AI Agents in Action: Real-Time Monitoring for Development Teams The transition from traditional SEI platforms to AI-driven solutions marks a significant shift in how engineering teams are managed By incorporating AI agents, platforms like Waydev are reshaping the industry, delivering predictive analytics, real-time monitoring, and automation that address the dynamic needs of modern software development
Evaluate ROI of Engineering Teams - docs. waydev. co Use Case: Improve Code Review Participation and Responsiveness; Understand Personal Contribution Trends; Monitor Engineering Health Over Time; Benchmark Teams and Projects Across the Organization; Evaluate ROI of Engineering Teams; Gain Insight Into the Impact of Their Work; Advocate for Career Growth with Data; Features Waydev Modules ; AI
Waydev Overview of Reviews Product Details - 2025 Waydev is an advanced solution in the Product Analytics category, designed to revolutionize how engineering performance is measured and managed By analyzing data from codebases, pull requests, tickets, CI CD activities, and even calendars, Waydev provides actionable insights into engineering processes, enabling organizations to improve efficiency, align technical efforts with business
Waydev - GitHub Marketplace Understand how engineering resources are allocated, visualize costs, and align efforts with business goals Improve team health and hygiene of your team’s practices Gain an overview of your company’s performance while identifying the challenges your teams and contributors face with Developer Experience (DX)
AI - Waydev Monitor AI adoption and performance across your organization Leverage AI Agents, predictive insights, and AI coaching to accelerate innovation, and drive measurable improvements in engineering efficiency
AI in Engineering: 6 Strategies for Effective Integration Integrating AI in Engineering requires a strategic roadmap to ensure successful adoption and scalability This involves understanding key integration strategies, such as building a strong data foundation, fostering an organizational culture that embraces AI innovation, and establishing agile workflows between data science and engineering teams