RightNow System Zero vs ScaleDown

RightNow System Zero

A well-documented decision API with an OpenAPI file, idempotent retries, a detailed error catalogue, streaming over WebSocket and published per-unit prices with USD 5 of starting credit. Standard context is 38,000 tokens; the 64k, 128k and 1M bands are held and video is a preview. The latency and benchmark figures are RightNow's own, and several of its pages disagree.

ScaleDown

Classify answers Jev-shaped choice, noul and score questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.

RightNow System Zero

1. Send audio only as inline 16,000 Hz WAV. The FLAC, MP3, OGG and MP4 audio named on the blog are refused with media_unsupported.
2. Keep state under 38,000 tokens. Long-context requests return 404 long_context_not_available, which never succeeds on retry.
3. Reuse the same Idempotency-Key and body on retries, and stop when error.retryable or x-should-retry is false.
4. Check every entry in answers even on HTTP 200, since one question can be refused while the others are answered.
5. Treat probabilities as uncalibrated while calibrated is false, and pin system-zero-2.0.0 when answers must not move with the alias.

ScaleDown

1. Send several questions about one item in one /v1/scaledown call. Each becomes its own Classify call and the usage is summed
2. Pin classify-1, extract-1 or summarize-1 once you've tuned thresholds on your own labelled cases
3. Set context_chars to 0 and use top_n on Extract unless you need the 500 characters of context each side
4. Set reasoning: false on /classify when you only need the label. The reasoning call bills its input at 2x
5. Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects