Subscribe
Sign in
- Products
- Intelec AI
- Alternatives
The best alternatives to Intelec AI are Lobe, TensorFlow, and Akkio. If these 3 options don't work for you, we've listed over 10 alternatives below.
What do you think of Intelec AI?
AssemblyAI — The most accurate API for conversational speech-to-text
PromotedBest alternatives to Intelec AI
- Lobe is an easy-to-use visual tool that lets you build custom deep learning models, quickly train them, and ship them directly in your app without writing any code.
- TensorFlow is a fast, flexible, and scalable open-source machine learning library for research and production.
- We make people who work with data more efficient. From cleaning and transforming data to building custom models and predicting future KPI outcomes, the Akkio platform is the easiest way for businesses to leverage the power AI across their operations.
- The fastest and most powerful end-to-end platform for Machine Learning and Deep Learning. Accelerate Machine Learning projects.
- Monitor ML tracks the performance of models throughout their lifecycle and connects them to business metrics. We support model tracking, metric logging/analysis/alerting and production event logging. You choose the framework, we monitor the model.
- Gauss enables any person with a smartphone and an internet connection to be a data labeler, our mobile app has unlocked a new labeler ecosystem. Our Enterprise Portal allows for Collaborative Data Labeling for Internal Projects across multiple data formats.
- Code free way to create a deep learning system. Use it to overlay marketing images, count objects, and setup custom conditions, such as alerts. Send data via email, or upload on the web. Optionally, scale deployment with your software team as your needs grow.
- As students in high school, we realised that even though it is amazing, machine learning is really difficult to implement into projects. To remove the hassle we faced ourselves, we created MLBlocks. -Train models with only 50 images per class -Create them without expensive GPUs -Deploy on any platform through our API -NO CODE REQUIRED
- No need to hire AI developers or specialists to introduce new technology and diversify your business. CLICK AI allows anyone to create deep learning-based AI models fast, with high accuracy, and without limitation by AI type/industry group.
- Deploy machine learning applications without worrying about setting up infrastructure, managing dependencies, or orchestrating data pipelines. Demo video: https://youtu.be/tgMjCOD_ufo
- Labeling AI is a deep learning-based technology that automatically labels (annotates) large amounts of data based on a small amount of pre-labeled data available, with minimal human intervention required only to review the final result.
- Boon AI converts complex machine learning integration processes into one that's agile and flexible—like software development. Build an ML pipeline in an hour and start automating your media management tasks using an ecosystem of pre-trained ML APIs.
- Deploy your model to an HTTP endpoint with a single line of code. Monitor, manage, and update your models in production with a simple Python API. Check out a demo or try it for free with a quickstart: TensorFlow or Hugging Face Transformers.
- Deploifai is a software platform that will manage all your machine learning infrastructure and deployment so that you can focus on building your AI models! Train and deploy a machine learning model with ease, all the way to production.
- No Code platform to accelerate cloud deployments, reduce risks and costs: Intuitive - Canvas, drag and drop and guided smart wizards No Code - Automatically generates the required the code Multi Cloud - Support for AWS, Azure, K8, and VMWARE.
- Optimizing ML models is not easy. Understanding and setting up different compilers, runtimes and process the models correctly for acceleration, is HARD! voltaML helps ML/DL teams accelerate their models by upto 10X using our easy low-code/no-code platform.
- Qualdo™ helps enterprises monitor mission-critical ML & data issues, errors, and quality using Advanced Data & ML Engineering.
