I'm Anudeep Sri Bathina, an AI Architect with 11 years of experience turning GenAI, RAG, and data platforms into reliable production systems, with explicit boundaries, rigorous evaluation, and measurable impact.
A selection of measurable outcomes from production GenAI, machine learning, and data systems.
Enterprise GenAI platform at AT&T
Policy queries accelerated through RAG and automation
Across 50K+ document pages per month
At $0.42 per 1K requests on Azure
Delivered through customer churn modeling
Moving ML deployments from quarterly to weekly
Eleven years across engineering, technical leadership, graduate research, and enterprise AI. One continuous practice of making complex systems useful.
Research rigor matters. So do deadlines, operating costs, and the people maintaining the system after launch. My work sits at that intersection.
Explore the full journeyAT&T
Architected enterprise GenAI platform serving 15K+ internal users, reducing policy-query resolution time from 4 hours to under 90 seconds. Built Python-based document parsers processing 50K+ pages/month with 97.2% extraction accuracy. Deployed RAG pipeline via FastAPI + Azure AI Search achieving p95 latency of 2.4s at $0.42/1K requests.
2024 to Present
United States
Capgemini
Led ML engineering team of 8 engineers to deliver 12+ production data pipelines, reducing model training time by 65% through PySpark optimization. Implemented MLOps framework that increased model deployment frequency from quarterly to weekly. Achieved 94% model accuracy in customer churn prediction, saving $2.3M in retention costs.
2019 to 2021
India
GainInsights Solutions
Engineered scalable PySpark pipelines processing 10M+ records/day, improving ETL performance by 78% and reducing job failures by 92%. Developed real-time dashboard serving 500+ concurrent users with sub-second query response. Optimized database queries achieving 3.2x faster report generation for 25+ enterprise clients.
2019 to 2019
India
Cognizant
Led cloud data migration for 6TB of enterprise data across 3 AWS regions, completing 3 months ahead of schedule with 99.8% data integrity. Implemented predictive analytics models that increased sales forecasting accuracy by 43% and reduced inventory costs by $1.1M annually. Automated 85% of manual data migration tasks, saving 40+ hours/week of engineering time.
2015 to 2019
India
The tools matter. The architectural judgment behind retrieval, evaluation, safety, infrastructure, and data flow matters more.
Multi-agent systems, reasoning engines & tool-use
Enterprise retrieval, grounding & search systems
Guardrails, observability & production trust
Agentic coding & AI-powered engineering
Enterprise infrastructure built for AI workloads
Scalable pipelines, warehousing & real-time processing
Current questions
Reference implementations that make the architecture, trade-offs, and operating boundaries visible, not just the demo.
Healthcare RAG reference implementation with department-scoped retrieval, citations, role checks, and PHI masking.
Local-first sensitive-media workspace with role-based access, PII-aware metadata handling, local AI tagging, semantic search, and audit trails.
Reference implementation for benchmarking and serving LLM inference across vLLM, NVIDIA NIM, and NVIDIA NeMo, with optional CUDA profiling, a FastAPI gateway, and a Streamlit dashboard.
Local-first code migration assistant for static analysis, dry-run migrations, MCP tools, rollback checkpoints, and PII/PHI/PCI-oriented pattern scanning.
Culture-aware, India-first AI meal planner and grocery assistant for South Indian vegetarian cooking with evidence-grounded recommendations.
Mentoring, teaching, and making complex AI work easier to understand for practitioners across 20+ countries.
Learners reached
Countries represented
Mentoring hours
Topmate sessions
“Anudeep is incredibly insightful, listening carefully and offering technical yet straightforward comments that are truly beneficial.”
Michael
Freelance Developer
“Extremely insightful and valuable discussion. Anudeep's depth of knowledge in Data and AI is evident, and his willingness to openly share his expertise is commendable.”
Shashank H.V.
Student, UMass Dartmouth
“His tailored advice on skills, job applications, and interviews was practical and insightful, leaving me confident and motivated.”
Baran Khazaee
MSc CS, UC Davis
“His strategic guidance and ability to simplify complex AI and career paths into clear, actionable steps were incredibly helpful.”
Nelisa Sebastian
Data Analyst, Northeastern
“An exceptional session, making complex Agentic AI concepts easy to understand. His motivating approach inspired me to take bold steps.”
Mide Sowunmi
UX/UI Designer, Comcast
Published work in computer vision and IoT, carried forward into a production practice grounded in evidence.
Let's talk about production AI, platform architecture, mentoring, or research collaboration.