Resources

Blog posts

The Future of Employee Benefits: Top Trends to Watch Out for in 2025

Imagine telling an insurance executive in the 1970s that, in the not-so-distant future, they would be crafting group benefit plans that include coverage for mindfulness app subscriptions, pet insurance, or even student loan repayment assistance. They might have chuckled at the absurdity—or marveled at the complexity. Yet here we are in 2024, navigating a landscape […]

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Top Insurtech Trends for 2025 and Beyond

The insurance industry stands at a crossroads. The global protection gap, a measure of uninsured risk, looms large. By 2025, it will reach $1.86 trillion. This is not just a number. It represents real people and businesses exposed to financial ruin. The old models of insurance are failing to keep pace with a rapidly changing […]

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A Guide to Managing Illiquid Assets in Pension Risk Transfers

As the sun rose on a crisp autumn morning in 2022, pension fund managers worldwide awoke to a startling new reality. The gilts crisis that had rocked UK financial markets had not only sent shockwaves through the economy but also dramatically reshaped the landscape of defined benefit pension schemes. For many, the path to buyout—once […]

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What’s Driving the Pension Risk Transfer Surge in the US, UK, and Canada?

Pension risk transfer markets are expanding. The United States, United Kingdom, and Canada are experiencing unprecedented levels of PRT activity.  Record-breaking transaction volumes define this new era. An influx of new insurers and innovative deal structures are transforming the market. The PRT boom is touching every segment from multi-billion-dollar megadeals to mid-market transactions. What is […]

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The Future of Retirement in the U.S.: Challenges, Solutions, and the Role of AI

At 74, Theresa Edwards rises before dawn, crisscrossing Los Angeles by bus to work as a caregiver. Her last patient of the day? Her husband of 55 years, recovering from a serious car accident. Every dollar counts in their household, where four grandchildren also reside. “Sometimes I wish I could stop working,” Edwards confides. “But […]

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The Role of Data Quality in Pension Risk Transfer

Pension funds are like a vast web, woven over decades, where each thread represents a worker’s career—their wages, years of service, and life events. When this complex web worth billions of dollars changes hands, a single loose thread can unravel the entire fabric. Remember that adage, “You can’t manage what you can’t measure”? Well, in […]

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The Evolving Landscape of LLMs in Enterprise Applications

November 2022. ChatGPT drops, and the AI world shifts on its axis. Little did we know, this was the digital equivalent of splitting the atom. Fast forward to today, and Large Language Models (LLMs) have gone from party tricks to power tools faster than you can say “Hey Siri.”. But let us cut through the […]

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AI Adoption in Enterprises: Key Strategies, Successes, and Challenges

From Wall Street to Silicon Valley, from London to Singapore, the race is on. Who will master AI first? Who will use it most effectively? And who will be left in the dust? This is not a story of robots taking over. It is a story of humans and machines learning to work together, each […]

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State of Enterprise AI Adoption: How Top Enterprises Are Building for the Future

The titans of industry are in an AI arms race. They’re not waiting for solutions. They’re building them.  They are on the front lines – with foundational models, intricate ML systems and computing services that serve their sprawling global ambitions. Others are arming themselves too. With cloud platforms, engineering solutions and homegrown AI. Before our […]

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Case Studies

Finding Conversion Anomalies at a Large E-Commerce Firm

Learn how a leading multi-billion dollar e-commerce company used Enrich to identify anomalies in their conversion rates and to find out their causal factors.

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Terrapay case study with Scribble Data

Streamlined data insights and agile data preparation for Terrapay

Learn how Terrapay, a leading cross-border payment infrastructure solution provider built the Terrapay Intelligence Platform (TIP) with Enrich to achieve operational efficiency through use cases such as Forecasting, Partner Performance Analytics, Customer Journey Analytics, and more.

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Mars great resignation case study with Scribble Data

How Mars Took Steps to Evaluate the Potential Impact of the “Great Resignation”

Learn how Mars, a Fortune 100 CPG company collaborated with Scribble Data to assign a “probability of attrition” through data, and ML modeling.

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Accelerated ML Engineering for a Leading E-Commerce Brand

Learn how a leading e-commerce brand selling children’s apparel built their data intelligence platform on Scribble Data that supported the rapid development and deployment of use cases such as Product Listing Optimization and Re-ordering.

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Shopping paths at a mall chain with Scribble Enrich

Understanding Shopping Paths at a National Mall Chain

Learn how a nationwide mall chain used Scribble Data’s Enrich platform to identify patterns of shopper footfalls, determine the timing and location of ads, and achieve a significant M-o-M increase in revenue.

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Data lake enrichment for a national retail chain using Scribble Enrich

A National Level Retail Store Chain

A national level retail chain in India leverages Scribble Data Enrich for developing an accurate understanding of their buyer personas, their distribution, demand and context at a fine granularity to address multiple operational use cases.

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Videos

MLOps Conference: Fast Development of ML Applications

Malavika Lakireddy (VP, Product Development, Zeotap), Saransh Verma (Director-Analytics, TerraPay), and Dr. Venkata Pingali (Co-Founder and CEO of Scribble Data) talk about the challenges in developing ML applications.

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Orchestrating AI Assistants at the Enterprise

Dr. Venkata Pingali, CEO of Scribble Data, talks about the complexities of orchestrating multiple AI systems to work seamlessly together.

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Lifecycle of a Data Product with Dr. Venkata Pingali

Watch this session where Dr. Venkata Pingali, Founder & CEO of Scribble data shares his perspective on Data Products, the types of Data Products, and the lifecycle of Data Products with the Data Heroes community.

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Customer Testimonial: Cloudphysician

Dileep Raman, Cloudphysician’s Co-founder and Chief of Healthcare, talks about how Scribble Data enabled them to rapidly build pipelines to transform their data and get daily updated feature sets as well as trustworthy models – all in less than 4 weeks!

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Customer Testimonial: Mars, Inc.

Dr. Vidyotham Reddi of Mars, Incorporated–a leading US-based multinational CPG manufacturer of confectionery, pet food, and other food products and a provider of animal care services, talks about his experience of working with Scribble Data. Learn how his team at Mars was able to assign a “probability of attrition” to employees, calculated based on which […]

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What’s the deal with sentient AI? – Achint Thomas

Sentience in AI has always been the holy grail for computer science. What qualifies as AI sentience, and what is just another case of a model mimicking the data it’s trained on?

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Anatomy of a production ML feature engineering platform – Venkata Pingali

This talk draws upon the Scribble’s experience in building and evolving a production feature engineering platform, and the many conversations we have had with user data scientists. The talk will focus on the learnings, and not on the Scribble product itself, and expand on the talk from Fifth Elephant Mumbai in Jan 2019 on reducing […]

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Accelerating ML using Production Feature Engineering Platform by Venkata Pingali

Anecdotally, only 2% of the models developed are productionized, i.e., used day to day to improve business outcomes. Part of the reason is the high cost and complexity of productionization of models. It is estimated to be anywhere from 40 to 80% of the overall work.

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Global Feature Store Meetup #13 – Scribble Data

Feature stores have been traditionally designed for complex ML applications (Big-ML) that normally assume clear and high value propositions, long lead times, skilled staff, and advanced methods. Sub-ML is a space of mid-complexity ML applications where there is higher uncertainty in terms of value, methods used, available staffing, and speed is critical. Sub-ML is interesting […]

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Webinar Post

[On Demand Webinar] Scribble Conversations: Responsible AI at the Enterprise

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