Build better models faster with Professional Services
Build better models faster with Professional Services
Work with our team of experts to build state of the art ML models and production-ready pipelines.
Move faster with experts
Accelerate your ML process
Leverage guidance from a team of experts with decades of experience.
Leverage a team of Deep Learning experts
Need help with GPU orchestration? Working on model tuning? Having trouble scaling your ML pipeline? From research to production, our experts can help you maximize efficiency throughout the entire ML lifecycle.
Optimize for production
Our team of experts can help you adopt modern ML best practices and help increase the efficiency of your model development and deployment process.
Deliver state-of-the-art performance
Use the most advanced ML techniques, architectures, and tooling to deliver maximum performance. Our expert support encompasses any major ML framework and model formats.
Faster time-to-market
Quickly take models from the concept phase all the way to production in weeks, not months. Our experts can help you deploy quickly but effectively, so you get from data to value even faster.
Any stage
Suited for any phase of your ML journey
Start with a prebuilt package or a custom solution tailored to your specific needs.
Quickstart
Move to an advanced MLOps while leveraging the full capabilities of an end-to-end platform that is built to scale with your team.
Migration Readiness
Migrate your existing on-prem or cloud-based workloads with minimal investment and best in class implementation patterns.
Production Best Practices
Move to production with optimized network security, authentication, roles and account setup, monitoring, and data-sharing.
Any challenge
Overcome common challenges
Make better decisions with the support of trusted experts.
- How do I train & tune a model on my own data?How much training data is required? What ML architectures should I use?
- How do I decrease my training time?Learn how to scale-up & scale-out your training & inference across your compute cluster.
- How do I refine my model for minimum size & latency?From quantization to pruning, our team of experts has you covered.
- How do I move my model to a production environment?Fine-tune your compute infrastructure and build a pipeline to automate routine steps.
- How do I explain my predictions?Learn about best-in-class model observability tooling & metrics collection.
Customer Success Stories
Customer
Developing an online marketplace for AI generated images
Build
Created a process to generate images given a set of input images and chosen style. The build out included a Gradient Notebook to highlight the feasibility of the model and allow for customer iteration of the process, a Workflow to run batch inference on a set of images and store generate images in a Dataset, and a live Deployment that allows users of the platform an interactive web application to generate art from their own source images.
Libraries
Customer
Creating an interactive search engine for existing patents in the US and abroad
Build
Built out an interactive web page deployed on Gradient that allows users to search a string of text and return the most similar patents to the searched text. This process was enhanced in a 2nd phase for the client by ensuring all models were stored offline and versioned and the sentence embeddings stored in a database. The main purposes of this 2nd phase were to speed up the rate at which new embeddings could be processed and stored, decrease response times of the application, and improve startup times of new instances to allow for more responsive auto scaling.
Libraries
Customer
Creating and implementing retailer technologies for autonomous stores
Build
Supported the ML team in building out Gradient Workflows to automate multi-layered pipelines that trained individual product object detection models that were aggregated with outputted annotated videos into a wide-reaching object detection solution.