Respan
An LLM engineering platform combining an AI gateway, observability, evaluations, and prompt management for teams running production AI applications.
🔗 Visit Respan
Description
Building an AI feature usually starts with a single API call to one model provider, but production reality is messier: you need fallbacks when a provider has an outage, visibility into what your agents actually did, and a way to know whether a prompt change made things better or worse. Respan bundles those needs into one platform instead of making you stitch together separate tools.
Respan (formerly Keywords AI) routes requests to over 1,000 LLMs through a single gateway with automatic fallbacks and retries, traces every call an application or agent makes for debugging, runs automated evaluations using LLM judges or deterministic checks, and manages prompt versions so teams can test and roll out changes safely. It's backed by Y Combinator, processes over 80 trillion tokens, and holds ISO 27001, SOC 2, and GDPR/HIPAA-track compliance. Pricing starts with a free tier (100k logs, 1k scores, 5 datasets a month), a Team plan at $199/month billed annually, and custom Enterprise pricing, with metered add-ons for extra logs, scores, seats, and HIPAA compliance.
💬 Our review
The short version: if you're running LLM features in production and currently juggling a gateway, a logging setup, and a spreadsheet of eval results, Respan's combination of all three in one platform is a legitimate time-saver — the free tier is enough to evaluate it seriously before committing budget.
Against LangSmith, the closest and most established competitor, Respan's pitch is being gateway-first: LangSmith assumes you already have a way to call models and focuses on tracing and evaluation, while Respan adds multi-provider routing with automatic fallback as a core feature, which matters if provider outages have ever taken down your app. Against Langfuse, the open-source alternative, Respan trades self-hosting flexibility for a more polished managed experience and broader compliance certifications (useful if you sell into regulated industries). Arize leans more toward ML-model monitoring generally rather than LLM-specific workflows. The free tier's caps (100k logs, 1k scores) will feel tight fast for a team with real traffic, and the add-on pricing for overages can add up, but for a 10-person company iterating quickly, it's a reasonable one-stop alternative to assembling five separate tools.
📊 Global score
🤖 AI-enriched data
Gratuit (100k logs, 1k scores, 5 datasets/mois). Team 199 $/mois (facturé annuellement). Enterprise sur devis. Add-ons : 8 $/100k logs, 1 $/1k scores, 15 $/siège/mois, 249 $/mois pour conformité HIPAA.
Pros
Support de 1000+ modèles LLM avec routage automatique et fallbacks inter-providers
Observabilité complète des chaînes d'appels LLM, outils et agents avec traces détaillées
Évaluations intégrées avec juges LLM et vérifications de code déterministe
Gestion et versioning des prompts pour tests et déploiement
Infrastructure conforme (ISO 27001, SOC 2, GDPR, HIPAA)
Cons
Offre gratuite assez limitée (100k logs, 1k scores seulement)
Pricing pour overages peut devenir coûteux à grande échelle
Équipe réduite (10 personnes) peut limiter le support et la roadmap