Full-stack product development
Java and Spring Boot services, React interfaces, cloud workflows, data models, incident ownership, and the operational detail that keeps products useful.
Go deeper ↗Full-stack AI engineer · Hyderabad
I’m Devi Prasad Choudhary Ratnala—better known online as rdprassy. I build full-stack products with Java, Spring Boot, React, cloud platforms, and an expanding AI engineering toolkit.
Eleven playable experiences now cover maze chase, board strategy, typing, algorithms, memory, cloud puzzles, game physics, systems defense, and a five-chapter career quest.
Create tasks, classify urgency and importance, move work across an Eisenhower Matrix, and check off progress. Data stays privately on your device.
The work is technical. The perspective comes from competition, storytelling, sport, community, and a habit of learning across boundaries.
Java and Spring Boot services, React interfaces, cloud workflows, data models, incident ownership, and the operational detail that keeps products useful.
Go deeper ↗RAG, agents, MCP, QLoRA, AI-assisted application building, and Azure AI foundations.
Open the AI case study ↗Fast reduction, proof, implementation, and edge-case thinking in C++.
See the mindset ↗A 92-page novel, technical notes, essays, rap, and ideas that need a different medium.
Explore the novel ↗University Kho-Kho, South Zone Handball, and lessons that still shape how I work.
Enter the field ↗Five public products span inspectable RAG, AI-assisted delivery intelligence, creator infrastructure, Web3 utilities, and local-first productivity.
Hybrid retrieval, reranking, grounded citations, abstention, traces, and executable evaluation.
Inspect the AI system ↗
Requirements alignment, evidence-backed gaps, and delivery traceability in one workspace.
View product story ↗
A no-code ERC-721 launchpad with allowlists, analytics, and token gating.
View product story ↗
MetaMask connection, direct address lookup, and resilient RPC configuration.
View product story ↗Work spanning enterprise analytics, cloud maintenance, operational reviews, insurance calculations, platform microservices, and biometric research.
Recent work connects models to business decisions, private knowledge, and operational reliability—with measurable usage and clear system boundaries.
An AI-powered analytics platform supporting approximately 50 sales and operations stakeholders across 5+ retail accounts, with an estimated 25% improvement in analytics turnaround.
A context-grounded Q&A workflow indexing approximately 1,500 uploaded documents and serving 300+ monthly questions through retrieval and semantic search.
An agentic system monitoring 20+ data pipelines and triaging approximately 50 failures per month, with automated alerts and a reported 10% reduction in incident response time.
The public record shows product ownership, long-term learning, incident responsibility, and code that can be inspected. Named recommendations belong here only when they can be attributed accurately.
Documented work spans leadership reporting, cloud maintenance, enterprise analytics, insurance calculations, platform services, and biometric research.
Read case studies ↗High-severity application incidents were carried beyond recovery through root-cause resolution and durable fixes.
See experience ↗GitHub repositories, technical writing, cloud credentials, and AI engineering tracks make continued growth visible.
Browse credentials ↗I’m strongest where product thinking, backend depth, frontend delivery, cloud operations, and clear communication overlap.
“A career is a growing capacity to solve useful problems—and to explain the solution clearly.”
Let’s talk about product engineering, full-stack systems, AI-enabled workflows, or the next ambitious thing worth building.