Rakesh Kumar

AI Product Manager & AI Lead

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Product Impact

70%+

Manual tasks reduced using agentic AI workflows

80%

Faster insight generation with BI dashboards

10×

Clinical research turnaround acceleration

85%

ML + LLM diet engine accuracy

20k+

Users onboarded in 90 days (coach-driven wellness)

$50k+/mo

Incremental revenue via recommendations

3×

Experimentation velocity (AI playground)

1M INR

GMV leakage prevented per month

Professional Experience

  1. Feb 2023 – Present

    AI Product Manager & AI Lead — Dr. Reddy’s (Svaas Wellness)

    • Built agentic AI framework to automate workflows and fine-tune LLMs; reduced manual tasks by 70%.
    • Architected RAG pipeline for clinical intelligence with customized data cleaning and ingestion; 5% better retrieval score than Azure managed services.
    • Designed Deep Research Agent for clinical studies; cut research turnaround time by 10×.
    • Architected GenAI voice agent for clinical support with <4s latency enabling real-time interactions.
    • Developed internal AI Playground for rapid product and design teams; 3× faster prototyping and AI experimentation.
    • Engineered ML + LLM-based diet engine achieving 85% accuracy.
    • Integrated RAG agent into BI dashboards; 80% faster insight generation and self-serve analytics.
    • Implemented symptom analyzer and health risk assessment tool impacting 5k+ users in 4 months.
  2. Dec 2021 – Jan 2023

    Product Manager (Customer Success, New Initiatives, Platform) — MediBuddy

    • Built tool generating valuable customer feedback; improved adoption and messaging.
    • Scaled B2B CS support and automated systems; raised CSAT from 2.8 to 4 and first contact resolution by 10%.
    • Launched social media automation; boosted organic reach.
    • Accelerated refunds with all payment sources; automated claims with third parties and insurers.
  3. Jul 2020 – Dec 2021

    Data Product Manager — eShakti

    • Improved conversion by 7% for new users via enhanced product discovery funnel.
    • Increased customization usage by 9% with $30,000+ per month CLV uplift.
    • Improved onsite search and sorting; 5% overall sales increase and $15,000/month reduction in overstock.
    • Built recommendation engine yielding $50,000+/month incremental revenue and 8% retention improvement.
  4. Jul 2015 – Apr 2018

    Software Engineer — Capgemini India Pvt. Ltd.

    • Resolved 10+ post-production issues; stabilized a web application.
    • 30% reduction in waiting time with 15+ new features enhancing UX.
    • Cut lead time of an upload service by 60% and reduced report generation time by 50%.
    • Developed and trained ML models using RNN, NN, and CNN for training programs.

Selected Case Studies

Agentic AI Platform — Healthcare

AI Agents LLM Automation

Problem

Manual processes and slow iteration for AI features across teams.

Action

Built a reusable agentic AI framework, custom data pipelines, and evaluation harness; integrated into BI stack.

Impact

70% reduction in manual tasks; 3× faster prototyping; 80% quicker insight generation.

Business Case

Addressed inefficiencies in healthcare workflows by leveraging AI to automate repetitive tasks, enabling faster decision-making and resource allocation for clinical teams.

PRD Highlights

  • Core Features: Agentic workflows, LLM fine-tuning, RAG integration for BI dashboards.
  • Success Metrics: Task reduction >70%, insight generation time <20% of original.
  • Tech Stack: Python, LangChain, custom RAG pipelines.
  • Stakeholders: Product, Design, Clinical teams.

Deep Research Agent — Clinical Studies

RAG Search Healthcare

Problem

Clinicians needed rapid, reliable summaries from large corpora.

Action

Architected custom retrieval with domain-specific cleaning, chunking, and evaluation.

Impact

10× faster research turnaround with improved retrieval scores.

Business Case

Accelerated clinical research processes to bring insights to market faster, reducing time-to-decision in drug development and patient care.

PRD Highlights

  • Core Features: Advanced RAG with custom data ingestion, low-latency querying.
  • Success Metrics: Turnaround time reduction to 10%, retrieval accuracy >95%.
  • Tech Stack: Vector DB, custom embeddings, evaluation harness.
  • Stakeholders: Clinicians, Researchers.

Recommendations at Scale — eCommerce

Recommender Systems Data Platform Experimentation

Problem

Low discovery and high overstock.

Action

Built hybrid recommendation engine and improved onsite search & sorting.

Impact

+$50k/month incremental revenue, +7% new-user conversion, −$15k/month overstock.

Business Case

Enhanced product discovery to drive sales and reduce inventory costs in fashion e-commerce, improving customer satisfaction and retention.

PRD Highlights

  • Core Features: Hybrid recs (content+collaborative), A/B testing framework.
  • Success Metrics: Conversion uplift >5%, revenue increment >$50k/mo.
  • Tech Stack: ML models, data pipelines, experimentation tools.
  • Stakeholders: Marketing, Sales, Data teams.

Other Projects

GenAI Voice Agent

Architected low-latency voice agent for real-time clinical support interactions.

GenAI Voice Healthcare

Impact: Enabled seamless support with <4s latency.

ML + LLM Diet Engine

Engineered hybrid engine for personalized diet recommendations with 85% accuracy.

ML LLM Wellness

Impact: Improved user health outcomes in wellness platform.

Symptom Analyzer & Risk Assessment

Implemented AI tool for health risk evaluation, reaching 5k+ users in 4 months.

AI Health Tech

Impact: Enhanced early detection and user engagement.

Internal AI Playground

Developed platform for rapid AI prototyping, accelerating experimentation by 3×.

AI Tools Prototyping

Impact: Faster iteration for product and design teams.

Skills

Education

Certifications

IBM AI Product Manager, IBM AI Developer, Google Digital Marketing, Six Sigma Green Belt, LLM Courses.

Contact

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