Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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Clazar is the leading Cloud Sales Acceleration Platform, built to help cloud GTM teams scale revenue across the AWS, Microsoft Azure, and Google Cloud marketplaces. Clazar streamlines the entire cloud marketplace sales journey, from listing and offer management to co-selling, metering, and revenue reconciliation, all from one unified platform with zero operational overhead.
With seamless integrations into Salesforce and HubSpot, Clazar enables sales, partnerships, RevOps, and finance teams to run marketplace and co-sell motions directly from their CRM. Companies can launch listings faster, create private offers in minutes, manage contracts end-to-end, and gain real-time visibility into pipeline, billing, and cash flow through powerful analytics dashboards.
With robust governance controls, enterprise-grade security compliance, and an embedded automation builder, Clazar is trusted by 300+ high-growth leaders like Pinecone, Perplexity, Confluent, Supabase, and Secureframe.
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txtai
txtai is an all-in-one open source embeddings database designed for semantic search, large language model orchestration, and language model workflows. It unifies vector indexes (both sparse and dense), graph networks, and relational databases, providing a robust foundation for vector search and serving as a powerful knowledge source for LLM applications. With txtai, users can build autonomous agents, implement retrieval augmented generation processes, and develop multi-modal workflows. Key features include vector search with SQL support, object storage integration, topic modeling, graph analysis, and multimodal indexing capabilities. It supports the creation of embeddings for various data types, including text, documents, audio, images, and video. Additionally, txtai offers pipelines powered by language models that handle tasks such as LLM prompting, question-answering, labeling, transcription, translation, and summarization.
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