Statistical validation, evaluation frameworks, and privacy-first LLM/RAG pipelines — defensible metrics for AI-driven products, from a team that's spent 15+ years doing exactly this kind of rigor for federally funded research.
Enter how two models did on the same eval items and get the accuracy gap with a confidence interval and a paired significance test. Runs in your browser.
Typical deliverables are listed below. Your proposal specifies the included outputs, available data, timeline and fee. Choose a focused project or ongoing support. See ways to work with DASS →
Our team's experience building data infrastructure for field research informs the data management needed for dependable evaluation. The example below describes that research experience; it is not an AI product benchmark.
Built and managed data infrastructure to support statistical analysis and reporting for a large intervention study.
DASS did a fantastic job. They were patient, clear about the coding, and very responsive to my emails. They took the time to understand the overall goal before proceeding with each step. Highly recommend.
It depends on the question. Accuracy's margin of error shrinks only with the square root of the number of items: near 80% accuracy, a 5-point margin takes about 246 items and a 3-point margin about 683. Showing that one model beats another usually needs several times more. See our guide, How many test items does an AI eval need?
Compare both on the same items with a paired test and look at the interval for the difference, not just the two scores. Our free model-comparison calculator does this in your browser and gives R and Python code for the same analysis.
A described test set, a scoring method checked against human judgment, failure cases reported rather than filtered out, and a stated scope. A single aggregate accuracy number with nothing behind it is the most common weakness. See what makes an AI eval defensible to auditors.
Evaluation and experimental design, a power and sample-size memo for your eval set, A/B testing for model and prompt changes, and privacy-first LLM and RAG evaluation pipelines, with analysis code you keep.
We don't publish a price list because cost depends on scope. The free 30-minute consult ends with a scoped proposal that includes methods, a timeline and a fixed quote, whether or not you hire us. If you have a deadline, such as a resubmission date, tell us on the first call so the timeline is built around it. We reply to inquiries within one business day.
A free 30-minute consult — bring your eval design or results, and we'll tell you where it holds up and where it doesn't.
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