Conductor catches user-facing web performance and accessibility issues early, prevents UX debt from piling up, and connects code health to business results.
Evaluate Conductor for your team!
Multi Agent Review Engine with built-in expert knowledge
Each PR is reviewed by a team of specialized AI agents, trained on our proprietary knowledge base built from real-world web performance and accessibility evaluations.
Unified Code Health Dashboard
See trends across projects, teams, and time. Identify recurring regressions, track improvement, and measure your code's alignment with business level goals.
Custom Business goals setting
You define your goals—like target LCP, WCAG level, or bundle thresholds, and Conductor will align its suggestions to those goals.
Developer Trusted Integration
Conductor integrates into GitHub in under 5 minutes. Actionable suggestions appear directly in your PRs—low noise, no blockers.
Conductor integrates effortlessly with your organization's LLM setup, leveraging your existing access provisions.
Whether you're hosting models through AWS Bedrock, Azure AI, directly with providers like Anthropic or OpenAI, or running open-source models like Meta's Llama on your own hardware, Conductor adapts to your needs.
Our secure design ensures Conductor operates within your environment, connecting to your tools—including LLMs—the way you choose, making it one of the best ai tools for software testing.
Conductor is currently focused and specialized for JavaScript, and TypeScript codebases. This specialization allows Conductor to write high quality passing tests for complex aspects of JavaScript and Typescript codebases.
Conductor sets itself apart as one of the best AI tools for software testing by leveraging specialized multi-agent agentic ai workflows that mimic human collaboration to create, review, and refine code. This approach delivers higher-quality tests uniquely tailored to an organization's coding standards. Unlike generic AI code generation tools like GitHub Copilot or Cursor, Conductor features automated self-healing loops, where agents independently run and iterate on tests, continuously adapting to the codebase's nuances without user intervention.
Additionally, Conductor enables teams to define specific testing guidelines and integrates with backlogs to incorporate business logic, ensuring tests align with both code correctness and underlying business requirements. This deeply customized and iterative process goes far beyond the capabilities of generic code generation tools.
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Conductor, one of the best AI tools for software testing, ensures its tests are genuinely valuable by tailoring them to the specific context of your codebase and business requirements—be they user stories, epics, PRDs, RFCs, or any combination thereof—while also aligning with your organization’s unique coding standards and practices. Unlike generic code generation tools, Conductor automatically adapts to each team’s development structure, guidelines, and preferences, and can be further refined by technical experts (like Principal Engineers) to support new practices. Through customizable multi-agent workflows, testing guidelines, self-healing loops, and backlog integrations, Conductor delivers context-aware, company-specific testing that goes beyond mere coverage metrics to ensure meaningful quality, security, and value at scale.
Conductor gathers business context in several ways. It can draw from specific business documents or files containing key information—such as PRDs, product visions, or OKRs—and it also integrates with popular backlog tools like Atlassian Jira and Microsoft Azure DevOps. This allows Conductor to automatically pull in relevant context, ensuring comprehensive test coverage that make sense for your business.
