Proof // Free to read

Guava Research

How I judge AI before I recommend it.
Two benchmarks that score models on the money they protect for a business, the AI setup I run Guava on, and my own AI usage, live.

At a glance // From the leaderboards

Guava Research at a glance
Models tested15 so far, across two private benchmarks of 100 hidden problems each
Main Street BenchClaude Opus 5.5, GPT-6 Astra and GPT-6.1 Sol are tied at the top, protecting $85,989 to $87,578 of $100,000 on average across their runs, with overlapping run ranges
MSP BenchClaude Opus 5.5 protects the most: $883,722 of $1,000,000 on average across its runs
Open sourceguava-stack, free under the MIT license
LiveMy Codex, Claude Code and OpenRouter usage, refreshed every minute
Updated

The work

Open any of them to see how it works.

  1. 01 Benchmark // Small business

    Main Street Bench

    Which AI protects a small business’s money best? Each model is handed everything for a messy neighborhood bakery, with 100 hidden problems and $100,000 at risk. Its score joins four public benchmarks in the Main Street Index, ranked against cost.

  2. 02 Benchmark // Managed IT

    MSP Bench

    The same test for a managed IT provider: its tickets, billing, backups, client accounts, scripts and contracts, with 100 hidden problems that put $1,000,000 at risk.

  3. 03 Open source // MIT license

    guava-stack

    The AI setup I run Guava on. One hub in your own Notion holds your context, rules, skills and memories, and every assistant you connect reads it. It’s a small add-on to Notion’s setup guide, with 16 working rules, a free workflow review, and a model router for Claude Code and Codex. Nothing is sent to Guava.

  4. Live

    04 Live // From Elastic

    Live AI Dashboard

    My own Codex, Claude Code and OpenRouter usage as it happens: model requests, tokens by model and response times. It’s the observability I set up for clients, pointed at myself. Prompts and responses are never captured.

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