CodeBurn vs Ito: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of CodeBurn and Ito — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
C
CodeBurn
AgentSeal
Free, local-first CLI and macOS menubar app that tracks AI coding token usage and cost across 36+ tools like Claude Code, Cursor, Codex, and Gemini CLI.
Key features
- Multi-tool cost tracking: Reads on-disk session files from 36+ AI coding tools including Claude Code, Cursor, Codex, Copilot, Gemini CLI, Kiro, OpenCode, and Goose and unifies them into one dashboard.
- Local-first architecture: No proxy, no wrapper, no API key, and nothing leaves the machine — everything is computed from the session files the tools already write.
- Task classification: Deterministically buckets every AI turn into categories like Coding, Debugging, Feature Development, Refactoring, and Testing without any additional LLM calls.
- Per-project and per-model breakdowns: Slices cost and token counts by project, model, tool, and task so developers can see which repos or models drive the bill.
- `codeburn optimize` grader: Grades the developer's setup A through F and flags duplicate file reads, context bloat, and ghost agents, with one command to apply the fixes and per-change undo.
- TUI and menubar UIs: Ships as both a terminal TUI dashboard for deep dives and a macOS menubar app for at-a-glance daily spend.
Best for
- Solo developer cost visibility: An indie dev running Claude Code and Cursor side by side sees which sessions burned the most tokens and adjusts their workflow.
- Team AI budget attribution: Engineering managers roll up per-project spend to attribute AI costs to specific product areas or clients.
- Debugging runaway sessions: When a coding agent burns thousands of tokens on one task, CodeBurn's classification pinpoints which turn category exploded.
- Optimizing agent setups: Running `codeburn optimize` on a laptop grades the AI setup and removes duplicate context that quietly inflates every prompt.
- Comparing model economics: Developers evaluate whether to move a task category from a frontier model to a cheaper one by looking at CodeBurn's per-model breakdown.
I
Ito
Ito
AI code review tool that builds and runs your app on every PR, catches runtime bugs, and attaches a failing test as evidence.
Key features
- Targeted Test Plans: Reads the PR diff and description on open, then focuses testing on the user flows the change affects — no test cases to write and no suite to maintain.
- Containerized Test Execution: For every PR, Ito builds a real single-use copy of your app from source and navigates it like a real user against your real backend.
- Self-Healing Codebase: Proposes a fix as its own PR for the bugs it finds so the fix loop starts before an engineer opens the ticket.
- Product Demo Videos: Posts a polished walkthrough of every change to the PR so reviewers see the feature in action, not just the diff.
- Automatic Smoke Testing: Maps each change to at-risk user journeys and builds a smoke-test plan without human authoring.
- Full PR Findings with Evidence: Every failure includes a video replay, exact lines responsible, logs, and reproduction steps, with severity ratings to prioritize.
- Auto Re-run on Fix: Push a fix and Ito re-runs the failed flows automatically to confirm the bug is resolved before merge.
- Agent Sandboxes: Gives autonomous coding agents a live, managed copy of your app to build and test against without hitting production.
Best for
- AI-Generated PR Verification: Teams whose engineers and coding agents open many PRs a day get every one built, exercised, and evidence-backed before merge.
- Catching Runtime-Only Bugs: Surface authentication, concurrency, service-authorization, and data-migration bugs a static reviewer or diff-only AI can't see.
- Removing Manual QA Bottlenecks: Reclaim the hours each developer spends manually verifying AI-written code by delegating the pre-merge runtime pass to Ito.
- Regulated & Security-Sensitive Codebases: Financial, healthcare, and defense teams get SOC 2 Type II, isolated test runs, and zero data retention on every PR.
- Enabling Agent Automerge: Give autonomous coding agents a runtime gate so they can merge safely without an added human review bottleneck.
- PR Demo Artifacts: Reviewers and PMs get a runnable video walkthrough of the feature attached to the PR instead of guessing from the diff.