Scribble Data
@scribbledata
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Scribble Data is a machine learning and generative AI company, that helps enterprises build AI-powered data products for advanced analytics.
Toronto | New York | Bangalore
Joined April 2016
We’re hiring! Check out our careers page or DM us to learn more.
I am hiring for my Tech team. We operate at the intersection of GenAI and fintech enterprise applications. We are building interesting and powerful AI assistants and workflows to improve business bandwidth. Message me to talk more. @scribbledata .
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RT @BigDATAwireNews: Scribble Data Launches Hasper: A Full-Stack Applied AI Data Products Engine.@scribbledata #dat….
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🥁We're thrilled to introduce Hasper, our game-changing #LLM powered intelligent engine for advanced analytics. Say goodbye to traditional workflows and embrace innovation driven by #GenerativeAI. 🚀.Discover how #Hasper can transform your data journey!.
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RT @Dev_Discourse: Scribble Data Launches Hasper: A Full-Stack Applied AI Data Products Engine
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"#LLMs and #FoundationalModels are going to show up in the feature engineering journey. It will enable 10x use cases. There will be a new class of features (like vectors) and new storage services (like, #vectorDB). And the LLM output will eventually create a new data source."
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"Every business problem is a data problem now. Our users/stakeholders are business decision-makers, such as the Head of Compliance teams or the Head of Operations, (and not the data science teams)."
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"Also, the context of the problem space evolves and thus this flexibility is a must".
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"When thinking about feature engg infrastructure, it needs to be flexible in order to be able to drive value for the end users/customers."
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"One big refinement happening to ML is that it is aligning itself more and more to the business context. It is not just about delivery but delivery in a usable (by business) manner. Quick wins over shorter cycles are more valuable than projects spread over long delivery cycles"
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"Data quality is just one dimension of trust. So, one needs to think wholistically while building ML solutions. One of our key lessons is that towards establishing trust in the output of ML solutions, Reproducibility is crucial and not optional.".
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"ML is trust business and Data is trust business. One needs to be able to give guarantees as required/defined by a customer's context."
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"There are choices to be made at every step of feature engineering"
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"ML landscape is quite rich now and business problems come in all shapes and sizes. Feature engineering services and processes vary across the customers"
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Live now: @pingali at @TeamTargetIndia's #Multiplai talking about our experiences and learnings with Feature Stores - their evolution, the initial hype and momentum, and the eventual course correction.
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RT @MarTechSeries: @scribbledata Earns SOC 2 Type II Compliance Certification #martech #marketing #Technology #Scri….
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We are proud to announce that @scribbledata is now SOC 2 Type II certified! 🔐.While we've always believed in security by design, this rigorous exercise has validated that we meet the highest security standards for our customers!. #security #compliance #datasecurity #SOC2 #MLOps.
Scribble Data Earns SOC 2 Type II Compliance Certification
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RT @BessemerVPIndia: @scribbledata @BessemerVP Congratulations!! We love companies that make #revolutions of their own and appreciate the d….
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We are proud to be featured in the 'Developer platforms in India' report published by @BessemerVP @BessemerVPIndia. Can you spot us?! .
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We’re also giving away some cool Scribble Data merch, so don’t forget to stop by and grab ‘em all!
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