AI agents are becoming a real buyer persona. When a developer asks Claude or ChatGPT to "set up invoicing," the agent — not the human — decides which SaaS to reach for. So we asked a simple question: if an AI agent showed up at your SaaS's front door today, could it get in?
We spent this summer verifying that question against 200 of Japan's leading SaaS products, using only publicly checkable facts. The result is the ARI Award 2026 Summer — and the headline is that only 41 of 200 (20.5%) earned an A rating or above. Eleven earned AAA.
This post explains what we measured, how the rating works, and what the 159 that didn't pass have in common.
KanseiLink is an independent rating agency operated by Synapse Arrows (Singapore). We verify Agent Readiness: how ready companies and SaaS products are to be discovered, understood, connected to, and executed by AI agents.
"Rating agency" is a deliberate framing. Gartner ranks vendors for CIOs. G2 aggregates human reviews. ESG ratings serve investors. Nobody was rating software for its newest class of users — AI agents — so we built the evaluation model for it:
Ratings run AAA to D. The formula is public, ratings are never for sale, and per-service success-rate figures stay unpublished until independent third-party telemetry reaches sufficient scale (Principles of Independence).
Numbers as of 2026-07: "Publicly verifiable" is the key phrase. We check what an agent can check: official MCP server availability, API openness, whether the developer docs are reachable without emailing sales, whether auth methods are documented. No vendor self-reporting, no pay-for-grade.
The certified tier (AAA 11 / AA 21 / A 9) shares a profile: The uncertified majority mostly fails on quiet things, not dramatic ones:
Japan's SaaS market is large, dense, and under-documented in English — which makes it a blind spot for most AI models. It's also moving fast: several major Japanese vendors (accounting, chat, workflow) now ship official MCP servers that rival anything in the US ecosystem. The ARI Award exists partly to make that legible to the global agent ecosystem.
A global index is the obvious next step; the 11,000+ service database already spans both markets.
If you're building agents rather than SaaS: the same database is queryable over MCP (github.com/kansei-link/kansei-mcp-server, MIT) so your agent can look up whether a service is worth attempting before burning tokens on trial-and-error.