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Adobe vs Sambanova

Adobe scores higher on the AgentReady, 51/100 against 48/100. They differ on 6 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Adobe. Adobe products and services empower developers to create memorable digital experiences through developer creativity

Sambanova. SambaNova is an AI infrastructure company pushing the AI frontier with premium inference, maximizing dataflow efficiency with high speed and sustained throughput for running the largest models.

Where Adobe is ahead

Adobe passes llms-full.txt / full agent docs, and Sambanova does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: cli available. Sambanova misses it.

And on operate, agent compatibility verified. Sambanova misses it.

Where Sambanova is ahead

Sambanova passes llms.txt published, and Adobe does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Adobe misses it.

And on adopt, copyable quickstart. Adobe misses it.

What neither does

Both fail public docs discoverable, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Both sit at 80/100 here. Adobe misses public docs discoverable, llms.txt published; Sambanova misses public docs discoverable, llms-full.txt / full agent docs.

Understand. Sambanova leads 38 to 31. Adobe misses openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Sambanova misses openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Both sit at 40/100 here. Adobe misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; Sambanova misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, cli available.

Operate is whether an agent can run against it in production and recover when a call fails. Adobe leads 53 to 35. Adobe misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; Sambanova misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Adobe does not publish a machine-readable starting price. Sambanova does not publish one.

Signal by signal

Which to pick

Signal counts are level here, so fit and price decide it. Full profiles: Adobe and Sambanova. Alternatives to each: Adobe, Sambanova.

An agent can fetch this as data: POST /v1/compare {"slugs": ["adobe", "sambanova"]}