Question: I'm looking for a platform that can help me develop and deploy computer vision models efficiently, what options do you have?

If you need a platform to build and run computer vision models, Roboflow is a good option. It's got automated annotation tools, AI-boosted labeling and a range of powerful deployment choices. With access to more than 50,000 pre-trained models and integration with TensorFlow, PyTorch and other frameworks, Roboflow is good for developers and enterprises. The service also can deploy to edge and cloud computing environments, so it's flexible.

Another good choice is Viso Suite, an all-purpose computer vision foundation designed to make the AI life cycle easier. Viso Suite includes automated data gathering, annotation tools and support for several AI frameworks. It also has drag-and-drop pipeline creation and automated deployment so teams can concentrate on business results. It's secure and scalable, with a wide range of industry use cases.

If you prefer a more data-first approach, Encord offers data ingestion, processing and curation tools along with automated labeling and model performance assessment. With tools like Annotate for automated labeling and Active for monitoring and debugging models, Encord is designed to make AI development more efficient and better. The company prioritizes high data quality and security, including certifications like SOC2 and HIPAA.

Ultralytics is another interesting option, with no-code AI model generation and mobile support. With features like real-time object detection and pre-built templates, Ultralytics makes it easier to build and deploy accurate AI models. Its pricing tiers range from startups to enterprises, so it should be useful for a variety of customers.