Unstract

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6️⃣ tax document challenges. 1 platform that handles all of them. ✅ From annual template changes to messy scanned documents to tax packets bundling multiple forms—tax document extraction is harder than it looks. Catch this snippet, then watch the complete breakdown of how Unstract solves each challenge on YouTube 👉 https://lnkd.in/gvDPF8NF #Unstract #TaxExtraction #DocumentProcessing #AIforBusiness #Automation #LLM

"Self-hosted" and "sovereign" are not the same. 🚨 This is usually how it pans out 👇 A team wants to extract information from sensitive documents using LLMs. Imagine claims, loan files, discharge records, KYC packets. 📄 Security rules out general, cloud AI tools. Fair enough. So the team does the responsible thing. They self-host the whole platform. It runs on their Kubernetes, documents sit on their storage, and nothing lives on anyone else's cloud. Everyone relaxes. ✅ Then when someone double-clicks on LLM settings, there it is: a base_url points at a hosted inference API. 🔌 Which means every extraction call has been shipping page text out of the building this whole time. Names, SSNs, diagnosis codes, account numbers. The data the self-hosted project was meant to protect. ⚠️ Nobody lied. Nobody cut corners. They just treated "on-prem" as a property of the software, when it's actually a property of the data path. For a document pipeline to count as sovereign, every single hop must stay inside your network: 📥 Intake 🗄️ Storage ⚙️ Processing and prompts 🧠 Inference on GPUs you own One outbound call anywhere in that chain and the boundary is gone. Not weakened, but gone. The encouraging part is that this is a solvable problem now. 💪 Capable open models run on local GPUs. Inference containers speak the same API as the hosted endpoints, so you can change where that base_url points without rewriting prompts. Self-hosting is the easy part. "Nothing leaves the building" is the standard. 🔒 #Unstract #DocumentDataExtraction #AIDocumentProcessing #SovereignAI #DocumentAI #DataPrivacy

"AI-ready" usually just means "converts to Markdown." But Markdown throws away what an LLM needs to read a document: layout, table structure, confidence. And it fails quietly. The output still looks clean. You find out when the data is wrong. 🧩 Full head-to-head comparison in the comments. 👇 #AIDocumentProcessing #AgenticDocumentExtraction #OCR #LLMWhisperer #Unstract #LLMs #IntelligentDocumentProcessing

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Your model never grasped the whole document. It read whatever the chunker handed it. Imagine a financial statement with lots of numbers interpreted incorrectly because of chunking issues. What appears to be a small mistake can have great consequences. 🧩 The fix? Intelligent Chunking Strategies. Check out the full article. Link in comments.👇 #Unstract #LLMWhisperer #IDP #RAG #Chunking #AIDocumentProcessing #LLMs #IntelligentDocumentProcessing

Block AI, and the work doesn't stop. It moves somewhere you can't see. That's the part missing from most "should we allow this" debates. A team is buried in claims, intake forms, discharge records. Legal says the data can't go to a hosted API, and they are right. But a backlog doesn't care who's right. So someone finds a door. A page gets pasted into a chatbot on a personal laptop. A file gets mailed to a tool nobody reviewed. A hard no relocates risk. It doesn't remove it. And it moves it somewhere with no logs, no review, and no way to reconstruct what happened. The durable answer is a sanctioned path that beats the workaround on convenience. For sensitive documents, that path exists now: capable models running as containers on your own GPUs, document processing on the same network, structured data out the other end. Nothing crosses the boundary, so nobody goes looking for a door. 🔒 Check out how to build it, end to end, on infrastructure you control: https://lnkd.in/gqTCq3kR #Unstract #LLMWhisperer #SovereignAI #AIDocumentProcessing #DataPrivacy #IntelligentDocumentProcessing

Your extraction worked. So why won't your ERP take the data? Watch us enrich data inline with Unstract's Look-Ups — no external code, no IT dependency. Register now 👉 https://lnkd.in/gkSvE-fe

🚀 Product Pulse is back! Here’s what’s new at Unstract this July: 🔹 Built-in Lookups: Clean, format, and enrich your extracted data natively before sending it to your ERP—no webhooks or complex prompt engineering required. 🔹 OpenAI-Compatible LLM Adapter: Connect seamlessly to OpenRouter, LiteLLM, or private inference endpoints following the OpenAI API spec without waiting for a custom connector. 🔹 Enterprise & Dev Upgrades: Enjoy AWS Bedrock bearer tokens, CSV/JSON log exports, full_access API permissions, and faster, streamed uploads for large files. 🔹 Better Onboarding: Get up to speed quickly with a new step-by-step onboarding guide for the Agentic Prompt Studio. Check out the video below to learn more! 🎥 #DocumentAutomation #LLMs #DataEnrichment #Unstract #ProductUpdate #AI