Rakuten uses Anthropic's Claude Code, an agentic coding tool, across engineering; in one test it worked autonomously for seven hours on a complex vLLM implementation and achieved 99.9% numerical accuracy versus the reference method. Anthropic reports Rakuten's average time to market for new features fell from 24 working days to 5 (79%).
Reported outcomes
Outcomes are reported exactly as stated by the source; we have not independently audited them.
How it works
- Engineer assigns a complex task in natural language.
- Claude Code works through a large codebase (vLLM, 12.5M lines) with occasional guidance.
- Output is validated against a reference implementation.
Risks & compliance
- Code review and testing remain required
Editor's notes
- Source page is undated; accessed 2026-10-17.
Tools mentioned & how to build it
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Tools mentioned
- Claude & Claude Code (Anthropic)
Anthropic's models, Claude Code and enterprise plans.
Build a version yourself
- n8n
Open-source workflow automation with AI agent nodes; self-host or cloud. - Relevance AI
Build an 'AI workforce' of agents, e.g. BDR agents that research and book meetings.
Sources
“Engineering teams saw their average time to market for new features drop from 24 working days to 5 days—a 79% reduction that changed how Rakuten delivers innovation.”Rakuten accelerates development with Claude Code
Grade rationale: Named organization with quantified outcomes on the vendor's customer page. Automated check on Oct 17, 2026: 1/1 quotes and 2/2 outcome claims matched the source. Compiled by the Agent Casefile research desk (AI-assisted; see methodology). Spot an error? Request a correction.
