LLM Quality Monitoring

Passing Launch Tests Isn't the Same as Staying Accurate.

An AI application that passed its launch tests can still get worse in production. New user questions, model updates, prompt edits and changing documents all shift quality, and spot-checking a few prompts won't catch it.

Codersarts LLM Quality Monitoring measures your live AI every month. We run your eval suite on fresh samples of real traffic, score outputs with calibrated LLM-as-judge pipelines and human reviewers, run regression checks before every change, and alert you when quality drops.

4.9/5 client rating · Clients in 50+ countries · Monthly plans · NDA on request · Working-hour overlap with US & Europe

WHAT'S INCLUDED

What's Included in LLM Quality Monitoring?

• Eval dataset creation — Test sets built from real questions, documents and edge cases.

• Scoring rubrics — Accuracy, groundedness, completeness, safety and tone criteria.

• Human expert review — Developers and domain reviewers score outputs where judgment matters.

• LLM-as-judge pipelines — Automated scoring calibrated against human labels.

• Regression testing — Evals run before every prompt, model or retrieval change.

• Quality dashboards — Scores tracked over time with alerts on drops.

• Monthly sampling of live traffic — Fresh real-world questions and outputs scored every month.

SIGNS YOU NEED IT

Signs You Need LLM Quality Monitoring

• You can't say how accurate your AI is in numbers.

• A prompt or model change fixed one thing and broke another.

• Stakeholders or customers ask for proof of quality.

• You need to choose between models for your use case.

• RAG answers sound right but cite the wrong sources.

KEY FACTS

Key Facts

HOW WE WORK

How It Works

1. Review — we assess your current setup, data, integrations, costs and quality, and set a baseline

2. Scope and SLA — we agree what's in scope, quality measures, response times, reporting and price

3. Onboarding — access, monitoring, alerts and documentation set up; we take over day-to-day operation

4. Monthly — we operate, improve and report against the SLA, with recommendations for next steps

WHAT WE MEASURE

What We Measure Every Month

• Accuracy and groundedness scores

• Pass rate on critical test cases

• Regressions caught before release

• Agreement between LLM-judge and human scores

WHO THIS IS FOR

Is This Right for You?

A strong fit if you are one of these:

• Teams launching an AI feature that must meet a quality bar.

• Companies comparing models or providers.

• Regulated teams that need documented testing evidence.

• Product teams that ship prompt changes often.

PLATFORMS

Platforms We Support

Promptfoo, DeepEval, Ragas, Braintrust, LangSmith, Langfuse, OpenAI Evals and custom Python harnesses, for any model provider.

See all technologies we work with.

PRICING

Pricing

Ongoing quality monitoring starts from $999 per month. If you don't have an eval suite yet, we build one first as a fixed-scope project through LLM Evaluation & Benchmark Engineering.

Compare all tiers on AI Managed Services Plans, or start with a free 14-day pilot review.

BUILD, FIX OR RUN

Build, Fix or Run: Choose the Right Service

Need it built? Start with one of these:

• LLM Evaluation & Benchmark Engineering

• MLOps & LLMOps Infrastructure

Need a one-time fix? Use one of these:

• Codersarts Support

• Codersarts Tasks

Need it run every month? That's LLM Quality Monitoring, part of Codersarts AI Managed Services.

FAQ

Frequently Asked Questions

What is LLM quality monitoring? An ongoing service that scores your live AI application's outputs every month, runs regression checks before changes and alerts you when quality drops.

How is this different from LLM Evaluation & Benchmark Engineering? Evaluation & Benchmark Engineering builds your eval suite and benchmarks before launch. Quality Monitoring runs those evals on live traffic every month.

Do you use human reviewers or automated scoring? Both. LLM-as-judge handles scale; human reviewers score cases where judgment matters and keep the automated scores calibrated.

Can you monitor RAG systems? Yes, including retrieval quality, groundedness and citation accuracy.

How much does it cost? Plans start from $999 per month.

GET STARTED

Tell Us About Your AI System — Get a Plan in 48 Hours

Share a few details about what you're running and a Codersarts AI engineer will review it and send a recommended plan, scope and price.

What happens after you submit

1. Review — we look at your system and goals

2. Call — a 30-minute call to confirm scope

3. Plan — a written plan with SLA and price

4. Start — onboarding begins within a week

BACKED BY CODERSARTS

More Ways Codersarts Supports Your AI

• AI Managed Services — the full catalogue of AI systems we run for you

• Forward Deployed Engineers — AI engineers embedded in your team

• AI Strategy & Architecture Audit — a one-time review of your AI stack

• Hire Developers — dedicated developers for your roadmap

Related Services in This Cluster

• Managed LLMOps — prompt versioning, model upgrades, regression checks and routing for LLM apps

• AI Red Teaming Services — adversarial testing and continuous security checks for AI apps and agents

• Managed AI Agents — monitoring, permissions, tuning and change control for production AI agents