Constructor.io is the only search and product discovery platform tailor-made for enterprise eCommerce where conversions matter. Constructor's cloud-based solutions use natural language processing, machine learning-enhanced results ranking, and collaborative personalization to deliver powerful user experiences across all facets of product discovery -- from search to browse, recommendations, and autosuggest. We optimize revenue before relevance. This has allowed us to generate consistent $10M+ lifts for our customers, which include some of the biggest brands in retail like Sephora, Backcountry, Tommy John, and Walmart companies Jet.com and Bonobos. Constructor is a U.S.-based company that was founded in 2015 by Eli Finkelshteyn and Dan McCormick.
CrateDB is an industrial-grade database extending the limits of traditional time-series databases. Large-scale machine data poses challenges other time-series databases can’t meet — the need to scale volume and variety while running aggregated complex real-time queries, anywhere. All without driving up costs. CrateDB has a different approach while keeping the familiar SQL interface. Rather than optimizing transactional architectures, CrateDB is optimized for efficiency, scale, & real-time thanks to its eventual consistency model.
DataCebo develops synthetic data libraries to generate data for simulations. It also offers multiple machine-learning models, benchmarking, and evaluation frameworks to help businesses incorporate synthetic data into their workflows.
Domino Data Lab empowers data science teams with the leading, open data science platform that enables enterprises to manage and scale data science with discipline and maturity. Model-driven companies including Allstate, Dell Technologies, and Bayer use Domino as a data science system of record to accelerate breakthrough research, increase collaboration, and rapidly deliver high-impact models.
EnsoData is a startup that utilizes artificial intelligence to analyze the human body to diagnose health conditions. EnsoData, whose software uses machine learning algorithms to help clinicians score sleep data and diagnose patients with sleep apnea and other disorders, has now realized that dream—and then some. EnsoData's autoscoring algorithm combines AASM scoring best practices with cutting edge machine learning algorithms that learn and adapt to every single patient.