chat-recall vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of chat-recall and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
chat-recall
chat-recall
Makes every conversation your team has had with AI coding assistants searchable, and flags secrets leaked into those chats.
Key features
- Unified Conversation Search: Full-text search across the chats, plans, task lists and notes written by five supported AI coding tools, searchable the moment they arrive.
- Local Secret Redaction: Passwords and API keys are stripped on your own computer before anything is uploaded; only the last few characters are ever received.
- Leaked Key Reporting: Shows every key found, whether it is still live, and how many conversations it appeared in, with support for custom in-house key formats you register.
- MCP Server and Recall Tools: Exposes the history to your assistants through an MCP server so they can query past work directly rather than starting cold.
- Ranked Action Plan: Derives code findings and a prioritized list of what to fix next, written out as CODE_TASKS.md.
- Self-Closing Bug Tasks: Each detected bug becomes a task with a sketched fix, and closes itself once the problem is actually gone.
- Config Distribution: Skills and MCP configuration follow you to every machine and to whichever assistant you pick up next, with a per-machine view of what is missing.
- Per-Project Rules: Mark a project as a prototype or a live product once, and every assistant that opens it plays by the matching rules.
Best for
- Credential Incident Response: Find which keys were pasted into assistant conversations, whether they are still valid, and where they spread.
- Recovering Past Decisions: Search months of AI conversations to recover a plan or rationale instead of asking the same question again.
- Onboarding a New Machine: Sign in on a new laptop and get the full conversation history and every accumulated skill without copying files by hand.
- Switching Assistants: Try a different AI coding tool without losing the add-ons and context built up in the previous one.
- Team Knowledge Sharing: Share project history selectively with teammates and assign follow-up work from a shared task board.
- Security Review Before Shipping: Run the secret monitor and code findings over accumulated history as a pre-release check.
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