EyeLevel.ai的封面图片
EyeLevel.ai

EyeLevel.ai

软件开发

Denver,Colorado 790 位关注者

Build Enterprise-Grade RAG On-Prem

关于我们

The world's first APIs for enterprise-grade RAG that are accurate, secure and scalable enough for regulated industries. Trusted by Air France, Dartmouth, Samsung and hundreds more. EyeLevel's GroundX APIs: - are 50% more accurate than other platforms - run in the most secure data centers including air-gapped on prem - autoscale to any workload - built on Kubernetes and fine-tuned open source models - a vision model trained on 1M pages of enterprise data for SOTA doc understanding Talk to us at www.eyelevel.ai

网站
https://eyeLevel.ai
所属行业
软件开发
规模
11-50 人
总部
Denver,Colorado
类型
私人持股
创立
2019
领域
chatbots、AI、virtual assistants、Retrieval Augmented Generation、RAG、Agentic AI、Kubernetes、RAG On Prem、LLM、Vision Model、Insuretech、Legaltech、Fintech、Customer Support、E-Commerce和Healthtech

产品

地点

EyeLevel.ai员工

动态

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    Can your RAG on Prem do this with medical bills? We see a lot of RAG apps built on bills of some kind: medical, legal, industrial. These apps often are integrated into BPO workflows. Extracting the information correctly is mission critical. In this video we show how GroundX turns this medical bill into LLM-ready data and accurate RAG search that runs in your data center, even air-gapped or hybrid cloud.

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    Can your RAG on Prem do this? Our customers try to challenge us with very complex unstructured docs for RAG all the time. We love this example - a photograph of a boxed camera presumably pulled from a supply chain or a retail shelf. See how GroundX tackles this "document", turns into LLM ready data and accurate RAG search. The best part is you can run all of it in your private data center, even air gapped. Of course you can run it on cloud too.

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    RAG on Premises: Crazy Doc of the Day Many industrial firms have docs like this.... a product sheet, with performance tables and a schematic of the part. These documents break most RAG pipelines. Can GroundX's vision model turn this into LLM-ready data and then accurate RAG search? Let's find out. The best part is GroundX runs in your private data center, even air gapped (and of course cloud too) with enterprise grade security, scale and accuracy.

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    We're launching a new series we call Crazy RAG Doc of the Day. The concept is simple. Throw a very hard, almost insanely hard, document at GroundX and see if it can turn it into correct LLM-ready data and accurate RAG search. We're kicking it off with a good one, the dreaded Ikea test. The best part is you can run this in your own data center, even air gapped (yes it runs on cloud too).

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    Build RAG on highly complex military documents? No problem with this great demo (with code) from Akshay Pachaar. Stack EyeLevel's GroundX APIs: Doc ingest, parsing and search DeepSeek: Completion model CrewAI: Agentic framework StreamLit: UI Worth a watch. The document is really hard.

    查看Akshay Pachaar的档案

    Co-Founder DailyDoseOfDS | BITS Pilani | 3 Patents | X (187K+)

    Let's build an enterprise-grade, agentic RAG over complex real-world docs! A step-by-step guide with code. We gonna do RAG over MIG 29 (a fighter aircraft) flying manual, which includes complex figures, diagrams, and more. The video below contains the complete demo and a step by step tutorial on how to build this. Tech stack: - CrewAI for agent orchestration - EyeLevel.ai's GroundX for SOTA document parsing Primarily the app features two agents: 1?? Retriever Agent The retriever agent is responsible for retrieving the right context for the user query and is assigned a task to do so. It is powered by GroundX which I have integrated as a custom tool with CrewAI. 2?? Response Gen Agent The Response Gen Agent is responsible taking the user query and context provided by the retriever agent and generate a coherent response to the user I have shared link to all the code in comments, it's fairly easy to follow along and customise to your needs! But before that, quickly test it on your own complex document: https://lnkd.in/gvqwQBnw

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    Our co-founder Neil Katz gave the keynote at Civic Hall yesterday on how government can safely build and use generative AI. Video coming soon.

