Baseten Blog | Page 13
New in July: A seamless bridge from model development to deployment
We've launched Truss, an OSS Python package for model serving and deployment. Baseten users have been using it unknowingly, now offering new capabilities.
New in June: Full-stack superpowers
Excited to highlight this month's major strides in empowering data scientists to create and maintain full-stack applications with real value.
Four ML models that accelerate content creation
Philip Kiely, our technical writer, demonstrates four tasks in his content creation process, highlighting models that enhance speed and quality of work.
New in May 2022: Off-site but on-track
In late April, we launched Baseten's public beta and new brand, now focusing on learning and enhancing the product for beta users like you!
Go from machine learning models to full-stack applications
Introducing Baseten, an ML Application Builder for Data Scientists
Announcing our Series A
Ending 2019, we founded Baseten to tackle challenges we faced in building ML models in various roles at big and small companies.
Create an API endpoint for an ML model
When you deploy a model on Baseten, you can call it via an API endpoint with zero configuration.
Baseten achieves SOC 2 Type 1 certification
In March, Baseten completed a rigorous audit by Sensiba San Filippo LLP, a leading CPA firm, to achieve SOC 2 Type 1 certification
How Baseten is using "docs as code" to build best-in-class documentation
"Docs as code" uses code tools/practices for documentation, easing engineers' contributions, enhancing quality, and saving time.
