PromptLayer

What it does

PromptLayer takes in LLM prompts, prompt versions, production requests and traces, and evaluation datasets, and produces versioned prompt releases, dashboards of cost, latency, and token usage, and evaluation scores. Its prompt registry holds version history, diffs, release labels, and rollback, while traces connect production requests to the exact prompt version that produced them.

People use it to edit and test prompts from a visual dashboard without redeploying the application, run dataset-backed regression evals with human and LLM-based graders, A/B test prompt versions, and inspect multi-step agent traces. It combines a prompt CMS, eval harness, and observability in one place, so domain experts can change prompts without touching application code.

It suits AI engineering teams that want to decouple prompt changes from code releases, and product, content, or domain-expert teams who iterate on prompts. The vendor states SOC 2 Type 2, HIPAA, and GDPR compliance, and offers an SDK and REST API for programmatic use. Pricing and any free tier are not listed in the product copy, so cost terms should be confirmed with the vendor.

What it can do

• Visually edit, version, test, and deploy prompts without an application redeploy
• Connect production traces to prompt versions and track cost, latency, and token usage
• Run dataset-backed evaluations with human review and automated graders
• A/B test prompt versions and run regression evals triggered on prompt updates
• Trace multi-step agent workflows, including tool calls
• Retrieve versioned prompts through an SDK or REST API

Before you choose

• Pricing and free tier are not stated in the product documentation; confirm plans with the vendor
• Compliance claims (SOC 2 Type 2, HIPAA, GDPR) are stated on the homepage and should be verified for your needs
• Many capabilities are described on marketing pages; implementation details are in the documentation

Listed under

• Coding
• DevOps and observability
• Agent tracing
• AI agents
• AI engineering
• Engineering teams
• LLM evals
• LLM observability

Get started

Docs recommend connecting observability first, then using Tables and the Prompt Registry.

1. Connect observability to trace production requests
2. Set up Tables with datasets to monitor results and run evaluations
3. Release approved prompt versions from the Prompt Registry using labels

Check the vendor's pricing page for current plans and billing terms.

We couldn’t find published prices for PromptLayer. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• PromptLayer — Prompt Management, Evals & Observability ↗www.promptlayer.com
• PromptLayer Documentation - PromptLayer ↗docs.promptlayer.com

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promptlayer.com: product, pricing and policy pages

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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.