GBrain vs Koreshield: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of GBrain and Koreshield — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
GBrain
GBrain
A shared team brain that syncs memory, connected apps and scheduled skills to ChatGPT, Claude, Cursor and any AI your team uses.
Key features
- 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.
Best for
- 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.
Koreshield
Koreshield Labs Ltd.
Runtime trust layer that scans customer input, retrieved context and proposed tool calls in AI support workflows before they become trusted instructions.
Key features
- Customer Input Scanning: Inspects messages, attachments and externally controlled text before model execution so injected instructions never reach the model as trusted input.
- Retrieved Context Screening: Keeps poisoned tickets, CRM notes and RAG documents from inheriting system-level authority inside the prompt.
- Proposed Action Evaluation: Checks tool calls against trust, approval and authorization limits before they are executed.
- Detect and Enforce Modes: Run in detect mode to record threats without interrupting traffic, then enable enforcement only where fallback behavior is ready.
- Decision Evidence Trail: Records severity, decision and reason for every request, retained for 7 or 30 days depending on plan, for review and audits.
- Scan API with Key Management: Server-side API keys and endpoints such as /v1/rag/scan make integration with existing support stacks straightforward.
- Flexible Deployment: Use the hosted console or run the FastAPI + PostgreSQL service in your own infrastructure, with VPC, self-hosted and air-gapped options for Enterprise.
Best for
- Prompt Injection Defense: Blocking malicious instructions hidden in customer messages before an AI support agent acts on them.
- RAG Poisoning Protection: Preventing tampered knowledge-base articles or ticket histories from overriding system prompts.
- Agent Action Guardrails: Holding refunds, account changes or other tool calls for policy review when trust limits are exceeded.
- Safe Production Rollout: Measuring real threat and false-positive rates in detect mode before enforcing on live traffic.
- Security Audits: Exporting decision evidence to show auditors and security teams why each request was allowed or held.