The right knowledge
Review the source material, permissions, and expected questions. Structure retrieval so the assistant can use relevant business information.
WORK WITH ME
AI development & integration
Give people a useful way to work with your information. I build AI assistants and integrate models into existing products, with clear limits, evaluation, and a route back to a person when needed.
Discuss your projectIs this what
you need?
- Customers repeatedly asking questions answered in your documents
- A team searching across scattered business knowledge
- An existing product that needs a carefully scoped AI feature
THE SCOPE
How I can help.
An integrated assistant
Connect the model to the product or workflow, including retrieval-augmented generation (RAG) when needed. Make the interaction understandable for its users.
Evaluation and boundaries
Test representative questions, failures, and uncertain answers. Define human handover, usage limits, and how the system will be monitored.
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Real Estate
I built a chatbot to answer common property inquiries and qualify leads outside business hours.
Read the case studyPLANNING YOUR PROJECT
A few useful answers.
What is RAG and when is it useful?
Retrieval-augmented generation retrieves relevant source information before a model answers. It can help an assistant work with your documents, but it still requires testing and does not guarantee correct answers.
Do I need to train my own model?
Often an existing model, useful source data, and a well-designed workflow are enough. We evaluate the requirement before considering fine-tuning or custom training.
Can the assistant escalate to a person?
Yes. Handover can be part of the design, especially for uncertain answers or decisions that need approval. The trigger and destination are agreed during scoping.
LET’S TALK ABOUT YOUR PROJECT
A useful place to start.
- The questions or tasks you want the AI to handle
- Representative source documents and access requirements
- An acceptable review process and examples of costly mistakes
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