Trainloop is an agentic AI QA automation platform that autonomously generates, executes, and maintains tests for web and mobile applications.

How is Trainloop different from traditional QA automation tools?

Unlike script-based or AI-assisted tools, Trainloop uses fully autonomous AI agents to manage the entire QA lifecycle without manual test maintenance.

How is Trainloop 5x cheaper than legacy tools?

By using agentic reasoning to optimize execution paths and token usage, and eliminating the need for manual script maintenance, we reduce total cost of ownership by up to 80%.

Does Trainloop support web and native mobile testing?

Yes. Trainloop supports modern web applications as well as native Android and iOS mobile apps using unified agentic AI logic.

Is Trainloop suitable for startups and enterprises?

Yes. Trainloop is designed to scale from early-stage startups to large enterprise QA environments with features like SOC 2 compliance and VPC deployment.

What does agentic AI mean in QA testing?

Agentic AI refers to autonomous systems that can independently plan, execute, adapt, and optimize testing activities without human intervention or manual scripting.

The Economics of Quality: How Agentic AI Unlocks 80% Cost Savings

Most CIOs view QA as a "cost center." It's slow, expensive, and requires highly specialized SDETs who are hard to hire. By switching to an **Autonomous QA Workforce**, you turn quality into a competitive advantage.

The TCO (Total Cost of Ownership) Formula

Traditional QA Cost = (SDET Salary * Creation Time) + (SDET Salary * Maintenance Time) + Infrastructure.

With Trainloop, the formula shifts:

- **Creation Cost**: Drops by 95% (Autonomous Discovery).

- **Maintenance Cost**: Drops to near-zero (Self-Healing).

- **Execution Cost**: 5x lower through optimized token routing.

ROI Case Study: 3 Days to 30 Minutes

One of our enterprise partners was spending 3 full engineering days every sprint manually verifying their mobile checkout flow. With Trainloop, the entire suite now runs autonomously and verifies the same flows in **30 minutes**.

The Economic Result

By reducing the TCO by 80%, engineering teams can reallocate their budget from "keeping the lights on" to building new revenue-generating features.