HyperRelease vs Fastlane
Fastlane automates builds and store uploads in CI. HyperRelease is agentic-first: your AI agent prepares listing copy via MCP while Fastlane keeps handling binaries.
Tired of editing lane files or hand-pasting metadata for every locale? HyperRelease is agentic-first: your AI agent prepares App Store and Google Play listing copy through MCP, you review readiness, and HyperRelease publishes. Fastlane stays the right tool for builds, signing, and binary uploads in CI — HyperRelease does not replace it.
What Fastlane does well
Fastlane runs in CI/CD. It uploads binaries, delivers metadata from files in your repo, captures screenshots, and submits to stores — repeatably and scriptably. For engineering teams that want release steps encoded in Ruby lanes and triggered on merge, Fastlane remains the default choice.
What HyperRelease is built for
HyperRelease is built so an AI agent can operate the release object: create the version, write per-locale store fields, and update Draft / Ready / Published status via MCP. Product and marketing review in the console without touching Ruby. Connected stores receive Promotional Text, What's New, and Play Release notes through official APIs. HyperRelease does not upload .ipa or .aab files and does not run in your pipeline.
At a glance
| Criteria | Fastlane | HyperRelease |
|---|---|---|
| Agentic workflow | Scripts and lanes — not agent-native | Agentic-first — agent drafts copy via MCP |
| Runs in | CI/CD pipelines and local CLI | Agent clients + web console for review |
| Build upload | Yes — core capability | No — listing copy only |
| Metadata source | Files in repo / deliver_metadata | Release object your agent reads and writes |
| Non-engineering users | Requires repo access or handoff | Review in console; agent does the prep |
| Relationship | Technical automation for builds and uploads | Agentic content layer beside your CI |
Read more
Connect your AI agent
HyperRelease documentation
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HyperRelease vs Google Sheets for releases
Spreadsheets cannot talk to your AI agent or the stores. HyperRelease is agentic-first: your agent writes the release object via MCP, then you publish.