PromptLayer was founded in 2021 in New York City by Jared Zoneraich and Jonathan Pedoeem, who built the product after experiencing firsthand how chaotic prompt iteration becomes once an LLM application has real users. Prompts are effectively a new kind of source code, but they are often buried in application code, untracked, and impossible for non-engineers to safely change. PromptLayer was created to give teams a dedicated workbench for managing prompts as first-class, versioned assets.
The platform centers on a prompt registry and a visual editor. Teams store prompts centrally, version them, and edit them through a no-code interface, which means product managers, domain experts, and other non-technical collaborators can iterate on prompts without waiting on an engineering deploy. Because prompts are decoupled from the codebase, changes can be tested and rolled out independently, accelerating the iteration loop that determines LLM application quality.
Around prompt management, PromptLayer provides observability and quality tooling. It logs every LLM request, giving teams searchable history, usage analytics, and cost visibility. It supports A/B testing of prompt and model variants, batch evaluations to score outputs, and deployment controls to promote prompt versions safely. This combination turns informal prompt tinkering into a measurable, collaborative engineering workflow.
The company raised a $5 million seed round in February 2025. PromptLayer has cultivated a substantial base of developers and AI teams who use it as the system of record for their prompts, and the funding supports continued investment in collaborative prompt engineering and evaluation features.
PromptLayer competes with broader LLMOps and observability platforms, but its sharp focus on prompt management and cross-functional collaboration, letting non-engineers safely own and improve prompts, gives it a distinct position for teams where domain experts, not just developers, drive prompt quality.