Ambiguity slowed development cycles. Agents now reason through code reviews and refactors, saving 2,300 hours per client.
A platform providing autonomous engineering systems to enterprises employing hundreds to thousands of developers.
Inconsistent engineering practices and organizational scale create bottlenecks that slow development cycles. Legacy tools lacked the reasoning...
“As software is built and companies grow, organizational structure and engineering practices become inconsistent. It leads to bottlenecks and slowdowns. There really wasn't any one tool or system that could handle the ambiguity required to navigate the entire software lifecycle, especially one that scaled with the organization.”
AI software development agents for automating engineering workflows.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Complex tool calls broke earlier models. Claude now navigates nested data, enabling agents to drive 3-5x productivity gains for clients.
Basic autocomplete failed on large codebases. Agents now reason across files, cutting pull request cycle times by 89%.
Engineers lost hours checking dependencies. Now, AI models handle architecture and reviews, letting them focus on code.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.