Anjana Sudhi

• Led a cross-functional team in the design and development of the Marketing Insights module within an agentic marketing platform, leveraging LangGraph, CrewAI, and advanced LLM orchestration methodologies to enable deep multi-source marketing research and insight generation.
• Delivered an end-to-end Generative AI solution for an international Life Sciences enterprise, achieving an 82–90% reduction in content creation time. The solution integrated AWS cloud infrastructure, Azure OpenAI, Midjourney, and Adobe Firefly, aligning with enterprise-grade content automation and digital asset generation standards.
• Executed multiple Proof-of-Concepts (PoCs) for retail, banking, and other verticals while driving core product development of Generative AI applications. Collaborated closely with pre-sales, Go-to-Market (GTM), and solutioning teams to align offerings with client needs and market trends.

Previous Work in the Same Role

• Product Manager and GTM Co-Lead for a portfolio of Generative AI assets and AI-powered content generation & intelligence platforms, enabling scalable marketing automation and cross-channel insights across industries.
• Developed Generative AI accelerators to:
  Identify emerging trends and audience segments using LLM-powered knowledge synthesis and NLP pipelines.
  Automate data mapping and interpretation of dashboards (AI over BI), enabling faster insights and decision-making across marketing analytics use cases.
• Designed and delivered Computer Vision and NLP-based AI products that automatically generate and analyze marketing content, leveraging state-of-the-art LLMs, foundation models, and CV algorithms.
• Drove end-to-end Product Management including:
  Strategic roadmap planning, resource alignment across engineering and AI/ML teams.
  Infrastructure architecture using cloud-native components.
  Pricing models, recovery frameworks, and stakeholder communication.
  Agile project tracking and leadership-level reporting for high-impact milestones.
• Co-led Go-to-Market (GTM) activities:
  Designed integrated GTM campaigns and presented solutions at global Sales, Marketing, and Commerce leadership workshops.
  Conducted competitive analysis and defined product positioning and differentiation.
  Supported business development (BD) through RFP/SOW shaping, pipeline governance, and recovery planning for strategic AI opportunities.
• B2B Intelligent Revenue Growth (Multiple Clients):
  Delivered AI-enabled revenue optimization solutions across industries, focusing on personalization, segmentation, and predictive targeting.
  Translated sales and marketing pain points into actionable product features, integrating AI/ML into traditional B2B revenue models.
• Plan Rationalization – Leading Singaporean Telecom Provider:
  Led initiative to simplify and optimize product and pricing plans through AI-driven analytics.
  Conducted customer segmentation, usage pattern analysis, and scenario modeling to inform rationalization strategy.

• Designed and implemented Customer 360, segmentation models, propensity scoring algorithms, and advertising analytics dashboards for a leading eCommerce platform, using Python for data preparation and modeling. Applied logistic regression, random forest classifiers, and unsupervised clustering techniques to enable personalized campaigns and conversion uplift.
• Developed a Digital Consumers Customer 360 (CAR - Customer Analytics Repository) for a major telecom provider, integrating multiple data streams and applying customer segmentation and behavioral analytics techniques using Python. The solution provided a unified, actionable view of consumer behavior for targeted marketing and retention.
• Built a Customer Lifetime Value (CLTV) model for an American multinational technology company, leveraging linear regression and time-series forecasting in Python to predict long-term customer profitability. Insights informed personalization strategies, resource allocation, and lifecycle marketing across digital channels.