# AI Studio **A Platform-as-a-Service, Planck AI Studio offers its clients AI model deployment, inferencing, fine-tuning, and training services. To help any business implement custom models, we at Planck also offer advisory services for creating a custom MLOps pipeline.** *** **API Calls:** * Build AI apps with foundational models like Llama-3 and other major open-source models. * Access a vast library of pre-trained AI models, covering a wide range of tasks such as natural language processing, image recognition, and more. * Easily integrate these models into your applications through simple API calls, without the need for deep machine learning expertise. * Example: A developer building a chatbot can use the Llama-3 API to provide the chatbot with advanced language understanding and generation capabilities. * Use case: A content creation platform can leverage the API to generate personalized product descriptions or blog post summaries based on user preferences. **AI Inference:** * Deploy trained AI models to make predictions and inferences in real-time applications. Once you've trained or fine-tuned a model, deploy it to our cloud platform for efficient inference. * Receive real-time predictions and insights from your models, enabling you to build responsive and intelligent applications. * Example: A fraud detection system can use a deployed AI model to analyze transaction data and identify suspicious activity in real time. * Use case: A customer support chatbot can leverage a deployed model to understand customer inquiries and provide accurate and timely responses. **AI Training:** * Train custom AI models from scratch using large datasets and our powerful infrastructure. * Build highly tailored AI models that meet your specific needs and requirements. * Utilize our scalable cloud infrastructure to train models on massive datasets, accelerating the training process. * Example: A medical researcher can train a custom AI model to analyze medical images and diagnose diseases with high accuracy. * Use case: An e-commerce company can train a model to predict customer preferences and recommend relevant products. **AI Fine-Tuning:** * Adapt pre-trained models to specific tasks and domains for improved performance. * Start with a pre-trained model as a foundation and fine-tune it on your own data to specialize it for your use case. * This process allows you to achieve better results with less training data and time. * Example: A language translation service can fine-tune a pre-trained language model on a large dataset of parallel texts to improve the accuracy of translations. * Use case: A social media platform can fine-tune a sentiment analysis model on its user-generated content to better understand user opinions and engagement. **AI Model Hosting:** * Deploy and manage AI models on our scalable cloud platform for easy access and use. * Easily deploy your trained or fine-tuned models to our cloud platform for seamless integration into your applications. * Benefit from our scalable infrastructure to handle varying inference loads and ensure high availability. * Example: A mobile app developer can deploy an AI model to the cloud to enable real-time image recognition features on the app. * Use case: A financial institution can host a risk assessment model on the cloud to provide automated credit scoring for loan applications. {% embed url="" %}