Answers
How do you handle LLM hallucinations?
In short
Handle LLM hallucinations with three layers: grounding (RAG against your data), structured output validation, and a human-in-the-loop for any decision that matters.
Short answer
Handle LLM hallucinations with three layers: grounding (RAG against your data), structured output validation, and a human-in-the-loop for any decision that matters.
What this actually means in practice
The combination matters more than any single defence. Ground the model in your data with RAG; validate the output against a schema; route low-confidence or high-impact outputs through human review. Track hallucination rate as a first-class metric.
The most common pitfall
Relying on prompt engineering alone — it doesn't scale.
What to do next
Define a hallucination eval set and measure against it on every change.
Frequently asked questions
Does Forth Systems help with this?
Yes — Forth Systems works with banks, payment institutions, insurers and infrastructure operators on exactly this kind of work. Engagements start with a fixed-scope assessment so you see the shape before committing.
How experienced is the team?
Engagements are staffed by named, UK-based senior engineers — not a rotating offshore pool. References from the second line of comparable clients are available on request.
Where are you based?
Edinburgh-based, delivering UK-wide with onsite presence in London and across Scotland as required.
How fast can we start?
Most engagements start within 2-4 weeks of a signed SoW, faster where an existing supplier framework is in place.