Case Studies
Accelerating Data Access and Collaboration
View studyNational Resilience, Inc. (Resilience) is a manufacturing and technology company that uses Quilt Data to manage and share data from its research sites, enabling scientists to access data faster and collaborate more effectively. By using Quilt's deep indexing and free-text search capabilities, Resilience can easily browse and access data from over 100 instruments and 10 million files in Amazon S3. The Quilt API also helps Resilience track data and intellectual property as it moves from research and analysis to downstream, GXP, and manufacturing processes.
Improving Data Management and NextFlow
View studyTessera Therapeutics is a pioneer in gene writing, using technology to insert messages into genomes to treat diseases. The company needed to manage and share more than 12 terabytes of scientific data across large teams of wet scientists and computational biologists. To address this, Tessera implemented Quilt Data and Nextflow to ensure that data was findable, accessible, interoperable, and reusable (FAIR) and to accelerate its gene-writing discoveries to market.
Exploring Data for Single Cell Genomics Research
View studyCelsius Therapeutics is using Quilt Data to manage and access data for single cell genomics research in the areas of cancer and autoimmune disease. Quilt helps Celsius maintain full versioning of its data sets and track data down to specific attributes and characteristics. The company has used Quilt to scale from a startup to production, uniformly access all its data types, and build apps to meet the specific needs of scientists.
Contextualizing Sound Data Management
View studyDSP Concepts is the global leader in embedded audio technology and creator of Audio Weaver, the audio development platform that makes audio innovation easy. DSP Concepts equips engineers with real-time workflows to quickly stand up prototypes, collaborate and modify designs across teams, and deploy to the most popular chipsets.
-
There were some big players, but they all required that you commit to their way of doing things. And they'll also take your million dollars. We knew we were going to want to do things exactly the way we wanted to. You guys care about the right things. You have the customer's best interest in mind, and you're very responsive. It's a good investment, instead of trying to build it in house.
Greg Desmarais
Senior Director, Data & Software Engineering at Celsius -
Quilt allows us to easily browse through millions of files stemming from our research sites, either programmatically or through the web app. It also allows us to frontend the data to users, without compromising on the key engineering efforts behind the scenes to provide file version control, immutability, and organizational efficiency. Leveraging Quilt Packages, users may also add custom analytics & visualizations and collaborate seamlessly to create well-structured data products shared across the company.
Adam Mendez
Associate Director of Data Engineering at Resilience -
Quilt provides Resilience with the optimal Scientific Data Management System that enables one-click access to data with a snappy and intuitive GUI. The contents of our data are deep-indexed allowing us to free-text search millions of files, with the results returned instantaneously. The Quilt API allows us to automatically post the raw data links back to our electronic notebook for a given experiment ensuring data traceability and capturing precious intellectual property.
Brian McNatt
Director of Digital R&D at Resilience -
The advantage of Quilt is data versioning, because we can link to the exact and correct version of any analysis. We adopted Quilt right after adopting Nextflow Tower, to create a better DevOps environment. So for us, Quilt was part of the data maturity process. Now we can really trust the data, and share it with the scientists directly.
Yohann Potier
Director of Data Platform at Tessera Therapeutics
Quilt is an Advanced AWS Technology Partner
Quilt Data is an AWS Advanced Technology Partner. Quilt brings seamless collaboration to Amazon S3 by connecting people, pipelines, and machines using visual, verifiable, versioned data packages. Amazon Web Services provides secure, cost-effective, and scalable big data services that can help you build a Data Lake to collect, store, and analyze massive volumes of heterogeneous data.