A/B Testing Prompts and Models in Production

Offline evals are necessary but not sufficient. The only way to know what works in production is to run a controlled experiment in production.

Why it matters

A/B testing AI features needs traffic-splitting at the gateway, business-metric attribution and statistical analysis that handles the high-variance nature of LLM outputs.

How Bhogar AI approaches it

Bhogar AI ships traffic-splitting at the gateway, attribution to user-defined business metrics and a built-in statistical analyser with sequential-testing support.

• Traffic-splitting at the gateway
• Per-experiment cost, latency and quality dashboards
• Business-metric attribution
• Sequential testing with safe early-stopping
• Shadow traffic and dark launches

What you get

Teams running structured A/Bs ship prompt and model changes with measured business impact instead of vibes.