not answer the question, offer a human support handoff rather than inventing instructions.

What to evaluate: Review answer accuracy against the source material, successful escalation, and whether users can complete supported tasks. Include questions about unsupported features in the test set. This is a proposed use case and does not represent measured support savings.

Technologies

LLM APIs Vector search Laravel