Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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$300 Free Credits to Build on Google Cloud
New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.
Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
Machinelearning server for developers and ML engineers
Apache PredictionIO® is an open source MachineLearning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machinelearning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machinelearning modeling with systematic processes and pre-built evaluation measures; support machinelearning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machinelearning models and seamlessly incorporate them into your engine; simplify data infrastructure management.
Intelligent e-knowledge base engine for any kind of knowledge-based applications, supporting effective knowledge presentation, precise knowledge search, adaptive learning and immediate consulting.
Cigol (logic, spelled backwards) is a deductive logic solver. It can be embedded inside a parent program or used from the command line. It has absolutely no relationship to Tom Mitchell's book on MachineLearning.