Respan
Unified LLM observability, gateway, and evaluation platform for engineering teams.
Respan is a strong contender for teams that want a single platform for LLM routing, observability, and evaluation. Its gateway approach with 500+ models and production-embedded evals set it apart, though smaller projects may find the feature set overwhelming. Worth trialing if you are scaling beyond simple chat or need granular cost control.
Verified 1h ago · liveness 95/100 · cite: rightaichoice.com/tools/respan
- Teams scaling LLM apps from prototype to production with multiple providers
- Platform engineers building internal AI infrastructure with routing and observability
- Product teams needing production evaluation across models
- Organizations migrating from Portkey after its acquisition by Palo Alto Networks
- Small projects or hobbyists needing a generous free tier
- Teams using only 1-2 models without routing needs
- Users wanting a lightweight standalone monitoring tool without gateway
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Skip Respan if you only need to monitor calls to a single model without routing or evaluation workflows.
Going past 100k logs on the Free tier requires paying $8 per additional 100k logs.
Respan's Free tier is generous for evaluation but limited in logs. The Team plan at $199/mo (yearly) with 5 seats competes with LangSmith, though LangSmith offers a more generous free tier for monitoring. Enterprise pricing is custom. For teams that need gateway + observability + evals in one, Respan can be cheaper than separate tools.
In short
Respan — Unified LLM observability, gateway, and evaluation platform for engineering teams. Best for Teams scaling LLM apps from prototype to production with multiple providers, Platform engineers building internal AI infrastructure with routing and observability, Product teams needing production evaluation across models. Free to start; paid plans from $199/mo.
What's new in Respan
Checked 5 days agoAcross the latest 5 updates: 3 feature updates and 2 changelog entries.
New Playground, cache visibility, dataset row deletion, improved reports, charts, experiments, prompt navigation, tables, logs, views/fixes
UI improvements across Playground, caching, dataset deletion, reports, dashboard charts, experiments, prompt navigation, table infinite scroll, logs stability, and various fixes.
Model status filtering, improved Models page, dashboard performance, prompt bulk updates, various fixes
New active/deprecated filtering on Models page; performance improvements to dashboard loading and models listing; fixed logs, reports, dataset, and playground issues.
How to Evaluate AI Agents in Production (Not Just Benchmarks)
Describes five production eval criteria for AI agents, with methodology to wire into live traffic.
Prompt Versioning Without Evals Is Just Diff Tracking (2026)
Compares Respan, LangSmith, Langfuse, etc., and outlines four gaps in 2026 prompt management stacks.
Single Agent vs Multi-Agent: Why We Rebuilt Our AI Agent
Compares single vs multi-agent architectures, regression net used to measure rebuild, and production data.
What independent users actually report about Respan
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
48 mentions across 4 sources (Hacker News, YouTube, Bluesky, Lemmy).
- +Unified gateway for 500+ LLM models from one API.
- +Automatic fallback, retry, and load balancing across providers.
- +Built-in evaluation with LLM judges, code checks, and human review.
- +Detailed trace trees with latency per span for debugging.
- +Custom dashboard charts with SQL, cost-by-key, and metrics.
- −Only one Hacker News user called it 'too much of everything'.
- −Very few real user reviews — hard to validate reliability.
- −Learning curve may be steep for smaller teams or solo devs.
- −No community case studies or third-party benchmarks yet.
- −Potential confusion with other products sharing the 'Respan' name.
- • Overage charges for exceeding free-tier request limits.
- • Cost for additional team seats beyond basic plan.
Viability Score
How likely is Respan to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Unified gateway for 500+ LLM models
- Automatic fallback and retry on model errors
- Cross-provider load balancing
- Per-API-key spend limits with soft/hard caps
- Response caching to reduce cost and latency
- Trace tree with latency per span
- Thread view for multi-turn agent conversations
- Custom dashboard charts (cost-by-key, SQL, metrics)
- Slack/email/webhook alerts on error rate, cost, latency, tokens
- Built-in evaluation workflows (LLM judges, code checks, human review)
- Online evals on sampled production traffic
- Prompt versioning and experiment comparison
- Reports with API key limit breach details
- Model status filtering (active/deprecated)
- HIPAA compliance add-on at $249/mo
About Respan
Respan is an LLM engineering platform that provides a unified gateway, observability, and evaluation layer for AI applications. It is designed for engineering teams building and scaling LLM-powered features—from agents and chatbots to content generation tools. Respan routes all LLM calls through a single gateway, giving teams one API to access 500+ models, automatic fallback and retry logic, and cost controls with per-key budgets and caching. Every request is traced with rich context, and teams can monitor latency, spend, and error rates on a customizable dashboard with alerts via Slack, email, or webhook. The platform also includes a built-in evaluation framework that combines LLM judges, code checks, and human review—all running on sampled production traffic for continuous quality monitoring. Recent updates add custom charts, metrics views, a Reports feature with API key limit breach details, and improved filtering and theme customization. Respan also offers extensive documentation with cookbooks for end-to-end workflows. Unlike lighter monitoring tools, Respan combines routing, observability, and evals into one workflow, making it a strong alternative to separate point solutions or competitors like LangSmith and Portkey.
