MLOps

62 posts in MLOps

KitOps: A Practical Approach to Accelerating AI/ML Development to Production

In this post, we breakdown how to identify which parts of your existing infrastructure, tools, and processes can be adapted to work with AI/ML and which parts genuinely require a new approach.

ai - 8 min read

From Proprietary Data to Expert AI with Lamini and KitOps

Build AI tailored to your data. Fine-tune LLMs with Lamini and deploy securely using KitOps for maximum privacy and ease of integration.

ai - 9 min read

Critical LLM Security Risks and Best Practices for Teams

Protect your LLMs from data breaches and attacks. Explore the critical security risks and strategies to protect your models and sensitive data.

devops - 9 min read

How to Extend Your DevOps Pipeline to MLOps with KitOps

Step-by-step guide for DevOps engineers: add ML model packaging, versioning, and deployment to your existing CI/CD pipeline using KitOps. Open source.

KitOps - 11 min read

Turn Your Existing DevOps Pipeline Into an MLOps Pipeline With ModelKits

In today’s world, where almost every company is embracing artificial intelligence (AI) and machine learning (ML) into their software offering, maintaining two separate pipelines for ML-powered software systems and conventional software projects can pose challenges. This also introduces friction within the team, which can slow down the development and deployment process.

KitOps - 12 min read

From Jupyter Notebook to deployed application in 4 steps

Deploy your Jupyter Notebook effortlessly with a ModelKit. Learn the 4-step process from unpacking and fine-tuning to pushing and deploying your ML models.