Resources
Blogs, videos, case studies and announcements from our team
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.
Read MoreStreamlined 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.
Read MoreManaging The Organizational Impact of Bad Data
Big data is an indispensable part of our modern existence, powering several real-world applications such as personalized marketing, healthcare diagnostics, fraud prevention and many more that have transformed the way we live, work, and communicate with each other. However, since big data has become such a critical component of organizational decision-making, it is imperative to […]
Read MoreBlog posts
Pension Risk Transfer for Plan Sponsors: A Complete Guide
It’s a story that’s becoming all too familiar: A plan sponsor, weighed down by pension obligations, decides to take the leap into the world of pension risk transfer (PRT). And why not? PRT offers a tantalizing promise – the chance to secure participants’ benefits while saying goodbye to the risks and uncertainties of managing a […]
Read MoreHow Genetic Algorithms are Shaping AI and ML
Life is sort of like a grand optimization problem, one spanning eons and ecosystems. The players? Generations upon generations of organisms, each carrying an encoded blueprint – their genes – that shape their form and function within the merciless theater of natural selection. Those best adapted to their circumstances thrive and propagate, passing on the […]
Read MorePension Risk Transfer Regulations: A Comparative Analysis
A tightrope walker gracefully balances high above the ground, their every step calculated and precise. One minor misstep, one gust of wind, could send them plummeting from the slim cable providing their precarious passage. This razor-edge act epitomizes the delicate dance between securing hard-earned retirement futures and maintaining overall financial stability. Just as the tightrope […]
Read MorePension Risk Transfer (PRT) Demystified: Types of Risk and Strategies
Imagine you are at the helm of a ship, navigating through the foggy waters of financial uncertainty. Much like ancient vessels, pension schemes carry the weight of future promises – a secure retirement for those who spent lifetimes in service. Enter Pension Risk Transfer (PRT), your beacon in the mist, a strategy as crucial as […]
Read MorePension Risk Transfer Explained: Key Concepts and Trends
A pension fund is like a beacon for retirees’ dreams. It represents more than just savings. It is a covenant between the company and its workforce, promising a secure future. But what if, beneath this symbol of stability, a storm is brewing, one that threatens to unsettle the very foundations of their trust and well-being? […]
Read MoreExploring OpenAI’s SORA and Text-to-Video Models: A Complete Guide
In every epoch, some moments redefine the course of human history. The discovery of fire illuminated the dark. The invention of the wheel set humanity in motion. The creation of the printing press unfurled the banners of knowledge across the globe. Unironically, we may be standing at the threshold of another such transformative moment with […]
Read MoreBuilding AI Assistants: A Comprehensive Guide
For years, a giant mystery confounded the world of medicine. How do proteins fold? The answer, elusive, held the key to life itself. Then, a heroic AI agent – AlphaFold, emerged from DeepMind’s depths. It tackled the giant. And won. AlphaFold produces highly accurate protein structures The implications? Beyond staggering. AlphaFold is just the beginning. […]
Read MoreHow GenAI and Machine Learning are Transforming Actuarial Science
In the late 17th century, Edmond Halley sat by candlelight. He pored over numbers. Charts. Life tables. Halley, an astronomer by trade, ventured into uncharted waters. He sought to understand mortality, to predict life spans. His work laid the foundation for modern actuarial science. It was a time of discovery, of manual calculations, and limited […]
Read MoreThe Top LLMs For Code Generation: 2024 Edition
Imagine a world where coding isn’t just typing, thinking, and more thinking. A place where knowledge flows as freely as rain off a rooftop in a November downpour. Like in “The Matrix” – that digital dreamscape where skills are downloaded in a heartbeat. You want Kung Fu? You got it. Helicopter piloting? Just a plug-in […]
Read MoreGenAI vs. LLMs vs. NLP: A Complete Guide
In the early light of artificial intelligence, the world was simple. Machines were taught to mimic basic human tasks. As time moved, so did the ambition of those who programmed these machines. The first whispers of understanding human language emerged in what we now call Natural Language Processing (NLP). It was a modest beginning, a […]
Read MoreCase 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.
Read MoreStreamlined 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.
Read MoreHow 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.
Read MoreAccelerated 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.
Read MoreUnderstanding 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.
Read MoreA 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.
Read MoreVideos
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.
Watch NowCustomer 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!
Watch NowCustomer 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 […]
Watch NowWhat’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?
Watch NowAnatomy 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 […]
Watch NowAccelerating 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.
Watch NowGlobal 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 […]
Watch NowOperationalizing responsible Machine Learning
ML models have to be both economically viable and FAccT (Fair, Accountable, Transparent). The terminology is new but not the need to defend models or to attest they can be trusted. Such requirements were present from the 70s for credit scoring models. What has changed is the scale and scope.
Watch NowExperimentation in Data Science
The ‘science’ in Data Science refers to the process of developing systematic understanding of the world through observations and experimentation. This science is happening in the context of fast moving organizations, in near realtime, and by folks who have varied backgrounds. The most familiar version of the experimentation is the A/B testing.
Watch NowDevOps for Machine Learning Projects
In this session, Dmitry Pretrov and Ivan Shcheklein – co-founders of DVC – discuss: How software engineering principles apply to Machine Learning development and deployment. How ML systems are different from traditional applications. Importance of data versioning.
Watch NowWebinars
Scribble Conversations: Responsible AI at the Enterprise
Join leading industry experts for a two-part webinar series that unveils strategies for understanding the importance, legal nuances, ethical considerations, and future challenges of responsible AI.
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