Description
Aidealy is a comprehensive platform designed to measure the real productivity of R&D workforces, encompassing both human engineers and AI agents, based on the code they actually ship to production. It addresses the challenge of gaining visibility into software development in the AI era, where traditional metrics often fall short.
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The platform offers four key lenses to analyze R&D performance: code quality, AI usage and cost, and code review efficiency. It calculates a "Productivity Rank" and a "Code Quality Score" by evaluating merged code, weighing it by quality, and penalizing fixes made soon after deployment. It also assesses code review contributions, crediting thoroughness and penalizing delays or approvals of broken code. Aidealy tracks the breadth of work across languages and repositories, and measures how effectively AI is utilized in the editor, though the primary focus remains on shipped code.
Aidealy connects to various data sources, including Git providers (GitHub, GitLab, Bitbucket, Azure DevOps) for commits, pull requests, reviews, and bot-versus-human detection. It also integrates with Cursor and Claude Code editor extensions to capture AI-assisted coding signals, such as prompts, responses, diffs, accepts, rejects, and token usage per session by model. This allows for a detailed understanding of AI's impact on development, separating AI-written code from human-typed code based on tool records, not statistical guesses.
The platform provides insights into delivery bottlenecks by analyzing review timing, including time to first review, time to approval, and time to merge. It helps identify which reviewers and teams keep delivery moving and where processes might be stalling. Aidealy also classifies AI-assisted sessions by area (backend, frontend, tests), purpose (planning, debugging, writing tests), and concerns (security, performance, cost), enabling leaders to understand how their teams are actually using AI.
Aidealy offers transparent per-seat pricing with a single plan that includes all features, regardless of team size. Pricing is tiered for human engineers, with volume discounts applying automatically as headcount grows. AI agents, Chat users, and Admin seats have flat rates. A one-time backfill charge loads historical Git, Cursor, and Claude Code data, providing immediate value from day one. The service is cloud-based, with data residency options in the EU or US, and emphasizes robust security measures including per-tenant isolation, dedicated encryption keys, and SSO, with a program designed to meet SOC 2, ISO 27001, ISO 42001, and GDPR requirements. It is built for engineering leadership, with access controlled via named chat seats, ensuring sensitive data is not broadly exposed to engineers.
- CategoryAI Code Review & Testing
- Pricing ModelPer-seat
- DeploymentCloud
- PlatformsWeb
Aidealy's Core Features
Measure developer productivity for human engineers and AI agents
Analyze code shipped to production, weighed by quality
Track code review contributions and efficiency
Assess breadth of work across languages and repositories
Monitor AI usage effectiveness in editors (Cursor, Claude Code)
Generate Productivity Rank and Code Quality Score
Identify delivery bottlenecks in code review processes
Track AI spend by model and engineer
Separate AI-written code from human-written code
Connects to Git providers (GitHub, GitLab, Bitbucket, Azure DevOps)
Integrates with Cursor and Claude Code editor extensions
Provides hands-on hours per pull request
Offers per-contributor breakdown of work and AI usage
Supports natural language queries for R&D insights
Ensures per-tenant data isolation and encryption
How to use Aidealy?
Connect Git Provider: Link your GitHub, GitLab, Bitbucket, or Azure DevOps account through the Aidealy admin web app.
Install Editor Extensions: Deploy the Aidealy extension for Cursor and a background program for Claude Code to your developers' IDEs.
Load Historical Data: Allow up to 24 hours for Aidealy to load and enrich your past Git, Cursor, and Claude Code history (default 1 year).
Ask Questions: Begin querying your R&D data in plain English to get immediate answers and insights.
Analyze Performance: Use the platform to understand team productivity, code quality trends, AI usage, and delivery bottlenecks.
Optimize Workflows: Leverage insights to improve code review processes and maximize the value of AI coding tools.
Aidealy's Use Cases
- Measure Developer Productivity
- Assess Code Quality
- Optimize Code Review
- Understand AI Tool ROI
- Identify Delivery Bottlenecks
- Analyze AI Usage Patterns
- Credit Engineer Contributions
- Improve R&D Visibility
