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AI Innovation: New Relic, Snyk, and DataRobot Unveil New Offerings

In the fast-evolving landscape of software development and AI, leading technology companies continue to introduce advancements aimed at enhancing productivity, security, and the development of intelligent systems. Recent announcements from New Relic, Snyk, and DataRobot highlight key developments in AI-assisted workflows, platform security, and framework innovation for agentic AI.

New Relic Integrates with GitHub Copilot

New Relic has revealed a significant new integration designed to streamline the monitoring and remediation of code deployments. This integration connects New Relic’s observability platform with GitHub Copilot’s coding agent, creating a more connected and automated workflow for developers.

The core functionality revolves around automatic issue detection following code deployments. New Relic’s intelligent observability technology is leveraged to monitor changes and identify any problems that may arise as a direct result of these new deployments.

When an issue is detected, New Relic takes proactive steps by automatically creating a new GitHub issue. This issue is populated with relevant contextual information gathered by the monitoring system. This contextual data is crucial for understanding the nature and source of the problem.

The process is further automated by allowing developers to assign the newly created GitHub issue directly to the GitHub Copilot coding agent. GitHub Copilot can then analyze the issue using the provided context, assist in drafting a potential solution, and even prepare a draft pull request for the developer to review and finalize.

Manav Khurana, chief product officer at New Relic, commented on the strategic importance of this integration. “With the innovative integration of New Relic’s intelligent observability technology with GitHub Copilot coding agent, we are closing the loop on ensuring continued application health,” Khurana stated. He emphasized the collaboration with GitHub, a long-time partner, in delivering this new approach to modern software development. This integration leverages the power of agentic AI, aiming to transform how enterprises approach innovation by providing an intelligent, automated assistant within the development workflow.

This integration represents a step towards more autonomous systems in software development, where monitoring tools can not only identify problems but also initiate the troubleshooting process with AI assistance. It aims to reduce the manual effort involved in detecting, diagnosing, and fixing post-deployment issues, potentially accelerating the feedback loop and improving overall application stability.

Snyk Introduces the AI Trust Platform

Snyk, a leader in developer security, has launched the Snyk AI Trust Platform, specifically designed to help software development teams address and mitigate business risks associated with working with AI technologies. As AI adoption grows within development practices, new security challenges emerge, requiring specialized tools and frameworks. The AI Trust Platform is Snyk’s answer to this evolving need.

The platform encompasses several key features and components aimed at providing comprehensive security support for AI-driven development:

AI Assistant for Security Intelligence: This feature provides developers with security intelligence recommendations, likely leveraging AI itself to analyze code and potential vulnerabilities relevant to AI applications and frameworks.
Suite of AI-Powered Security Agents: The platform includes various security agents that utilize AI capabilities. These agents are designed to identify and address security concerns specific to AI models, data, and the surrounding application infrastructure.
AI Governance Solution: To ensure responsible AI development, the platform offers a governance solution that helps deploy and enforce guardrails throughout the AI development lifecycle. This is critical for maintaining compliance and ethical standards.
Framework for Building and Maturing an AI Strategy: The platform provides a structured framework to assist organizations in developing and advancing their overall AI strategy, integrating security considerations from the outset.
Partner Integration via Snyk’s MCP server: The platform is designed with an open architecture, allowing Snyk’s partners to integrate the platform’s capabilities into their own offerings using Snyk’s MCP server. This promotes a wider ecosystem of secure AI development tools.

Danny Allan, chief technology officer at Snyk, expressed confidence in the platform’s potential impact. “I’m confident that the Snyk AI Trust Platform will be a gamechanger for global organizations looking to further invest in AI-driven development,” Allan remarked. He drew an analogy to aviation, stating that just as autopilot didn’t replace the need for actual pilots, Snyk envisions AI augmenting developers rather than fully replacing them. Allan asserted that Snyk is uniquely positioned to assist with the near-term strategic and practical adoption of AI by ensuring security is built into the process from the very beginning.

The Snyk AI Trust Platform addresses the increasing complexity of securing applications that incorporate AI components. By providing tools for vulnerability scanning, governance, and strategic planning specifically tailored for AI, Snyk aims to empower developers to build and deploy AI applications securely and responsibly, reducing the potential for exploitation and misuse.

DataRobot Introduces syftr Open Source Framework

DataRobot has announced the launch of syftr, a new open-source framework specifically designed to aid developers working with agentic AI systems. Agentic AI refers to systems composed of multiple AI agents that interact and collaborate to achieve complex goals. Developing such systems requires careful selection and configuration of various components.

Syftr is built to tackle the challenge of discovering and implementing the optimal combination of elements for agentic AI workflows. These elements include components, parameters, tools, and overall strategies. Developers can utilize syftr to evaluate the performance and suitability of any specific module, data flow, embedding model, or large language model (LLM) within their agentic architecture.

According to the company’s announcement, syftr addresses a critical need as organizations increasingly explore and implement agentic AI systems. Practitioners and developers need efficient methods to quickly evaluate the latest technologies and ensure their agentic workflows are optimally performant for specific use cases. This optimization must consider multiple factors, including the quality of the underlying models, computational cost, and the desired behavior of the AI agents.

The framework achieves this through a groundbreaking multi-objective approach. It rapidly simulates various possible configurations of the agentic system. By simulating different combinations of components and parameters, syftr can identify the best AI workflows for enterprise data. The optimization process takes into account multiple objectives simultaneously, aiming to balance task accuracy, latency, and operational cost.

The open-source nature of syftr means it can benefit from community contributions and widespread adoption, potentially becoming a standard tool for building and optimizing complex agentic AI systems. By providing a systematic way to evaluate and select components, syftr aims to accelerate the development process and improve the reliability and efficiency of agentic AI applications in real-world enterprise scenarios. This initiative by DataRobot underscores the growing importance of structured approaches and specialized tools for building the next generation of AI systems.

These three announcements from New Relic, Snyk, and DataRobot collectively point to the increasing integration of AI into the software development lifecycle itself, focusing on automation, security, and the practical challenges of building sophisticated AI applications.