Frequently Asked Questions

It quantifies AI trustworthiness using mathematical bounds from information theory—measuring how many nats (natural units of information) are required to guarantee reliability. This approach lets us make precise statements about when and why AI systems fail, rather than relying on empirical benchmarks alone.

Strawberry uses a technique called "evidence scrubbing" to measure whether a model actually uses its cited sources. It computes two probabilities:

• p₀ — the model's confidence without access to the citation
• p₁ — the model's confidence with the citation

If p₁ isn't significantly higher than p₀, the citation is flagged as "decorative" — the model is citing without actually using the evidence. The difference is quantified as a "budget gap" in bits.

Factual hallucinations occur when the model lacks the necessary knowledge — it simply doesn't know the answer.

Procedural hallucinations are different: the correct information exists in the model's hidden states, but it fails to route that information to the output. Research shows approximately 74% of hallucinations are procedural, meaning the model "knows" the right answer but fails to produce it.

This distinction matters because procedural hallucinations can be detected and prevented with the right tools, while factual hallucinations require external knowledge sources.

Strawberry is available as an MCP (Model Context Protocol) server, which means it integrates directly with:

• Claude Code — Add Strawberry to your Claude Code configuration for real-time hallucination detection
• OpenAI Codex — Use Strawberry skills in your Codex agent workflows
• Python API — Call detect_hallucination() or audit_trace_budget() directly

For enterprise deployments or custom integrations, contact us.

The budget gap measures how much information (in bits) is missing between what a claim requires and what the evidence provides. A negative budget gap (e.g., -2.1 bits) means the evidence strongly supports the claim. A positive budget gap (e.g., +8.4 bits) means the claim needs more evidence than provided — a hallucination flag.

Yes. Strawberry is released under the MIT license. For access to the source code, documentation, and examples, contact us or visit the Strawberry demo for integration guides.