AI Chatbot Development & Knowledge Assistants

Turn Conversations Into Better Experiences.

Custom AI chatbots that understand questions, retrieve relevant information, and deliver helpful, context-aware responses — aligned with your business, brand, and knowledge.

I design and build AI chatbots tailored to specific business needs, from customer-facing assistants that help people explore products to knowledge assistants that make specialized information easier to access.

By combining conversational AI, structured knowledge, and carefully designed instructions, I create experiences that go beyond generic, one-size-fits-all chatbots.

The goal is to make information easier to access, conversations more useful, and digital experiences more engaging.

More Than a Chat Window

A useful AI chatbot does more than generate text. It understands what users are asking, draws on relevant information, and helps them find the answers or guidance they need.

Whether it supports customers, helps visitors discover products, or provides access to specialized knowledge, a well-designed chatbot should serve a clear purpose and deliver meaningful value.

Every solution starts with understanding the use case, the people who will use it, and the information the chatbot needs to provide relevant responses.

What I Build

AI Customer & Product Assistants

Help visitors discover products, explore options, and get personalized guidance through natural conversations.

AI-powered assistants can answer product questions, explain available options, and guide customers through their decision-making process using relevant product information and brand knowledge.

Examples
Product discovery and recommendationsCustomer FAQs and product questionsBrand-specific conversational experiencesShopping assistance across web chat and messaging channels

AI Knowledge Assistants

Make complex or specialized information easier to search, understand, and navigate.

Knowledge assistants can connect to approved information sources and retrieve relevant content to help users find answers without manually searching through large collections of documents.

Using retrieval-augmented generation (RAG), the system can retrieve relevant information before generating a response, helping ground answers in the available knowledge.

Examples
Internal documentation and company knowledgeProfessional guidelines and specialist resourcesTechnical documentation and knowledge basesDomain-specific information retrieval

Multichannel Conversational AI

Bring AI-powered conversations to the channels where your customers already interact with your business.

Depending on the use case, a chatbot can be integrated into a website, WhatsApp, or other supported messaging platforms, creating a more consistent conversational experience across channels.

Examples
Website chat assistantsWhatsApp AI assistantsConnected messaging experiencesChannel-specific conversational workflows

How I Build Useful AI Chatbots

01
Knowledge & Retrieval

Connect the chatbot to relevant business content, product information, documentation, or specialist resources. Where appropriate, retrieval-augmented generation (RAG) allows it to retrieve relevant information from a knowledge base before generating a response.

02
Context-Aware Conversations

Design conversational logic that considers the current question and relevant conversation history, helping the chatbot maintain continuity across follow-up questions and provide more relevant responses.

03
Instructions & Guardrails

Define the chatbot's role, scope, tone, and response boundaries. Carefully designed instructions and testing help keep conversations focused and encourage appropriate handling of unsupported or off-topic requests.

04
Integrations & Access Control

Connect the chatbot to the necessary platforms and data sources. Where information is restricted, access permissions must be enforced so users can retrieve only the content they are authorized to see.

05
Testing & Refinement

Test realistic conversations, follow-up questions, edge cases, and situations where the chatbot should ask for clarification or hand the conversation to a human.

The objective is to create a chatbot that is not only useful in ideal scenarios but also better equipped to handle real-world interactions.

How an AI Chatbot Works

1
Understand the Question

A user asks a question in natural language. The chatbot interprets the request and identifies the information or assistance needed.

2
Retrieve Relevant Knowledge

When necessary, the system searches connected knowledge sources to find information relevant to the question.

3
Generate a Response

The AI uses the question and relevant context to formulate a response that fits the chatbot's purpose and instructions.

4
Respond or Escalate

The chatbot provides an answer, asks for clarification, or directs the user to human support when appropriate.

The result is a conversational experience designed around useful information, clear boundaries, and the needs of its users.

Technology & Capabilities

The Right Technology for the Right Use Case

Every chatbot has different requirements. The technology and architecture depend on the information involved, the expected conversations, and the systems that need to be connected. Depending on the project, the implementation may include:

Large Language Models (LLMs)

For natural-language understanding and response generation.

Retrieval-Augmented Generation (RAG)

For answering questions using relevant external knowledge.

Vector Databases & Semantic Search

For retrieving relevant information from larger collections of content.

APIs & Webhooks

For connecting the chatbot to other applications and services.

Workflow Orchestration

For managing conversational steps, integrations, and supporting processes.

Messaging Integrations

For deploying conversational experiences across supported channels.

Security & Testing

For defining boundaries, protecting restricted information, and validating response quality.

Not every chatbot requires a complex architecture. I focus on selecting the appropriate tools and building a solution around the actual problem.

Selected Projects

Digital Esther

Digital Esther

AI Fashion Assistant

A conversational AI fashion assistant developed for Esther Perbandt, bringing brand and product discovery to web chat and WhatsApp.

The project combined conversational AI, product knowledge, messaging integration, and workflow orchestration to create a digital brand experience available across multiple channels.

Focus areas
Conversational AIProduct discoveryWhatsApp integrationWorkflow orchestration
DGI

DGI

AI Knowledge Assistant

A domain-specific AI knowledge assistant designed to help authorized dental and implantology professionals access relevant medical and dental guidelines.

The solution uses a knowledge-retrieval approach to make specialized information easier to find through a conversational interface, with access restricted to authorized users.

Focus areas
Retrieval-augmented generationKnowledge retrievalDomain-specific informationAccess control

My Approach: Practical AI, Built Around Your Needs

I believe a useful AI chatbot starts with a clear purpose, reliable information, and a thoughtful user experience.

My approach begins with understanding the problem the chatbot should solve, the people who will use it, and the knowledge or systems it needs to access.

From there, I design and implement the conversational experience, connect the necessary data sources and integrations, and test how it behaves across realistic scenarios.

The goal is not simply to add AI to a website. It is to build a conversational tool that makes information more accessible and interactions more useful.

Let's Build a Chatbot That Knows Your Business.

Have a knowledge base to make more accessible, a customer experience to improve, or an idea for a conversational AI assistant?

Let's explore how a custom AI chatbot could support your business and create a more useful experience for your users.

Schedule a Chat