Embedding OpenAI and open-source models (LLaMA 2, Mistral) for natural language understanding, log analysis, and contextual chat features.
Utilizing embeddings + vector databases (e.g., Weaviate, Pinecone, or MongoDB Atlas Vector Search) to power semantic search and recommendations.
Domain-specific prompt pipelines to extract insights, generate summaries, and automate user interactions with precision.
Intelligent log summarization and anomaly detection using embeddings from structured logs via Serilog + MongoDB.
Fine-tuning small models using our proprietary food-tech data to power autonomous agent use-cases and dynamic decision flows.