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
Reducto
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Reducto's parser reads documents like a human would—capturing layout, structure, and meaning with high accuracy. Our Agentic OCR reviews and corrects outputs in real-time for near-perfect results, even on edge cases. Reducto's parser reads documents like a human would—capturing layout, structure, and meaning with high accuracy. Our Agentic OCR reviews and corrects outputs in real-time for near-perfect results, even on edge cases. Automatically separate multi-document files or long forms into individually useful units. Intelligent heuristics and layout-aware splitting keep your pipelines clean and efficient—no manual pre-processing needed. Extract structured data directly from documents with schema-level precision. Whether it's invoice fields, onboarding forms, or financial disclosures, Reducto ensures the right data lands exactly where you need it. Fill in detected blanks, tables, and checkboxes with supplied data. No bounding boxes or pre-defined templates are required; Edit dynamically identifies fillable elements regardless of document layout or format, supporting scanned PDFs, digital forms, and complex multi-page documents. Reducto helped us parse documents we previously could not because of table complexity. It's probably the only AI product that has actually worked for us. Reducto first uses layout-aware models to break down the document visually, capturing regions, tables, figures, and text. VLMs make corrections to mistakes Like a human editor, our Agentic model can detect minor mistakes and correct them, ensuring accuracy even in the most detailed cases. VLMs review Reducto's outputs Vision-language models then interpret each region in context—linking labels to values, understanding tables, and classifying segments. Everything else you need to make your data LLM-ready. Battle-tested infrastructure you can trust in production and at scale. Hands-on forward deployed support and tailored SLAs to meet your enterprise needs. Run Reducto entirely within your own infrastructure—ideal for strict security, compliance, and data residency requirements. Widely trusted by enterprises worldwide
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