    查看Neil Katz的档案

    Building the AI economy. 4X Emmy Winner. Yes I know that's a non sequitur.

    Great time talking about how to build safe AI for government at Civic Hall today in NYC. Thanks to James Dunn and Jim Malatras for creating a great event. And yes that’s my 100% accurate portrait.

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  • 查看EyeLevel.ai的组织主页

    790 位关注者

    The World’s Most Accurate RAG—Now in Your Data Center ?? RAG (Retrieval-Augmented Generation) is reshaping how enterprises integrate private data with LLMs. But let’s be honest—most first-gen RAG tools aren’t ready for enterprise-scale demands. ?? They struggle with accuracy, can’t handle scaling without performance drops, and aren’t built to meet security requirements for on-premises or air-gapped environments. Enter GroundX RAG on Prem. ? Built for Enterprise. Powered by Open Source. GroundX is the only RAG platform designed on Kubernetes and fine-tuned open-source models. It’s ready to scale, secure, and thrive in your data center. ?? Air-Gapped and On-Prem Ready. GroundX runs fully offline, integrating with high-performance workloads using Kubernetes-native features like CPU/GPU pods and essential AI infrastructure: MySQL, Redis, OpenSearch, Kafka, and MinIO. ?? Scalable and Accurate at Scale. Unlike vector-based systems, GroundX doesn’t lose accuracy as workloads grow. In fact, it outperformed Pinecone in accuracy during a head-to-head study. Ready to bring enterprise-grade RAG into your data center? Let’s make it happen. https://lnkd.in/eVEtdBPd #AI #RAG #EnterpriseAI #Kubernetes #OnPrem #LLM

  • 查看EyeLevel.ai的组织主页

    790 位关注者

    ?? GroundX On-Prem is Here: RAG Built for the Enterprise ?? Tired of choosing between innovation and security? With GroundX On-Prem, you no longer have to. EyeLevel has officially launched the world’s most secure, scalable, and accurate Retrieval-Augmented Generation (RAG) solution, now open-source and deployable entirely on-premises. Built for industries like finance, healthcare, government, and defense, GroundX On-Prem is designed to meet the strictest security and compliance requirements—all while delivering enterprise-grade performance that just works. ?? Why it matters: ?? Keep your data 100% on-site—no external APIs. ?? Scale effortlessly to handle real-world enterprise needs. ?? Open-source flexibility for any infrastructure. As Co-Founder Neil Katz puts it: “On-prem RAG isn’t optional anymore—it’s a necessity for industries where security and compliance come first. GroundX On-Prem combines unmatched security with enterprise scalability, whether you’re in a financial institution or an air-gapped classified facility.” Ready to explore the next evolution in RAG? ?? Learn more at eyelevel.ai

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  • 查看EyeLevel.ai的组织主页

    790 位关注者

    GroundX RAG On-Prem: The Next Evolution in Enterprise Grade RAG from EyeLevel Building advanced Retrieval-Augmented Generation (RAG) systems is hard. Making them secure, scalable, and on-premises for regulated industries? That’s a whole new level of complexity. That’s why we’re thrilled to share our latest episode of RAG Masters, where we unveil something groundbreaking: ?? GroundX On-Prem — An open-source beta release that lets you deploy enterprise-grade RAG with 10 lines of code. Yes, you read that right. ?? What’s in the episode? ? The challenges of deploying secure RAG systems in healthcare, finance, and defense. ? Why air-gapped, on-prem RAG solutions are game-changers. ? A step-by-step guide to setting up GroundEx On-Prem in AWS (or any Kubernetes-based setup). ? A live demo showcasing how even small LLMs can deliver big results with the right RAG pipeline. This episode is packed with insights for anyone working on enterprise AI, secure systems, or retrieval-based LLM applications. ?? Watch the full episode on YouTube: Link in comments We’d love to hear your thoughts: Drop a comment or DM us—we’re always up for a conversation! #AI #EnterpriseAI #RAG #RetrievalAugmentedGeneration #GroundEx #Innovation #TechLeadership

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