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

A side-by-side comparison of GBrain and Radar — 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.

Particle (Mina Labs, Inc.)

Paid

A podcast search engine and API that transcribes 130,000+ shows so people and AI agents can search, quote and monitor what was actually said.

Semantic Podcast Search: Query 130,000+ transcribed shows by topic, company or person and get back the exact passage rather than a whole-episode match.
Timestamped Clip Extraction: Radar pre-selects notable, self-contained clips with timestamps so you can listen to or read a specific moment without the full episode.
Entity Recognition and Tracking: Speaker labels plus tagged people, companies, brands, products and topics let you follow a single entity across the whole podcast corpus.
Configurable Alerts: Mention alerts arrive by email, Slack or webhook in real time or as a daily or weekly digest, filterable by guest, topic or top-podcasts-only.
Podcast Ad Search Engine: Find every episode where a given company advertises and track how that spend trends over time.
API and MCP Access: The same intelligence is exposed programmatically so AI agents — otherwise blind to audio — can read and reason over spoken content.
Podcast Analytics Layer: Listener ratings and reviews, chart rankings, audience-size estimates, sponsorship data, political bias analysis and brand suitability scoring.
Daily Index Refresh: About 20,000 new episodes are transcribed and added every day, covering all Apple Top 200 shows across 135 verticals.

Investment Research: Hedge funds pull statements executives make on podcasts that never surface in filings or text-based web crawls.
Grounding AI Agents in Audio: Developers connect the MCP or API so their agents can cite what was actually said on a podcast instead of only web text.
Brand and Reputation Monitoring: Set alerts on a company or product name and get notified whenever it is mentioned across top shows.
Competitive Ad Intelligence: Marketers audit where a competitor advertises, on which shows, and how that footprint changes over time.
Journalism and Fact-checking: Reporters locate the exact quote and timestamp behind a claim attributed to a podcast appearance.
Academic and Market Research: Researchers study how a topic or entity is discussed across a large, structured corpus of spoken media.