AI for all developers
Without Featrix, predictive AI projects can take weeks or months.
Featrix changes projects into tasks.
How Featrix Works
AI for all developers
Any developer can become a machine learning powerhouse with
our "Data Science Team in a Box" solution.
Simply provide Featrix with some data and configure up one or more neural functions to run on that data and you're ready to start building AI-powered applications without having to hire a specialized team or spend a lot of time learning how to build and scale machine learning workloads. Featrix takes care of the details so you can focus on the business results.
Featrix Feeds simplifies personalization and recommendation for all apps
Simply send events and get predictions
No matter what type of application you're building, whether it's internal to a business or a consumer iPhone app, customers expect smarter applications. Featrix Feeds is a easy way to provide predictive recommendations to your customers no matter the app type with almost no work for you.
Featrix Feeds gives you a robust and easy recommendation system to enable personalization in your apps and web services without a big investment.
Simply send event streams to Featrix with a single API call and ask Featrix to provide recommendations with another API call. You can change your data formats, provide positive and negative events, and even put change event weights so that Featrix can help you achieve your business goals without the complexity of a big machine learning project.
Change AI projects into tasks
Train a model for as little as $10
We've heard the same story from every customer: Machine learning projects are fraught with risk. The cost to prepare data, connect data, and architect and operate a machine learning system is non-trivial. It requires highly specialized skills and years of experience to choose the right machine learning approaches to the right kinds of data and problems.
By leveraging the power of new generative AI techniques, Featrix lets you build robust systems directly on top of uncleaned data. Featrix provides "progressive enrichment" of its systems to let you get up and running quickly and refine the quality of your systems over time. You can get started with the data you have today instead of waiting for months to get approval for budget to clean and optimize data for machine learning experiments that frankly have an unknown ROI when you start.
Featrix untangles gnarly data into the richest statistical representations, meaning you don't have to do any feature engineering or cleaning to build a robust machine learning system.
Today, machine learning teams handle this process manually, leading to exploding budgets, project delays, and fragile results.
Now you can implement AI successfully
with the data you actually have,
not the data you wish you had.
Many data experts insist that enterprise data is in no shape to be used with machine learning due to problematic data. For traditional approaches to machine learning, they are absolutely right. Data preparation is a considerable burden and an ongoing challenge for machine learning project prototypes and production deployments. That's one of the reasons we built Featrix. Once you try machine learning with Featrix, you'll never go back to the old way of spending days or weeks messing with data.
Featrix can be controlled via API or GUI
Collaborate with coworkers, partners, consultants, customers. End-to-end management from data access to model serving. There's nothing else to buy or configure.
You can easily set up machine learning functions with Featrix in just a few clicks. You can also use our API to automate creation and manipulation of Featrix models.
Connecting data sources, collaborating with team members and monitoring your machine learning system is easy with Featrix. No separate tools are needed to build, test, and run a complete machine learning operation.
Enrich data without joining
The best way to improve model accuracy is to enrich the data, i.e., to add more data to the model that provides additional context. This usually involves doing some kind of join, which is computationally expensive, and when the data requires mapping multiple fields together that don't quite line up, it can turn into a week long project.
Featrix lets you skip over that by training an embedding space with multiple data sources. You can bring together disparate data and create models across the data sets, uncovering insights that are not directly in any single data set.
The power of embedding-based analytics lets us build this capability without the join--not only do you not do the join, but we don't either. This is a huge savings of your time and compute bill of traditional data providers.
Featrix is a new approach to machine learning
We remove the noise. Literally.
Stop guessing what might work and let Featrix figure it out
In this figure, Featrix uncovers the relationships between two variables during its learning process. These relationships will be preserved and automatically available to neural functions built on this data.
This means these functions get rich context from their input data but can be built in a straightforward manner. You can build a variety of neural functions within a project in Featrix, enabling efficiency across the group of functions. This means lower costs and greater confidence in your results.
Pretraining & Fine-Tuning
Do you have strong opinions? You're in luck. Featrix offers tons of flexibility, but you don't have to use it. You can also fine-tune the Featrix embedding models for your own specific needs, as well as train models on a subset of the embedding space.
Controlled spend
No one wants a surprise bill. You can set a budget when creating your machine learning models and ensure your training never exceeds that budget. If you want more accuracy, simply apply more budget to the model and Featrix will pick up where it left off before.
With Featrix, your bill is always predictable and never exceeds what you configure.
Multi-modality enrichment
Featrix's underlying use of vectors enables you to combine embeddings from other systems into one unifying representation. You can connect other embeddings, use standard open source models, provide your own, and more. Featrix handles all the versioning, semantics, and management of the vector space.
So Easy to Use Your Boss Could Do It
But maybe we'll keep that between us.
"… we changed to the Featrix approach and let our model figure out what matters. [We had] remarkable improvement in the model. And what I like best is we no longer have to hand engineer all these features and track them and so forth."
— Sr Staff Machine Learning Engineer, Fortune 200
Get a demo. Stay in touch.
Data scientist? ML engineer? ML manager? We're all ears. We'd love to show you how we are helping teams cut costs and improve their ML project ROI. Send us an email at hello@featrix.ai or reach out with this form.