Respan Review 2026: LLM Gateway, Observability, Evals, and Pricing
A research-based Respan review covering features, pricing, privacy, limitations, alternatives, and a practical buyer test.

Bottom line
Respan, formerly Keywords AI, combines a multi-model gateway with tracing, cost monitoring, prompt management, datasets, evaluations, alerts, and production controls.
Editorial accountability
Who checked this guide
- Evaluation type
- Hands-on evaluation
- Last materially checked
- Evidence
- 4 listed sources
Hands-on testing is identified explicitly. Research-based coverage uses cited product documentation and other named sources; it does not imply every paid plan was used. Read the full methodology.
Editorial freshness
Pricing and material product claims were checked September 9, 2026.
Review evidence
What this guidance is based on
- Editorial basis
- Current first-party product, pricing, documentation, privacy, security, and terms material
- Review type
- Research-based product assessment
- Material review date
- September 9, 2026
- Buyer test
- Controlled workflow test covering quality, cost, privacy, permissions, reliability, and adoption risk
Important limits
- • DiscoverAI did not complete the proposed long-term paid deployment for this research-based review.
- • Features, prices, limits, rights, security controls, privacy terms, and provider data paths can change; verify the linked first-party pages before purchase.
In this guide
Short answer
Respan is a credible shortlist choice for teams that want one control plane for model routing, agent traces, prompt releases, evaluation, spend, and operational alerts. The generous free allowance makes a realistic pilot possible. Its biggest architectural tradeoff is concentration: routing and logging every model call through one vendor improves visibility but also creates a sensitive data path and a potential dependency that must be tested under failure.
Best for
- Teams operating multiple model providers
- Developers debugging production AI agents
- Organizations unifying gateway, prompts, evals, and spend
Look elsewhere if
- Workloads that cannot send traces through a third party
- Teams needing an evaluator to act as ground truth
- Simple low-volume prototypes with no operations burden
What Respan verifiably does
Current first-party material covers a unified gateway for hundreds of models, provider fallback, retries, load balancing, caching, key storage, budgets, rate limits, OpenTelemetry-compatible tracing, multimodal logs, prompt versioning, datasets, deterministic and LLM-judge evaluators, human review, production sampling, custom dashboards, and alerts through Slack, email, or webhooks. The former Keywords AI URLs now redirect to the Respan brand, while the legal entity remains Keywords AI, Inc.
Important limitations
Prompts, outputs, tool arguments, retrieved content, and user identifiers may enter traces unless teams omit or mask them. Automated evaluators are not ground truth and require calibration against expert labels. Gateway outages, routing changes, cache semantics, provider-specific features, and retry behavior can alter quality or duplicate consequential actions. The $199 Team figure is annualized, and downstream model inference remains an additional cost.
Respan pricing
Respan lists a $0 Free plan with 100,000 logs, 1,000 scores, five datasets, two evaluators, five prompts, seven-day retention, and one workspace. Team is $199 per month when billed annually and adds unlimited datasets, evaluators, and prompts, 30-day retention, five members, and private Slack support. Extra usage is listed at $8 per 100,000 logs and $1 per 1,000 scores; additional Team seats are $15 per member. Enterprise and model-provider charges are separate or custom. Reviewed September 9, 2026.
A fair buyer test
Mirror five percent of sanitized production traffic for two weeks, then route a reversible workload through Respan with direct-provider bypass available. Compare trace completeness, evaluator agreement with 300 expert labels, fallback correctness, cache safety, p50 and p95 latency, gateway and provider errors, cost attribution, PII masking, export quality, and recovery during an injected outage. Calculate platform cost per investigated failure and per accepted output.
Final verdict
Respan earns a pilot for teams whose model traffic, evaluations, and prompts have outgrown separate dashboards and scripts. Use the free tier to prove trace quality and incident-time savings, keep a tested provider bypass, exclude sensitive fields by default, and grant production evaluators authority only after measuring false positives and false negatives.
This is a research-based product assessment, not a claim of hands-on long-term testing. Product, pricing, privacy, security, ownership, and usage claims were checked against the first-party sources below on September 9, 2026. Verify current terms and run the proposed test with approved data before adoption.
Reusable trial worksheet
Test Respan before you commit
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Teams operating multiple model providers; Developers debugging production AI agents; Organizations unifying gateway, prompts, evals, and spend
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Mirror five percent of sanitized production traffic for two weeks, then route a reversible workload through Respan with direct-provider bypass available. Compare trace completeness, evaluator agreement with 300 expert labels, fallback correctness, cache safety, p50 and p95 latency, gateway and provider errors, cost attribution, PII masking, export quality, and recovery during an injected outage. Calculate platform cost per investigated failure and per accepted output.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Respan lists a $0 Free plan with 100,000 logs, 1,000 scores, five datasets, two evaluators, five prompts, seven-day retention, and one workspace. Team is $199 per month when billed annually and adds unlimited datasets, evaluators, and prompts, 30-day retention, five members, and private Slack support. Extra usage is listed at $8 per 100,000 logs and $1 per…
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.3/5; AI quality 4.1/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: OpenAI SDK, Vercel AI SDK, LangChain, LlamaIndex, Mastra, OpenTelemetry
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Creates a central traffic and telemetry dependency; Team price requires annual billing; Judges and fallbacks need independent validation
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Community evidence
How verified users put Respan to work
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
Sources and verification
Product details and claims were checked against the following primary sources.
Frequently asked questions
What is Respan?
Respan is the new name for Keywords AI's LLM engineering platform, combining a model gateway, observability, evaluations, prompt management, and monitoring.
How much does Respan cost?
Respan lists a free plan, Team at $199 per month billed annually, metered log and score overages, and custom Enterprise pricing; model-provider usage is separate.
Can Respan route between AI models?
Yes. Its gateway supports a unified endpoint, provider fallbacks, retries, caching, load balancing, budgets, and rate limits.
Does Respan replace human evaluation?
No. Its automated and LLM-judge evaluations should be calibrated against expert labels before they block traffic or approve a release.
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Gateway, traces, evaluations, and prompts in one platform
Tools mentioned in this article
Respan
Route, trace, evaluate, and monitor model and agent traffic through one engineering platform
Respan, formerly Keywords AI, combines a multi-model gateway with tracing, cost monitoring, prompt management, datasets, evaluations, alerts, and production controls.
Langfuse
Open-source tracing, evaluation, prompt management, and metrics for LLM applications
Langfuse unifies traces, costs, prompts, datasets, and evaluation with cloud and self-hosted options, but telemetry sensitivity, retention, operational load, and fast-rising plan costs demand a scoped pilot.
Helicone
An open-source AI gateway with request monitoring, cost tracking, caching, fallbacks, prompts, and evaluations
Helicone combines multi-provider routing and observability behind a familiar API, but proxy trust, logged payloads, retention, usage-based costs, and gateway dependency need careful architecture review.
Patronus AI
Evaluate, debug, and guard AI systems with managed judges, benchmarks, traces, and an investigation agent
Patronus AI combines offline evaluation, production guardrails, tracing, prompt management, curated benchmarks, and Percival for investigating agent failures.
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