Atlaso vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Atlaso and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Atlaso
Atlaso Labs
Shared AI memory layer that lets Claude Code, Cursor, Codex, Claude Desktop, OpenCode, and Antigravity read and write from one persistent memory.
Key features
- Cross-Tool Shared Memory: One persistent memory that Claude Code, Cursor, Codex, Claude Desktop, OpenCode, and Antigravity read from and write to automatically.
- Automatic Capture & Recall: Facts, decisions, and preferences are captured as you work and recalled by whichever AI tool needs them next.
- Conflict Resolution: Repeated facts, contradictions, and confidence are tracked so the memory knows what's settled vs. what's still open.
- Memory Health Dashboard: Web dashboard shows memory power, breadth, agreement percentage, and buckets memories as Helpful / Caution / Open / Warnings.
- Personal + Per-Project Scopes: Separate personal and per-project memory scopes keep unrelated contexts from bleeding into each other.
- Secrets Scrubbed Before Storage: Secrets are stripped before anything is written to the shared memory layer.
- One-Line Install: Single curl-based installer for macOS, Linux, and Windows Terminal.
Best for
- Multi-Tool Developers: Engineers who bounce between Claude Code, Cursor, and Codex stop re-explaining project context in every session.
- Long-Running Projects: Teams keep decisions like 'launch moved from January to March' visible to every AI tool without a status doc.
- Personal Preferences: One-time preferences ('Sarah prefers async standups', 'demo day is first Friday') stick across tools.
- Onboarding New Tools: When you add a new AI tool, it inherits everything your other tools already know.
- Reducing Hallucinated Facts: Contradiction tracking flags outdated facts (like 'old pricing deck still in circulation') so tools don't reuse them.
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