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Diptanu Gon Choudhury
Founder and CEO @ Tensorlake
Diptanu Gon Choudhury is a prominent figure in the field of artificial intelligence and distributed systems, currently serving as the founder of Tensorlake, a company focused on developing innovative solutions for handling unstructured data. He has a rich background in technology, having held significant roles at major companies such as Facebook, Netflix, and HashiCorp.
Professional Background
- Founder of Tensorlake: Choudhury leads Tensorlake's efforts to create Indexify, an open-source, scalable structured extraction engine designed to process unstructured data for AI applications. This project aims to facilitate near-real-time knowledge bases for AI-driven workflows and query engines.12
- Previous Experience:
- Facebook: He was the tech lead for the FB Learner machine learning platform and developed a real-time speech inference engine.23
- Netflix: Choudhury invented the Titan/Titus cluster scheduler, which is pivotal for managing cloud services.2
- HashiCorp: He created the Nomad cluster scheduler, further showcasing his expertise in distributed systems.24
Contributions and Philosophy
Choudhury emphasizes the importance of embracing challenges and failures as integral parts of technological innovation. He believes that understanding the complexities of unstructured data is crucial for leveraging its potential in analytics and AI applications. His work aims to democratize access to advanced data processing tools by promoting open-source solutions, fostering collaboration within the tech community.14
Vision for AI
In his discussions, Choudhury highlights the need for tailored solutions in AI deployment, recognizing that a one-size-fits-all approach is insufficient. He advocates for a deeper understanding of business use cases to effectively integrate AI technologies into various industries. His insights reflect a commitment to advancing the field of AI while ensuring that developers have the necessary tools and resources to innovate.45
Choudhury's LinkedIn profile can be found under the username diptanu, where he shares updates about his work and insights into the evolving landscape of AI technology.5
Highlights
Announcing Context-Aware Signature Detection in @tensorlake Cloud
Signature Detection is a key aspect of business workflows, but ingestion APIs provide predictions related to presence/absence of signatures in documents and bounding boxes.
Context-Aware signature detection in @tensorlake extracts names of signatories, date and place from documents. You can even combine that with Basic Signature Detection to get bounding boxes of signatures!
This allows building AI Agents which can check for compliance in legal, accounting, healthcare and other regulatory industries!
All this is an API call away, vs building brittle pipelines which calls multiple models to piece all the information together!

Seeing a lot of demand for parsing Excel sheets in @tensorlake cloud from customers. What's a good representation that's helpful for building Knowledge Agents form excel sheets?
The files we are looking at are WIDE and long. Think 100s of columns wide and 1000s of rows long.
My immediate thought is to convert the sheet into a data frame, and extract formulas and describe which formula is applied to which columns, etc.
Anything else we could do to help ingesting excel sheets?

