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Asserta leverages a technology stack including Ollama, Python, and PostgreSQL, all running on an Ubuntu environment. This project is focused on developing a robust system for generating optimal tests across various programming languages, likely utilizing an API for integration. Julian orchestrated an intelligent test generation system that leverages LLMs through Ollama to automatically create optimal test cases across multiple programming languages.
Read moreEverpot aims to streamline the creation of technical documentation by employing tools like Ollama, Google AI-gen, and sophisticated prompting techniques. The underlying infrastructure includes Python, PostgreSQL, and Ubuntu, with an API facilitating its services for any product or service. Julian developed an AI-powered technical documentation platform backend that combines local LLM capabilities with Google AI. This generates comprehensive and accurate documentation through advanced prompting techniques and tested POC for a code-generation based on created specs.
Read moreEvercoda is designed as a lightweight IDE with integrated AI capabilities to assist in code generation, built using FastAPI, Python, and Ollama. It relies on a PostgreSQL database and operates on an Ubuntu system, offering a streamlined coding environment. Julian created a lightweight IDE backend with embedded AI assistance that helps developers generate code and code-autocomplete efficiently using local LLM integration via Ollama and FastAPI.
Read moreTEC/POC focuses on evaluating educational documents through both general and course-specific assessments, utilizing Google AI-gen and prompting strategies. The project is built upon a microservice architecture using TypeScript, with data management handled by NoSQL and PostgreSQL databases. Julian curated the creation of a sophisticated educational document evaluation system using microservices architecture that performs both general and course-by-course-specific assessments through advanced AI prompting strategies via Google AI gen models.
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