Archestra Integrations

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.

Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.

Jira is the only project management tool you need to plan and track work across every team. Jira by Atlassian is the #1 software development tool for teams planning and building great products. Trusted by thousands of teams, Jira offers access to a wide range of tools for planning, tracking, and releasing world-class software, capturing and organizing issues, assigning work, and following team activity. It also integrates with leading developer tools for end-to-end traceability. From short projects, to large cross-functional programs, Jira helps break big ideas down into achievable steps. Organize work, create milestones, map dependencies and more. Link work to goals so everyone can see how their work contributes to company objectives and stay aligned to what’s important. Your next move, suggested by AI. Atlassian Intelligence takes your big ideas and automatically suggests the tasks to help get it done.

Confluence by Atlassian is a leading content collaboration software for modern teams. It empowers teams to create, share, and collaborate on projects in one place, easily publish and access company information, capture, store and grow team's knowledge, and so much more. Confluence is also available on mobile, enabling teams to track team activity, give feedback, and stay in sync regardless of device.

OpenAI’s mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity. We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome. Apply our API to any language task — semantic search, summarization, sentiment analysis, content generation, translation, and more — with only a few examples or by specifying your task in English. One simple integration gives you access to our constantly-improving AI technology. Explore how you integrate with the API with these sample completions.

Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.

Anthropic is an AI research and technology company focused on building safe, reliable, and advanced artificial intelligence systems. It is best known for developing the Claude family of AI models, designed for reasoning, coding, and enterprise applications. The company emphasizes AI safety and alignment, ensuring that its systems behave predictably and responsibly. Anthropic’s models are used across industries for tasks such as content creation, analysis, and automation. It develops both consumer-facing tools and enterprise AI solutions through APIs and integrations. The company collaborates with major cloud providers to make its models widely accessible. Anthropic also invests heavily in research to improve AI transparency and controllability. Overall, it aims to create powerful AI systems that are both useful and trustworthy.

Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.