Self-driving AI observability and evals for agents
By Tanmay Verma, Founder · Last verified 05 Jun 2026
In short
Respan — Self-driving AI observability and evals for agents. Best for Engineering teams shipping production AI agents and LLM features, Teams needing unified observability across multiple LLM providers, Organizations that require automated eval pipelines (LLM judges + human review). Free to start; paid plans from $199/mo.
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A serious observability play for agent-heavy teams. The automatic trace capture and evaluator workflows reduce manual debugging, but it's best for those already using LLMs at scale. Smaller projects may find the feature set overkill.
Last verified: June 2026
Respan delivers on its promise of self-driving observability. For teams running production agents, the one-gateway approach and automatic trace capture are game-changers. The eval workflows, pairing LLM judges with human review, beat siloed evaluation tools. However, the platform is clearly built for scale – smaller teams might find the pricing steep for basic needs. Compared to LangSmith, Respan feels more purpose-built for agents vs. general LLM debugging. The 500+ model gateway and fallback logic are differentiators. Real-world caveat: while setup is quick (SDKs for Python/JS, OpenAI SDK adapter), you'll want to invest time in tuning evals to avoid noisy alerts. Overall, a strong pick for mature AI teams – pass if you're prototyping or need simple ChatGPT wrappers.
Skip Respan if Skip Respan if you need a free, self-hosted, or open-source observability tool without evaluation or gateway features.
Across the latest 10 updates: 5 feature updates, 1 launch and 4 news mentions.
Five eval criteria for production agent evaluation that catch failures benchmarks miss.
Comparison of Respan vs LangSmith, Langfuse, PromptLayer, Braintrust, Humanloop, Helicone, Agenta on closed-loop iteration gaps.
Monitor thresholds support prior-interval comparison; load balancing across providers; public dashboard API with new URL prefix.
When single-agent vs router-pattern multi-agent wins, regression net used to measure rebuild, and production data.
Portkey becomes Prisma AIRS AI Gateway; Respan compared with LiteLLM, OpenRouter, Vercel Gateway, Cloudflare Gateway as alternatives.
New rate limits and throttling features announced during Launch Week.
50+ new integrations added, including agent frameworks, LLM SDKs, and coding agents.
Respan Agent CLI with JS hooks, Claude Code/Codex CLI/Gemini CLI Node.js hooks, @respan/cli v0.6.0.
Evals 2.0 with experiment seed, dataset outcome spans, and reproducible runs.
Added gpt-5.4, gpt-5.4-mini, gpt-5.4-nano; reproducible experiment runs; payment methods in billing UI.
How likely is Respan to still be operational in 12 months? Based on 6 signals including funding, development activity, and platform risk.
Respan is an LLM engineering platform for teams building and scaling AI agents. It provides end-to-end observability, evaluation, and gateway management so you can trace every call, catch regressions, and deploy with confidence. Key features include a unified API gateway (500+ models, fallback, load balancing), automated evaluation workflows (LLM judges, code checks, human review), and production monitoring with alerting. Respan integrates with frameworks like LangChain, LlamaIndex, Vercel AI SDK, and Mastra, and supports security standards (SOC2, HIPAA, GDPR). Compared to alternatives like LangSmith, Respan offers self-driving observability that surfaces issues automatically without manual setup.
Tell us what you want to build — we'll match the AI tools that fit your goal, budget & existing stack.
Concrete scenarios for the personas Respan actually fits — and what changes day-one when you adopt it.
Production traces show high latency in sub-agent responses. Using Respan's trace tree and playground, the engineer replays the failing trace, inspects each step, and identifies a redundant tool call. They fix the workflow and deploy via the gateway.
Outcome: Latency reduced by 40% and the fix is validated with before/after baseline comparison.
The team manually reviews agent outputs. The lead sets up an evaluation workflow with an LLM judge for correctness and a code check for format, then runs online evals on 10% of production traffic. Alerts fire when scores drop below threshold.
Outcome: Evaluation cycles shrink from 2 hours per model to continuous automated scoring, catching regressions in minutes.
With Portkey acquired by Palo Alto Networks, the CTO evaluates Respan as an alternative. They test the gateway with 3 models (GPT-5.4, Claude Opus, Gemini 2.5 Pro), set up load balancing and fallbacks, and trace a sample workflow.
Outcome: Respan replaces Portkey with single-vendor observability and gateway, reducing integration complexity.
Free tier is capped at 100k logs and 1k scores. Team plan costs $199/month (billed yearly) with only 5 member seats; extra seats are $15/member. Additional logs cost $8 per 100k, and additional scores cost $1 per 1k. Self-hosting is only available on the Enterprise plan. Some advanced security features like HIPAA compliance and SSO with SAML require the Enterprise tier. The AI gateway adds 50-150ms latency.
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
For each published Respan tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Pro
$0/month
Ideal for
Individual developer or small team exploring AI agent observability with up to 100k logs and 1k scores.
What this tier adds
Free entry point; includes 100k logs, 1k scores, 5 datasets, 2 evaluators, 5 prompts.
Team
$199/month (yearly)
Ideal for
Startup or growing team needing unlimited datasets, evaluators, and prompts with SOC 2 report and Slack channel.
What this tier adds
$199/mo (yearly) adds unlimited datasets, evaluators, prompts, private Slack channel, SOC 2 report; 5 seat limit.
Enterprise
Custom
Ideal for
Large organization requiring custom volume discounts, HIPAA BAA, self-hosting, and dedicated support.
What this tier adds
The company stage and team size where Respan's pricing actually pencils out — and where peers do it cheaper.
Respan's free tier covers 100k logs and 1k scores, suitable for small teams. The Team plan at $199/mo (yearly) targets startups but caps at 5 seats. Enterprise pricing is custom. Compared to Langfuse (open-source, self-hosted free) or LangSmith (per-seat, $99/mo), Respan is pricier at scale due to additive log costs and seat limits. Portkey's acquisition may make Respan more attractive for ex-Portkey users.
How long it actually takes to get something useful out of Respan — broken out by persona, not the marketing-page minute.
For a single developer: get your first trace in 5 minutes by installing the Python or JS SDK and adding @workflow / @task decorators. Framework integrations (LangChain, Vercel AI SDK, etc.) require a one-line exporter. Full evaluation pipeline including custom judges: 1–2 hours. Team onboarding with gateway setup: half a day.
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Pricing, brand, ownership, or deprecation changes worth knowing before you commit. Most-recent first.
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Last calculated: June 2026
Custom pricing; adds self-hosting, HIPAA compliance, SAML SSO, dedicated support engineer, custom SLAs.
Spans, traces, threads, and how Respan organizes your LLM data.
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