Ito vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Ito and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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.
sizeless
sizeless
Turns a smartphone video of an open trench into a centimetre-accurate 3D point cloud, CAD as-built plan and GIS-ready digital twin of buried utilities.
Key features
- Smartphone capture: Field crews record an open trench with a standard iPhone Pro — no specialist scanning hardware and no separate surveying appointment
- Centimetre-accurate point clouds: Reconstruction algorithms developed at ETH Zurich build a high-resolution 3D point cloud of the excavation from the video alone
- Standards-compliant CAD output: Generates as-built plans in DWG and DXF, with couplings and pipe runs identified and measurements simplified
- 3D digital twin and GIS export: Produces a model of the pipe route including building entries that drops into existing GIS systems
- Works without GPS: Captures basement sections and building entry points where GNSS-based surveying fails
- Immediate backfilling: Because capture takes minutes, trenches close right after filming instead of waiting on a survey crew
- Documentation in about 72 hours: Complete records arrive weeks earlier than conventional surveying, enabling prompt connection billing
- Third-party utility capture: Records crossing utilities and as-laid geometry as unbroken 3D evidence, replacing hand sketches
Best for
- A utility network operator documenting residential service connections without booking a surveyor for every site
- A contractor closing a trench the same day instead of leaving it open pending a survey appointment
- Capturing a building entry point in a basement where GPS-based surveying cannot get a fix
- A district heating project producing as-built DWG plans for regulatory sign-off
- Spotting a laying error in the 3D point cloud before backfilling, while the fix is still cheap
- Feeding as-built pipe geometry into a GIS system for long-term network maintenance planning