Your AI change passed eval and shipped last week.Are your customers actually getting better answers - or did you just hope?
Most evaluation tools score one dimension on synthetic prompts. The failures your customers actually see - wrong numbers, drifting context, hallucinated citations - slip through because they don't show up until the response is in the wild.
variA/Bly is the deterministic evaluation layer for production AI. 40+ scored dimensions, claim-level grounding, hallucination detection - same input, same score, every run. Experimentation built on top, so when you ship a change, you know whether it actually improved the system.
1,000 free credits.
Catch hallucinations, verify grounding, defend every claim with an auditable trail - powered by deterministic scoring across 40+ dimensions.
What teams measure with variA/Bly
Your eval said 91%. The hallucination still reached the customer.
Most teams score AI responses with shallow metrics - fluency, relevance, a thumbs up from an LLM judge. The score lands at 91%. The ungrounded answer still ships.
Why? Because standard eval never sees the retrieved chunks from your RAG pipeline. It never checks whether claims exist in source documents. It never tracks whether turn 5 contradicts turn 2 across multi-turn interactions.
The result? Two variants both score 91%. You ship one and hope. That's not evaluation - that's a coin flip dressed up as a metric.
Shallow evaluation makes every deployment a gamble.
6× cleaner on the failure mode that produces compliance breaches.
We benchmarked variA/Bly head-to-head against RAGAS on the public RGB dataset. Same 592 question + answer + reference tuples, both scorers, scripts open-sourced. Here's the failure rate that matters.
When variA/Bly says “grounded”, it's right 9 out of 10 times. Built for regulated, customer-facing AI.
The LLM judge defaults to “probably verifiable” on keyword overlap — even when the passage doesn't actually support the claim.
Methodology · 12-phase journey · reproduction scripts · downloadable PDFs
Everything you need to actually know which variant won.
Deep evaluation, statistical A/B testing, and the audit trail to prove what shipped. Built for teams whose AI customers deserve more than gut-feel decisions.
Prompt Registry
Version prompts and configurations with clear history, rollback, and deployment tracking.
Golden Datasets
Define representative test cases and benchmark quality consistently.
AI Optimization
Generate improved variants based on evaluation patterns and weaknesses.
Multi-Category Evaluation
40+ metrics across 6 categories: quality, safety, grounding, semantic, coherence, advanced.
Multi-Provider
Compare providers and models without changing your experimentation workflow.
Statistical Analysis
Measure win rate, confidence, and effect size to support shipping decisions.
How AI experimentation works
Five steps to test AI changes, compare performance, and ship winners with confidence.
Define your dataset
Create representative evaluation cases that reflect real user interactions and edge cases.
Run an experiment
Test prompt, model, retrieval, or configuration variants with controlled traffic allocation.
Score responses
Evaluate outputs across 40+ dimensions in 6 categories: quality, safety, grounding, semantic, coherence, advanced.
Compare results
Measure quality, business outcomes, and statistical confidence across variants.
Deploy the winner
Roll out the highest-performing version and keep monitoring for drift over time.
The experiment engine considers:
- Your golden examples (ideal responses)
- Multi-category, 40+ dimensional evaluation scores
- Identified strengths to preserve
- Weaknesses to address
Use cases
Built for teams shipping AI in production
From customer-facing copilots to regulated decision agents, variA/Bly helps teams experiment with AI behavior where quality, trust, and outcomes matter.
Customer Support AI
Test tone, escalation logic, guardrails, and retrieval quality to improve CSAT and reduce escalations.
AI Interview & Hiring Agents
Evaluate scoring prompts, decision consistency, and candidate experience across different interview flows.
AI Knowledge Assistants
Compare retrieval strategies, prompt templates, and models to improve answer quality and reduce failure cases.
Healthcare & Clinical AI
Validate grounding against medical sources, catch hallucinations on dosage and diagnoses, and ship with auditable confidence.
Financial Services AI
A/B test advisory copilots, KYC agents, and fraud-explanation flows. Catch regressions before they hit a regulator.
Legal & Compliance AI
Compare contract-review and case-retrieval pipelines across models. Score citations and contradictions claim-by-claim.
Sales & Outbound Agents
Evaluate prospecting, personalization, and qualification logic. Ship the variant that converts, not the one that sounds good.
E-commerce & Retail AI
Test conversational shopping, search relevance, and product Q&A across catalogs and customer segments.
Internal Copilots & Ops
IT helpdesk, code copilots, document Q&A — measure quality and cost across models before rolling out company-wide.
Works with any LLM
Provider-agnostic SDK. Call your model however you want; score the response with one line. Swap models mid-experiment without changing your evaluation pipeline.
...and any other provider with an HTTP API. The SDK doesn't care which model produced the response.