Blog
How Octolane scaled to 4.4M agent requests with Respan
Octolane uses Respan to see every agent tool call and trace, scaling from thousands to 4.4M agent requests while managing $700M in real pipeline.
Octolane · September 30, 2026
How Finta runs evals in production with Respan
Finta uses Respan to test every AI categorization change against golden datasets, with prompt versions, evaluators, and accuracy thresholds in one place.
Finta · September 22, 2026
How Retell AI runs 1M+ hourly LLM calls for voice AI agents on Respan
Retell AI ingests 1M+ LLM calls per hour on Respan, with full per-call thread visibility, metadata-indexed exports for evals, and real-time alerts on stream timeouts and fallbacks.
Retell AI · February 24, 2026
How Mem0 built a 99.99% reliable memory layer for AI agents on Respan
Mem0 runs hundreds of millions of LLM calls a day across multiple providers on Respan, with 99.99% reliability, end-to-end traces, and per-user cost visibility.
Mem0 · February 21, 2026
How Apten debugs and deploys LLM models 10x faster with Respan
Apten uses Respan to debug and deploy LLM-powered SMS, voice, and email agents 10x faster, processing 150,000+ requests per day with full visibility.
Apten · February 19, 2026