Promptfoo — Test, evaluate, and red-team your LLM applications to ensure reliability and security.

Analyzed by · AI · Testing & Security · View on GitHub

What It Is

Imagine you're building a house, and before you let anyone live in it, you want to make sure the foundation is solid, the plumbing works, and it can withstand a storm. Promptfoo does this for AI applications. It's a tool that lets you rigorously test your AI prompts, models, and agents, much like how software developers use unit tests to check their code.

This matters because AI apps often behave unpredictably, leading to security vulnerabilities, incorrect outputs, or poor user experiences. Promptfoo kills the problem of 'trial-and-error' by providing a systematic way to evaluate performance, compare models, and proactively find weaknesses, helping you ship reliable and secure AI faster.

Promptfoo GitHub repository card

License Verdict

MIT License — Build and Sell Freely — Commercial Use Approved • No Copyleft Restrictions

The MIT License allows you to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the software. This means you can freely build commercial products and services on top of Promptfoo without needing to open-source your own code.

How to Use It

Promptfoo is a CLI tool for evaluating LLMs. Install it globally via npm, brew, or pip. You'll need Node.js. After installation, initialize an example project, set your LLM API key, and run evaluations directly from your terminal or view them in a web UI.

Prerequisites:

Estimated setup time: 5 minutes.

npm install -g promptfoo
export OPENAI_API_KEY=sk-abc123
promptfoo init --example getting-started
cd getting-started
promptfoo eval
promptfoo view

What I'd Build With This

Prompt & Model Comparison Dashboard (micro-saas)

Build a simple web service where users can paste prompts, select various LLM models, and run quick, predefined comparisons with automated evaluation criteria. Users pay for usage credits or a monthly subscription to access more models, advanced evaluation metrics, and historical testing data. This targets indie developers and small AI teams needing quick validation.

Effort: 1 Week Build Time · Target: Indie Developers, Small AI Teams · Pricing: $19/mo

AI Security & Compliance Platform (saas)

Develop a full-fledged SaaS platform offering automated red-teaming, vulnerability scanning, and continuous evaluation for LLM applications. It integrates directly into CI/CD pipelines, provides detailed security reports, and tracks compliance metrics over time, alerting teams to new risks. This serves mid-sized to large enterprises building critical AI applications with regulatory concerns.

Effort: 3 Months Build Time · Target: Mid-Market to Enterprise · Pricing: $299/mo to $999/mo

Custom LLM Risk Assessment & Audit Service (enterprise)

Offer a specialized consultancy service to large organizations. Utilize Promptfoo internally to perform deep-dive security audits, identify prompt injection vulnerabilities, data leakage risks, and ensure regulatory compliance for their proprietary LLM deployments. Deliver custom reports, provide actionable recommendations, and offer ongoing monitoring. This is ideal for financial institutions, healthcare providers, or government agencies.

Effort: 6 Weeks (initial setup + first client) · Target: Financial, Healthcare, Government · Pricing: $10,000 - $50,000 per audit

Sai Pavan Gopularam's Take

Promptfoo solves a critical problem: validating AI outputs before they hit production. I've seen too many founders launch AI features based on gut feelings, only to deal with embarrassing failures later. A SaaS built on this for automated red-teaming could easily fetch $500/month per mid-market client.

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