GBrain vs Lenz: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of GBrain and Lenz — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

GBrain

Paid

A shared team brain that syncs memory, connected apps and scheduled skills to ChatGPT, Claude, Cursor and any AI your team uses.

Shared Team Chat: The whole team prompts in one shared chat where anyone can follow up and see how answers were worked out.
Plain-File Memory: Team knowledge lives as markdown notes in folders you can open, correct and copy, and every AI answers from the fix.
Connect Once Credentials: Connect Gmail, Calendar, Drive, Stripe and more once; AIs receive call results, never passwords.
Per-AI Permission Levels: Set each AI to Off, Read, Draft, Manage or Full per account, with every action on one record.
Scheduled Skills: One-click skills like Team Standup, Customer Comms Tracker and Inbox Cleanup run daily or once.
Multi-AI Sync: Sync the same memory to Claude, ChatGPT, Cursor, Claude Code, Codex and your terminal.
Tools Plan: A password manager for AI that puts your applications into every AI you use for individuals.

Team Standups: Summarize the team's work across GitHub, Gmail and Calendar and email it out each morning.
Customer Follow-Up: Track customers and prospects owed a reply and flag overdue ones daily.
Issue Triage: Turn customer bugs and requests from email and support chats into deduplicated tracker issues.
Meeting Prep: Build sourced briefs on candidates, guests or investors before you meet.
Inbox Cleanup: Archive mail you never read on a schedule.
Pricing Decisions: Combine call notes and billing data in a shared chat to evaluate a price change.

Lenz IO

Freemium

Audit-grade fact-checking API that runs claims through an eight-model, five-stage adversarial pipeline and returns a cited verdict.

Five-Stage Adversarial Pipeline: Eight models across five stages gather evidence, argue the opposing side, and pass through three independent reviewers before a verdict is issued.
Multi-Vendor Independence: Verdicts come from LLMs across several vendors rather than one provider, so a single model's blind spot cannot decide the outcome.
Full Citation Trail: Every verdict ships with the real sources it rests on and the reasoning shown, so a human can audit why the answer came out the way it did.
Depth Ladder of Primitives: /extract, /assess, /verify and /ask let you trade latency against rigor — a fast multi-model check for live UX, the full pipeline for anything that will be published.
Claim Extraction from Free Text: /extract pulls the individually verifiable claims out of any document or model output so each can be checked separately.
Grounded Follow-Up Q&A: /ask answers questions about a completed verification using only that verification's evidence, keeping the conversation anchored to sources.
Drop-In Integrations: OpenAPI 3.1 with Python and TypeScript SDKs plus a CLI, and ready-made hooks for Claude, Cursor, n8n and Zapier.
Public Workbench and Bookmarklet: Paste a statement, link or question and get a sourced verdict without writing code, including a bookmarklet for checking claims while browsing.

Runtime Output Verification: Check what your LLM feature just produced against real sources before it reaches a user, asynchronously or inline.
Pre-Release CI Gates: Run generated content, docs or marketing copy through /verify in CI so unsupported claims fail the build.
Incident Triage: Verify claims circulating during a live incident and get a verdict with sources instead of a confident guess.
Editorial and Newsroom Checking: Extract the checkable claims from a draft and get each one scored with citations before publication.
Compliance and Risk Review: Produce an auditable trail showing what was verified, against which sources, for regulated or high-liability content.
Agent Tool Use: Give a Claude, Cursor or n8n agent a verification tool so it can confirm facts mid-workflow rather than asserting them.