Nomic Atlas

Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.

AtlasMap is a data mapping solution with interactive web based user interface, that simplifies configuring integrations between Java, XML, CSV and JSON data sources. You can design your data mapping with AtlasMap Data Mapper UI canvas, and then run that data mapping via runtime engine. In addition to plain Java API provided by runtime engine, camel-atlasmap Component is also available to perform data mapping as a part of Apache Camel route. There is also a Camel Quarkus extension available. The easiest way to use AtlasMap Data Mapper UI is the standalone mode. Or you can use it through a VS Code plugin. Historically, the AtlasMap Data Mapper UI was designed to work within Syndesis UI and it’s still a best way to experience full benefits of integrated typed data mapping with UI. You can install and run Syndesis by following the Syndesis Developer Handbook. You will find the AtlasMap Data Mapper UI under the integrations panel after selecting or adding an integration with a Data Mapper.