AI & Agents
FastRecall
Last updated 2026-09-17 · benchmark measured 2026-09-17 — deterministic & reproducible
FastRecall provides persistent context storage for AI models, routers, and multi-agent systems.
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Legit.Show scored FastRecall 81/100 on 2026-09-17, measured across all 7 frames from its public surface. legit.show/s/fastrecall-ai/2026-09-17
Is FastRecall production-ready?
Legit.Show scores FastRecall 81 out of 100 — the simple average of its 7 measured frames. Legit.Show ran its deterministic 7-Frame production-readiness benchmark on FastRecall (public-surface assessment), measured from the public surface with no LLM in the scoring path. Its strongest frame is Accessibility; its weakest is Privacy. Every frame it averages is published with its evidence on the Legit.Show listing.
The 7 Frames
- Performance — 98/100
- Accessibility — 100/100
- Security — 80/100How this compares across the catalogue: The Web Security Baseline
- Privacy — 25/100How this compares across the catalogue: The Privacy Gap
- Reliability — 100/100
- Standards — 86/100
- Discoverability — 75/100
What we measured
- Security headers present: CSP, X-Frame-Options, X-Content-Type-Options, Referrer-Policy.
- No HSTS.
- Served over HTTPS with a valid certificate.
- Real Lighthouse performance run — 87 ms to first byte.
- Returns a proper 404 for unknown routes.
- 3 of 3 sampled routes reachable.
- No privacy policy found.
- Sets cookies / loads scripts with no consent prompt.
Who built it
Thompson Rose (@TomRrrose) · product account @FastRecallAI
Who it's for
AI engineers · Multi-agent system builders · Developers using multiple AI models · Side project builders · Production teams
Pricing
Free sandbox (1 week); Hobbyist $2/month minimum; Hacker $7/month minimum; Developer $25/month minimum; metered usage charged monthly
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