Prompt Foundry

Prompt management and side-by-side LLM evaluation for OpenAI and Anthropic models.

Freemium· Free tier (10 prompts, 500 evals/mo); Pro $15/user/mo; Enterprise customEvaluationOpenAI + Anthropic (multi-model)

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Best for

Pick Prompt Foundry if you want a fast, low-ceremony way to manage and A/B prompts across GPT and Claude without standing up a full eval framework.

Skip if

Skip it if you need broad model coverage (Gemini, Llama, Mistral), heavy offline dataset evals, or fully open-source tooling.

Prompt Foundry is a hosted prompt engineering and evaluation workbench aimed at teams building production LLM features. The core workflow is iterating on a prompt, running it across OpenAI and Anthropic models side by side, plugging in variables, simulating tool calls, attaching images for multimodal tests, and then deploying versioned prompts that your application can pull at runtime. Evaluation runs let you regression-test prompt changes before they hit users.

What differentiates it from heavier eval frameworks (Promptfoo, LangSmith, Braintrust) is the deliberately small surface area and a generous free tier that ships GPT-4o-mini usage with no API key required, which makes it usable inside a single afternoon. Pricing is $15 per user per month for Pro with unlimited deployed prompts and unlimited eval runs; the free tier caps at 10 deployed prompts and 500 monthly eval runs. Enterprise adds self-hosted deployment, SSO, custom roles, and audit logs.

Integrations are focused on the two frontier-lab APIs (OpenAI, Anthropic) rather than the long tail of open-source models, and the product leans toward prompt CRUD plus structured comparison rather than offline dataset scoring or LLM-as-judge pipelines. Docs live at docs.promptfoundry.ai and confirm an SDK exists for pulling deployed prompts into application code.

Editor's take

A focused, pragmatic alternative to the increasingly bloated eval platforms. The free tier is honest enough to actually ship a small project on, and the OpenAI-plus-Anthropic scope is realistic for most production apps. If your stack ever grows past those two providers, you will outgrow it.

— The AI Tool Bible editorial team