Repository-scale understanding
Builds structured indexes for large codebases so it can reason across files and modules.
Tabro Code is built for enterprise engineering teams. It understands repository structure, team conventions, and historical context inside IDEs, code review, and automation workflows to help complete coding, testing, fix, and review loops.
Tabro Code is designed for Enterprise Coding Agent workflows, helping enterprise teams move AI into production with stronger control and governance.
Builds structured indexes for large codebases so it can reason across files and modules.
Forms a closed loop from requirement breakdown to code edits, test execution, and result summary.
Adjusts its output style to team history, folder structure, and workflow rules.
Supports on-premise, VPC, and audit-trail setups for security-sensitive teams.
Can perform first-pass checks and propose improvements inside CI or review workflows.
Helps teams understand years of accumulated monolith code and automatically fills in regression tests and API adapters during migration.
Runs the first review pass against company rules to surface risks and convention drift earlier.
Completes initial triage, fix drafts, and validation output before a human steps in.
Combines semantic vectors, ASTs, and symbol indexes to reduce irrelevant context.
Updates indexes from commit history instead of rescanning the whole repository.
Isolates commands, tests, and builds to reduce automation risk.
Selects the right model for task complexity, balancing latency and cost.