RightNow System Zero vs SPEV

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.

SPEV

SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email.

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.

SPEV

1. Send model: "spev" to POST https://api.sprag.ai/v1/decisions with a bearer key. /v1/systemone returns 410
2. Ask every question about one piece of evidence in one request. Answers come back in question order
3. Send audio as base64 in input_audio with format, not as a data URL, and at most one image across all messages
4. Keep evidence and questions under 8,192 tokens. Over the limit returns 400 model_limit_exceeded
5. Back off on 429 and 503 for Retry-After seconds. Limits are 60 requests a minute per organisation by default
6. Handle an answer of type refusal, which carries no probabilities