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SnapLogic delivers intelligent automation that connects your enterprise and unlocks the power of your applications and data. The company`s leadership in intelligence-powered workflows and self-service integration capabilities make it fast and easy for organizations to manage all their application integration, data integration, and data engineering projects on a single, scalable platform. Hundreds of Global 2000 customers – including Adobe, AstraZeneca, Box, GameStop, Verizon, and Wendy`s – rely on SnapLogic to automate business processes, accelerate analytics, and drive digital transformation. SnapLogic was founded by data industry veteran Gaurav Dhillon and is backed by blue-chip investors including Andreessen Horowitz, Capital One, Ignition Partners, Microsoft, Triangle Peak Partners, and Vitruvian Partners.
Pillittieri is a Jamestown, NY-based company in the Software and Internet sector.
Sed-It is a Louisville, KY-based company in the Software & Internet sector.
Fictiv offers manufacturing agility and speed through a portfolio of optimized manufacturing processes for hardware companies of all sizes. Its digital manufacturing ecosystem combines an easy-to-use cloud platform; design, quoting, billing and logistics systems; and an intelligent orchestration engine that manages a network of highly vetted and monitored manufacturing partners that together deliver high-quality mechanical parts at unprecedented speeds. The ecosystem is supported by “boots-on-the-ground” experts to manage programs, inspect quality, and provide DFM guidance along the way. Over the last six years, Fictiv has manufactured more than 10M parts for early-stage companies and large enterprises alike, helping them innovate with agility and increase supply chain predictability.
Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb to focus on building differentiated models vs. labeling data.