LLM Ops & Evaluation Platform

Real-time LLM monitoring, evaluation, and A/B benchmarking dashboard

LLM applications in production lack observability — teams cannot track quality degradation, cost overruns, or prompt drift. Built a monitoring and evaluation wrapper that works with any LLM application and provides real-time quality metrics, cost tracking, and A/B benchmarking.

January 1, 2025

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Overview

Implemented a call tracer recording latency, token counts, and cost estimates per model pricing table; added LLM-as-judge evaluation on four axes (faithfulness, relevance, completeness, toxicity); built an A/B benchmark runner executing N model configs against identical test cases. Delivered a live Streamlit dashboard with rolling eval scores, benchmark comparison charts, and a trace explorer; designed for CI/CD integration with configurable regression thresholds per metric.

The Problem

LLM applications in production lack observability — teams cannot track quality degradation, cost overruns, or prompt drift without dedicated tooling.

The Solution

Call tracer for latency/token/cost, LLM-as-judge on four axes, A/B benchmark runner, live Streamlit dashboard with rolling eval scores and CI/CD integration.

LLM Ops & Evaluation Platform

Tech Stack

Overview

The Problem

The Solution