Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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ERA EHS Software
ERA Environmental Software Solutions provides a cloud-based EHS management platform designed to streamline compliance, sustainability, and chemical management for manufacturers. ERA’s software helps organizations manage complex regulatory requirements across air, water, waste, and refrigerant emissions. The platform supports comprehensive reporting for programs like TRI, NPRI, Title V, and NEI. Its SDS Authoring solution enables rapid generation of safety data sheets in more than 40 languages, with built-in support for GHS, OSHA, WHMIS, and REACH compliance. Health and safety tools include incident tracking, training management, and audit-ready documentation. ERA’s sustainability module tracks Scope 1, 2, and 3 emissions, providing the data infrastructure needed for ESG reporting and long-term sustainability planning.
ERA's software is also SOC 2 Type II certified, ensuring enterprise-grade security, data integrity, and over 99.6% platform uptime. Its proprietary automation framework and database of over 216,000 curated chemical records powering automated hazard classification and chemical inventory control allows clients to reduce manual data entry, improve reporting speed, and guarantee compliance accuracy. With modular architecture and industry-specific configurations, ERA serves various industrial sectors, including automotive, aerospace, chemicals, oil and gas, coatings, and furniture manufacturing.
ERA boasts Fortune 100 and Fortune 500 clients while also offering a fair pricing strategy and modular design that have allowed the company to become the market leader for small and medium businesses.
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Perst
Perst is an open source, dual-licensed object-oriented embedded database management system (ODBMS) created by McObject. It comes in two versions: one designed as an all-Java embedded database and another tailored for C# applications within the Microsoft .NET Framework. This database system enables developers to efficiently store, sort, and retrieve objects, ensuring high speed while maintaining low memory and storage requirements. By utilizing the object-oriented features of both Java and C#, Perst showcases a significant performance edge in benchmarks like TestIndex and PolePosition when compared to other embedded database solutions in Java and .NET. One of its standout capabilities is its ability to store data directly in Java and .NET objects, which eliminates the need for translation typical in relational and object-relational databases, thereby enhancing run-time performance. With a compact core comprised of only five thousand lines of code, Perst demands minimal system resources, making it an attractive option for resource-constrained environments. This efficiency not only benefits developers but also contributes to the overall responsiveness of applications utilizing the database.
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Gilhari
Gilhari is a microservice framework that provides persistence for JSON objects in relational database. This microservice framework is available as a Docker image and can be configured according to an app-specific object or relational model. Gilhari exposes REST (Representational State Transfer) interface for APIs (POST/GET, PUT and DELETE ) to perform CRUD (Create. Retrieve. Update. Delete) operations on app-specific JSON objects.
Here are some highlights from Gilhari:
* Metadata driven, object model independent and database agnostic framework
* Easily customizable/configurable to your JSON object model
* JSON attributes can be mapped to table columns, allowing full query capabilities as well as optimizations
* Supports complex object modeling, including 1-m, 1-m and m-m relationships
* No code is required to handle REST APIs (POST/GET, PUT/DELETE), data exchange (CRUD), or database schema creation.
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