PromptLayer

About PromptLayer

PromptLayer positions itself as the collaboration layer for AI engineering teams, built around a specific organisational problem: the people with the domain knowledge to write a good prompt are usually not the people with commit access. It provides a prompt registry with a visual editor, so subject-matter experts can edit, version, test and deploy prompts without touching the codebase or waiting on an application redeploy — the vendor's case studies describe curriculum designers at an education company compressing months of iteration into a week on exactly that basis. The second pillar is evaluation: dataset-backed regression tests, automated graders and human review runs, executed before a prompt or workflow change reaches production, so a prompt edit is gated the same way a code change would be. The third is observability, connecting production traces back to the specific prompt version that produced them and tracking cost, latency and token usage per version, which is what makes a regression diagnosable rather than merely visible. Together that is the prompt CMS, eval harness and observability stack most teams end up building internally. Reference customers include Gorgias, Speak and NoRedInk. Pricing scales from a free hacker tier through per-seat team plans to enterprise deployments, with pay-as-you-go transaction rates once included volume is exhausted, so a team can start on the free tier and grow into the same tooling rather than migrating off it.

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