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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Sendbird
Sendbird provides AI-powered omnichannel communication solutions, including AI agent for customer service, Chat API, and Business Messaging for seamless customer conversations across mobile apps, websites, social media, and more. Our platform supports iOS, Android, JavaScript, Unity, and .NET.
Sendbird’s AI Agent Platform enables businesses to automate customer support across a wide range of channels, including SMS, web, mobile apps, and social media. This solution leverages AI to provide proactive, continuous support by anticipating customer needs and engaging them on their preferred platforms. Businesses can build and manage their own AI agents with an easy-to-use interface, ensuring smooth customer interactions. The platform integrates seamlessly with existing systems, providing businesses with insights into customer conversations, improving agent performance, and offering reliable support in high-traffic environments.
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Agency
Agency specializes in assisting businesses in the development, assessment, and oversight of AI agents, brought to you by the team at AgentOps.ai. Agen.cy (Agency AI) is at the forefront of AI technology, creating advanced AI agents with tools such as CrewAI, AutoGen, CamelAI, LLamaIndex, Langchain, Cohere, MultiOn, and numerous others, ensuring a comprehensive approach to artificial intelligence solutions.
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Agno
Agno is a streamlined framework designed for creating agents equipped with memory, knowledge, tools, and reasoning capabilities. It allows developers to construct a variety of agents, including reasoning agents, multimodal agents, teams of agents, and comprehensive agent workflows. Additionally, Agno features an attractive user interface that facilitates communication with agents and includes tools for performance monitoring and evaluation. Being model-agnostic, it ensures a consistent interface across more than 23 model providers, eliminating the risk of vendor lock-in. Agents can be instantiated in roughly 2μs on average, which is about 10,000 times quicker than LangGraph, while consuming an average of only 3.75KiB of memory—50 times less than LangGraph. The framework prioritizes reasoning, enabling agents to engage in "thinking" and "analysis" through reasoning models, ReasoningTools, or a tailored CoT+Tool-use method. Furthermore, Agno supports native multimodality, allowing agents to handle various inputs and outputs such as text, images, audio, and video. The framework's sophisticated multi-agent architecture encompasses three operational modes: route, collaborate, and coordinate, enhancing the flexibility and effectiveness of agent interactions. By integrating these features, Agno provides a robust platform for developing intelligent agents that can adapt to diverse tasks and scenarios.
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