Direct answer
Use this estimator to classify hallucination risk before launch and identify the cheapest mitigations that actually reduce user harm.
Business RAG writing assistant
Input: Generative writing, RAG grounding, LLM-judge guardrail, business domain risk.
Output: The output should show medium risk with mitigation recommendations around citation checks and human review.
How to use this tool
- 1. Choose task type.
- 2. Set grounding strategy and guardrails.
- 3. Choose domain risk.
- 4. Review risk band, mitigation priorities, and pre-launch test checklist.
Hallucination is a use-case property
A model is not simply safe or unsafe. Risk depends on the task, domain, grounding, user expectation, review path, and consequence of being wrong.
RAG can reduce ungrounded answers, but it does not eliminate bad retrieval, stale documents, reasoning errors, or overconfident synthesis.
Guardrails that are measurable
Human review, retrieval citation checks, constrained output schemas, eval sets, and multi-step verification can reduce risk when measured. Vague policy prompts and cosmetic filters are weaker unless tied to tests and escalation.
Assumptions and methodology
This tool uses transparent browser-side calculations and curated assumptions rather than LLM-generated recommendations. Outputs are planning estimates. They should be validated against provider pricing, production traces, engineering quotes, or domain review before money, compliance, safety, or hiring decisions are made.
Numerical defaults are dated and surfaced on the page. The methodology favours explicit assumptions over false precision: every estimate is meant to expose the variable that drives the result, not to pretend that early planning data is exact.
Turn the result into an implementation plan
Bring the scenario to a strategy call and I will pressure-test the workflow, assumptions, failure modes, and delivery path.
Book a strategy callFrequently asked questions
- What is hallucination?
- Hallucination is output that appears plausible but is unsupported, false, or inconsistent with the available evidence. In production, the risk is determined by user reliance and consequence.
- Does RAG eliminate hallucinations?
- No. RAG improves grounding but can retrieve wrong documents, miss relevant context, or let the model synthesize unsupported claims. It needs evals and citation checks.
- Do LLM judges work?
- LLM judges can help triage outputs and catch obvious failures, but they should be evaluated against human labels and not treated as proof of correctness in high-risk domains.
- What is unacceptable risk?
- Risk is unacceptable when the system can cause safety, legal, financial, medical, or rights-affecting harm without reliable review and mitigation.
- How do I test hallucinations?
- Use scenario evals, adversarial prompts, gold-answer sets, citation checks, retrieval audits, and human review of high-impact cases before launch.
- What is the cheapest useful mitigation?
- The cheapest useful mitigation is usually a scoped task, explicit refusal policy, retrieval citations, and human review for uncertain or high-impact outputs.