Tune your AI Agent to best meet its KPI with a cyclic process of analyze, improve and simulate

Exploratory data analysis and interactive model-understanding and evaluation tool for chatbot training data and feedback

An open-source framework for robust, LLM-powered testing and tracing of conversational AI applications.

This is a repository for a Jupyter based tool to calculate Greedy Matching, Vector Extrema and Average Embedding evaluation metrics for generative AI chatbots

Evaluation results and experimental data for TRACER, demonstrating its effectiveness in discovering chatbot functionalities and detecting errors with coverage analysis and mutation testing.

AI chatbot evaluation benchmark for mental health and suicide prevention with rule-based ethical alignment, inclusivity scoring, and sentiment analysis. Research paper submitted to AI & Society (Springer Nature) under review.

Self-hosted LLM/Agent batch evaluation platform with OpenAI-compatible API testing, streaming response parsing, LLM-as-a-Judge scoring, Docker deployment, and CSV/XLSX export.

Structured evaluation of 30 support bot conversations measuring containment, escalation rate, intent accuracy, and CSAT correlation, LLM-assisted qualitative coding, edge cases, and recommendations.

First publication & part of Master’s thesis at HCMUS: End-to-end automatic evaluation framework for retrieval-augmented chatbots (accepted at ACIIDS 2026)