Behind the Verdict
Respan is a full-stack LLM engineering platform designed for teams that need more than just monitoring—they need routing, cost control, and evaluation in one place. Its gateway handles 500+ models with automatic fallback and retries, which is a lifesaver when providers go down or rate-limit you. The evaluation framework is deeply integrated: you can run LLM judges, code checks, and human reviews on sampled production traffic, so quality monitoring is continuous rather than ad-hoc. We'd reach for this when your team is scaling from a single provider to multiple, or when your agent traces become too complex for a simple logging tool. That said, the free tier is quite limited (100k logs, 1k scores) and the Team plan at $199/mo with 10k scores may feel tight for heavy users. The $249/mo HIPAA add-on is a notable extra. Compared to LangSmith, Respan offers a tighter gateway-evals loop, while Portkey's acquisition may drive users toward Respan. Where it bites: the free tier's 412 requests/min throughput and 7-day retention are restrictive for anything beyond small prototypes, and the Enterprise plan is required for SSO and on-prem. If you only need standalone monitoring, consider something lighter and cheaper.
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Real-world workflow fit
Concrete scenarios for the personas Respan actually fits — and what changes day-one when you adopt it.
You need to route traffic across GPT-5 and Claude Sonnet 4, with fallback if one errors.
Outcome: Set up a gateway endpoint with fallback_models, and within 10 minutes, all calls route through Respan with automatic retries and cost tracking.
You want to run faithfulness LLM judges on 5% of production traffic to catch regressions.
Outcome: Configure an online evaluator that scores sampled spans automatically; alerts fire on Slack when faithfulness drops below threshold.
You need to compare two prompt templates for a customer support agent against a dataset of 50 edge cases.
Outcome: Import a CSV dataset, run experiments with both prompts, compare scores in the dashboard, and deploy the winner with one click.
Use Cases
- Debugging multi-agent workflows in production to identify where a sub-agent failed.
- Building evaluation pipelines that combine LLM judges and human reviewers to score agent responses.
- A/B testing prompt variants across models and deploying the best-performing prompt to production.
- Monitoring cost and latency across different LLM providers to optimize spend.
- Creating regression test suites from real production traces to prevent regressions after updates.
- Setting cost and request limits per API key to control spending and prevent abuse.
- Migrating from Portkey after its acquisition by Palo Alto Networks.
Models Under the Hood
as of 2026-07-06
Limitations
- 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 (HIPAA add-on $249/mo).
- The AI gateway adds 50-150ms latency.
- Certain features like advanced customization and dedicated support are paywalled.
as of 2026-06-28
12-month cost
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.
Plans compared
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.
Free
$0/mo
Ideal for
Solo developers or small teams evaluating Respan with low traffic (up to 100k logs).
What this tier adds
Free entry point with full platform access but capped at 100k logs, 1k scores, and 7 day retention.
Team
$199/mo billed yearly
Ideal for
Growing startups that need unlimited datasets and evaluators, private Slack support, and SOC 2 report.
What this tier adds
Adds unlimited datasets, evaluators, and prompts, 30 day retention, and 8,400 requests/min throughput.
Enterprise
Custom
Ideal for
Large organizations needing self-hosting, HIPAA BAA, SAML SSO, dedicated support, and custom SLAs.
What this tier adds
Adds self-hosting, HIPAA compliance (add-on $249/mo), SAML SSO, dedicated support engineer, 99.99% uptime SLA.
Where the pricing makes sense
The company stage and team size where Respan's pricing actually pencils out — and where peers do it cheaper.
Respan's Free tier is generous for evaluation but limited in logs. The Team plan at $199/mo (yearly) with 5 seats competes with LangSmith, though LangSmith offers a more generous free tier for monitoring. Enterprise pricing is custom. For teams that need gateway + observability + evals in one, Respan can be cheaper than separate tools.
Setup time & first value
How long it actually takes to get something useful out of Respan — broken out by persona, not the marketing-page minute.
Platform engineers can set up the gateway and start routing calls in under 15 minutes using the SDK or OpenAI-compatible endpoint. Enabling evaluations and alerts takes another 30 minutes. Team onboarding including SSO and custom dashboards may take a few hours.
Switching to or from Respan
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Portkey: use a Python migration script to repoint API calls and import logged traces.
- →From LangSmith: export datasets as CSV, import into Respan, and recreate evaluators.
- →From custom gateway: switch endpoint URL and API key, then configure fallbacks in Settings.
- ↗To Portkey: export traces via batch export (JSONL) and import into Portkey.
- ↗To LangSmith: export datasets and prompt templates via API, then manual setup in LangSmith.
- ↗To custom solution: export all logs via JSONL/CSV and build your own monitoring.
Integrations
Resources & Guides
- Documentationrespan.ai
What is Respan?
Respan is a full-stack LLM engineering platform for developers and PMs.
- Resourcerespan.ai
Overview
Integrate Respan with your LLM stack
- Resourcerespan.ai
Core concepts
Spans, traces, threads, and how Respan organizes your LLM data.
- Resourcerespan.ai
Changelog
Helpful link from respan.ai
Official links
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