Pulse STUDIO Vision API Launches: Production-Grade Unstructured Document Extraction

Pulse STUDIO Vision API recently launched!

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^{"An API + playground for production-grade unstructured document extraction, turning complex information into LLM-ready inputs. No training required."}

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Founded by Sid Manchkanti & Ritvik Pandey‍‍

The founding team has deep machine learning experience at Tesla, NVIDIA, D. E. Shaw, and AWS — as well as research experience at world-class AI labs at Berkeley and Georgia Tech.

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❌ The Problem

Most enterprise data is unstructured, making it difficult to parse with LLMs

Approximately 75% of enterprise data is unstructured, the majority of this is directly within PDF files. This makes it extremely difficult to build RAG applications with this data, and ingestion is often the bottleneck.

Current solutions are slow, inaccurate, and expensive

They personally tested nearly every other tool on the market and found they lack accurate contextual understanding, multi-column PDFs, and multimodal documents. Most of the current technologies are simply wrappers on Textract or Gemini — which have their own inherent flaws.

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✅ The Solution

Pulse STUDIO Vision API, a SOTA document/spreadsheet vision model

The team has trained their own set of Vision Language Models (VLMs) and OCR techniques to bridge this gap. They achieved what they think to be a state-of-the-art (SOTA) vision model for documents and spreadsheets. You’ll get bounding boxes across your documents and spreadsheets, alongside incredible OCR on tables and graphs.

They are also actively working on a novel reasoning tool on spreadsheets using this technology – stay tuned!

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Learn More

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^{🌐 Visit www.trypulse.ai to learn more.}

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^{⚡ Their API is deployed in companies across hardware, healthcare, manufacturing industries and more. They are expanding rapidly! Fill out this form for access and they will reach out within 24 hours with playground access.}

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^{🤝 Please share this post, as you never know who it may help! Reach out to the founders here.}

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^{😎 There's more info on the product page here.}

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