Dagster
Dagster is the data orchestrator platform that helps you build, schedule, and monitor reliable data pipelines - fast, flexible, and built for teams.
Dagster Labs is the organization behind Dagster, the open-source project, and Dagster Cloud. We’re a small, well-funded, and collegial team with a proven track record of shipping open-source software with global adoption. We are fortunate to be able to partner with some of the best venture capital investors in the business. We are a team that is intrinsically driven and executes with fierce urgency. We think big, aim high and are here to be the best at what we do. We value grit, resilience, and are able to persevere to get to the best outcome. We play to win and we do not mistake motion for progress, striving to quickly focus in on what really matters and avoid work about work We hold ourselves to high standards and trust each other to do the same. We do not believe that quality and velocity are at odds with each other, and taking our craft seriously means we can move fast with excellence. We we do what we say we’re going to do. We work from first principles and solve fundamental problems. We provide continuous, direct, and thoughtful feedback to one another in order to improve. When failures happen, we learn from them as an opportunity to improve our future outcomes. Our workplace should reflect the full diversity of interests, backgrounds, and ideas of all of our employees. We invest in creating experiences to foster meaningful connections and encourage everyone to connect genuinely with colleagues. Building is hard and we believe it will be more sustainable, and we will have more fun when we engage authentically and inject some levity into our daily interactions. We optimize for the group, the company, and not just for the individual. We have a mutual responsibility to support one another to succeed and multiply our impact beyond the sum of our individual parts. We sometimes put aside the work that’s most important within our focus area to help with higher-priority work in other areas. We empower people to have sufficient context across the company to be able to work cross-functionally. We sometimes operate outside of our defined responsibility and never say that something is “not our job”. We act as owners, roll our sleeves up to pitch in, and fix problems and gaps that we see. We started off as an OSS project - our community has been with us the entire journey and they are the reason Dagster Labs exists. The developer experience at Dagster Labs is everyone’s responsibility. We are dedicated to doing everything we can to improve their experience working with data platforms. This means that everyone is invested in our community, their success and their sentiment towards our products. Nick is the founder of Dagster Labs. Prior to that, he was a Principal Engineer and Director at Facebook between 2009-17, where he founded the Product Infrastructure team and co-created GraphQL. Pete previously led teams at Twitter, co-founded Smyte, and was a member of the early React team at Facebook. Yuhan was a senior software engineer and tech lead o
Google Document AI
The Document AI solutions suite includes pretrained models for document processing, Workbench for custom models, and Warehouse to search and store.
Create document processors that help automate tedious tasks, improve data extraction, and gain deeper insights from unstructured or structured document information. Document AI helps developers create high-accuracy processors to extract, classify, and split documents. Seamlessly connect to BigQuery, Vertex Search, and other Google Cloud products Enterprise-ready, along with Google Cloud's data security and privacy commitments Built for developers; use the UI or API to easily create document processors Use generative AI to extract data or classify documents out of the box, with no training necessary to get started. Simply post a document to an enterprise-ready API endpoint to get structured data in return. Document AI is powered by the latest foundation models, tuned for document tasks. Also, with powerful fine-tuning and auto-labeling features, the platform offers multiple paths to reach the required accuracy. Structure and digitize information from documents to drive deeper insights using generative AI to help businesses make better decisions. Extract data from your documents using generative AI. For full product capabilities head to Document AI in the Google Cloud Console. Document AI Workbench provides an easy way to build custom processors to classify, split, and extract structured data from documents. Workbench is powered by generative AI, which means it can be used out of the box to get accurate results across a wide array of documents. Furthermore, you can achieve higher accuracy by providing as few as 10 documents to fine-tune the large model—all with a simple click of a button or an API call. With Enterprise Document OCR, users gain access to 25 years of optical character recognition (OCR) research at Google. OCR is powered by models trained on business documents and can detect text in PDFs and images of scanned documents in 200+ languages. The product can see the structure of a document to identify layout characteristics like blocks, paragraphs, lines, words, and symbols. Advanced features include best-in-class handwriting recognition (50 languages), recognizing math formulas, detecting font-style information, and extracting selection marks like checkboxes and radio buttons. Try Document OCR now for accurate text and layout extraction. Developers use Form Parser to capture fields and values from standard forms, to extract generic entities, including names, addresses, and prices, and to structure data contained in tables. This product works out of the box and does not require any training or customization and is useful across a broad range of document customization. Explore document processing with Form Parser. Try out pretrained models for commonly used document types including W2, paystub, bank statement, invoice, expense, US driver license, US passport, and identity proofing. Explore pretrained options in the processor gallery. Document AI is helping customers improve fraud detection, automate customer support, and pro
Dagster
Google Document AI
Dagster
Pricing found: $10, $100, $120, $1200, $.005
Google Document AI
Pricing found: $300, $1.50, $0.60, $6, $6
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Only in Dagster (10)
Only in Google Document AI (10)
Dagster
Google Document AI