Mobile development, wherever your agent runs.

Coding agentFix saved recommendation state
Running
Implement the change, build it with Xcode, exercise the affected flow, and return verification evidence.
Code changed0:42
Xcode build passed1:08
Flow replayed in live simulator1:26
Capturing verification evidencenow
Change verified18 simulator actions · screenshot and recording attached
Live simulator
9:41● ▰
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Building a native iOS app in Windows with Linor in Codex

Build and operate

Agent-native mobile development

Coding agents are pretty good at writing code. But completing mobile development tasks still requires someone to open Xcode, run the app, inspect its behavior, and determine whether the change actually worked.

Linor gives agents the native iOS development tools they need to complete tasks end-to-end. Build, run, and verify iOS apps from the coding tools you already use, including Claude Code, Cursor, and Codex, on Windows, Linux, or macOS.

Fixing iOS bugs with Linor in Claude Code

AUTOMATE TASKS

Create async mobile workflows that run 24/7.

Turn mobile development tasks into workflows that run without someone standing by. With Linor, agents can reproduce crashes, verify fixes in the simulator, and open PRs backed with evidence.

A Jira issue is marked Ready. The agent implements the change, verifies it in the simulator, and opens a draft PR with evidence.

Learn and improve

Turn every run into reliability intelligence.

Linor turns multiple builds into shared intelligence. It captures logs and tests, connects patterns across runs, and proactively proposes fixes for issues that keep resurfacing.

Explore Linor for your team
Linor Insights dashboard showing recurring failures, controlled runs, investigations, and verified repairs
Detect

Find repeated failures

Group failures across builds, devices, tests, and app flows before another run wastes time.

Investigate

See the full sequence

Follow the run, evidence, logs, and agent actions that led from failure to diagnosis.

Repair

Propose high-impact fixes

Rank recurring failures by impact, then automatically propose a pull request for the highest-impact repair with diagnosis and verification evidence.

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