# Test New Model Versions with Real Production Calls Using Cekura

Written by:

Shashij Gupta

Last updated

Oct 15, 2025 · 2 min read

When large language models evolve, one of the biggest risks is regression: new model behavior that breaks something that previously worked. That’s why teams rely on **replay testing**: rerunning real user interactions from production against the latest model version to ensure nothing critical changes for the worse.

Cekura makes this process simple, automated, and measurable.

## What Replay Testing Does

| Function | What It Means |
| --- | --- |
| **Production Data Capture** | Cekura automatically logs real user-facing calls or chats from live environments. Sensitive information can be filtered or anonymized. |
| **Replay Engine** | Feed those stored conversations back into a new model version - such as moving from GPT-4o to GPT-5 in a controlled environment to reproduce realistic behavior. |
| **Diffing & Evaluation** | Cekura compares new vs. old outputs using numeric, Boolean, or rating-based metrics like accuracy, tone, latency, or hallucination rate, with timestamped issue markers. |
| **Human-in-the-Loop Review** | Teams can annotate and rank results directly on Cekura’s UI to validate which version performs better in real-world conditions. |
| **Regression Detection** | Automatically flag drops in correctness, responsiveness, or reliability when migrating to a new model or infrastructure. |
| **Batch & Segment Testing** | Run replays across user segments, prompt clusters, or domains to identify where performance differs most. |

## How Cekura Extends Replay Testing

- **Baseline Regression Suites**: Teams create steady-state test suites that serve as a “version control” for conversational quality. Cekura re-runs these automatically whenever a prompt, model, or infra change happens in CI/CD.

- **Turn-Level Metrics & Charts**: Latency, interruptions, and factual correctness are tracked turn by turn, not just at call level, with visual diffs and performance curves.

- **Multi-Model Benchmarking**: Test GPT-4o vs. GPT-5 vs. Gemini on the same data to quantify which one performs best before deploying to production.

- **API & GitHub Integration**: The entire platform is accessible by API so you can trigger replays directly from your CI pipeline.

## Why It Matters

Without automated replays, teams face blind spots when upgrading models. Cekura closes that gap by showing exactly how a new version behaves on **your real users’ conversations**, not just synthetic benchmarks.

From regression detection to A/B model comparison, Cekura turns model upgrades into a data-driven decision rather than a leap of faith.