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

A side-by-side comparison of GBrain and Portfolio Lab — 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.

alphaAI Capital Management

Freemium

AI-powered platform to build, validate, and auto-execute systematic investment strategies through your own brokerage.

AI Strategy Builder: Describe an investing goal and Portfolio Lab generates several complete, tunable strategies with holdings, entry/exit rules, and rebalance logic.
Multi-Objective Optimization: Every build outputs strategies optimized for Return, Sharpe ratio, and Minimum Drawdown so you can compare tradeoffs side by side.
Live Paper Validation: Strategies are stress-tested with in-sample and out-of-sample data, then run on live paper trading with real market prices and simulated fills.
Agentic Trading via MCP: Claude, ChatGPT, or any MCP-compatible agent connects to your own brokerage account, mirrors your portfolio, and places timestamped trades.
Diverse Strategy Rulebooks: Risk-Aware Hedged, Tactical Long-Only, Tactical Long/Short, Momentum, Mean Reversion, and Leveraged Regime Switcher — each with a clear discipline.
Specialized AI Models: Seven purpose-built models with 200+ predictors work over fundamental, technical, estimate, macroeconomic, and alternative data — not LLM guesswork.
Full Explainability: Every trade, allocation shift, and move to cash is visible, timestamped, and auditable so you can see exactly why the strategy acted.

Systematic Long-Term Portfolios: Build a core hedged strategy that shifts to cash or adds a downside hedge automatically when AI detects elevated market risk.
Trend Following: Deploy momentum strategies that rank assets by signal strength and rotate into the strongest performers while cutting losers.
Dip Buying: Run mean-reversion strategies that systematically buy oversold assets and exit when prices snap back, with a cash buffer during high-risk regimes.
Agent-Driven Execution: Let your AI agent auto-execute today's trade plan in your own Robinhood or brokerage account without giving up custody.
Strategy Research: Explore how the same idea performs under different objectives (Return vs. Sharpe vs. Drawdown) before deploying real capital.
Hedged Trend Following: Combine momentum with an AI-activated margin hedge to capture trends while protecting against sharp reversals.