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AI Case study

Project : Spellforge AI

Industry: LLM, AI

Sub industry: AI Software Testing

About the project introduces an innovative solution for quality assurance in AI-driven applications, specifically targeting Large Language Models (LLMs) like GPT-4. This framework facilitates AI-to-AI testing by simulating user interactions using synthetic personas and automatically evaluating the responses of LLMs. It integrates seamlessly into existing release pipelines, enhancing the development process with efficient, cost-effective quality assurance. The project emphasizes the importance of realistic simulation for accurate response evaluation, aiming to ensure that AI applications meet user expectations before release. The open-source nature of Spelltest encourages collaboration and continuous improvement within the community, aligning with the project's philosophy of accessible, high-quality AI application development.


AI Platforms: OpenAI, Langchain, Spelltest

Prototyping Tool: Streamlit

Development Stack: Python, Django, PostgreSQL, Celery

Deployment Solutions: Docker, Azure, Bare-metal Servers

Monitoring Tools: Sentry, Prometheus, Grafana, Flower

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