Accelerated Scientific Knowledge platform using Agentic RAG

Sysvine Technologies is partnered to deliver an initiative that includes strengthening of microservices, WCAG compliance, scalable cloud infrastructure and AI-driven scientific content awareness to a global scientific knowledge provider. We delivered a zero-trust microservices architecture, secured inter-service communication using encrypted API gateways, and automated vulnerability detection through CI/CD pipelines. Disciplined Test-Driven Development (TDD) and robust observability principles significantly engineering velocity, improved quality and production reliability. We integrated multiple large language models — including Claude 3.5 Sonnet, OpenAI GPT-4 Turbo, Anthropic Claude 3 Opus, and Mistral 7B — enabling semantic content summarization, contextual retrieval, intelligent query reformulation, and AI-assisted discovery. These models were orchestrated via an agentic RAG (Retrieval-Augmented Generation) framework with vector databases for domain-specific grounding. Our DevOps team led EKS optimization and Java Spring Boot patches, enhancing scalability and deployment speed.