# Lovelaice

> Lovelaice is the product analytics platform for AI features. Product teams validate AI features before deployment with real data, real test cases, and no engineering ticket required — testing across 15+ LLMs side-by-side, catching failures before users do, and shipping with proof instead of hope. Built for product managers and domain experts in regulated industries (fintech, healthtech, legal, compliance).

Key differentiators: domain experts (not developers) lead evaluation; no time limits on experiment runs (competitors cap at 15 minutes); failure-pattern clustering across the full dataset; AI Act-ready audit trail.

## Product

- [Homepage](https://www.lovelaice.com/): Overview of the platform — catch failures before they ship, validate prompts and model swaps head-to-head, own the quality story over time.
- [For Product Managers](https://www.lovelaice.com/product-managers): How PMs use Lovelaice to design, test, and own AI quality without waiting on engineering. Includes the four-step framework and live ROI calculator.
- [Sign up (free)](https://app.lovelaice.com/sign-up): Start experimenting on real data. No engineering required.
- [Book a demo](https://www.lovelaice.com/book-a-call): Schedule a guided walkthrough on your use case.

## Use Cases

- [All use cases](https://www.lovelaice.com/use-cases): Industry-segmented view across FinTech, Legal & Compliance, Procurement, Real Estate & Insurance, Operations, and Marketing.
- [Data extraction](https://www.lovelaice.com/use-cases/data-extraction): Test extraction across LLMs on real invoices, contracts, and forms. Proof point: 11x cost difference between models at equal accuracy.
- [AI chatbots & assistants](https://www.lovelaice.com/use-cases/ai-chatbot): Evaluate full conversation flows, not just single prompts. Catch silent failures and multi-turn context breakdowns before users do.
- [Compliance automation](https://www.lovelaice.com/use-cases/compliance-automation): AI-powered compliance features for regulated industries. Compliance experts evaluate outputs directly — no engineering bottleneck. AI Act-ready audit trail.
- [Text generation](https://www.lovelaice.com/use-cases/text-generation): Find the balance of quality, consistency, and cost across content types and brand voice.
- [Classification](https://www.lovelaice.com/use-cases/classification): Route, tag, and score with measured drift detection the moment a model ships.
- [Document processing](https://www.lovelaice.com/use-cases/document-processing): Classify and route documents at scale on your actual document mix.
- [Image analysis](https://www.lovelaice.com/use-cases/image-analysis): Vision model testing at scale — accurate, consistent, and cost-effective for your specific use case.

## Resources

- [Resources hub](https://www.lovelaice.com/resources): Guides, newsletters, and masterclasses on AI experimentation and evaluation.
- [The complete guide: from product idea to fully validated AI feature](https://www.lovelaice.com/resources/complete-guide-to-ai-experimentation): Step-by-step methodology covering the 4 core concepts (system prompt, model selection, parameters, user input) and the 6-step experimentation process.
- [Why your AI evaluation is lying to you](https://www.lovelaice.com/resources/why-your-ai-evaluation-is-lying-to-you): Why most teams automate evaluation before understanding what they're evaluating, and the Evaluation Ladder approach that actually works.
- [Lessons from one year of AI product building](https://www.lovelaice.com/resources/lessons-from-one-year-of-ai-product-building): Key insights from shipping AI features systematically over the past year.
- [The death of the prompt box](https://www.lovelaice.com/resources/the-death-of-the-prompt-box): What A16Z's 2026 prediction means for AI features.
- [The expert test](https://www.lovelaice.com/resources/newsletter-jan): How to identify high-value AI features for your product.
- [Why ship and learn doesn't work for AI features](https://www.lovelaice.com/resources/why-ship-and-learn-doesnt-work-for-AI): Why traditional MVP thinking breaks down for AI.
- [Systematic AI development: the five principles](https://www.lovelaice.com/resources/systematic-AI-development-the-five-principles): The principles that separate hope from data.
- [The business case for AI experimentation](https://www.lovelaice.com/resources/the-business-case-for-AI-experimentation): Why structured testing saves more than it costs.

## Tools

- [AI Eval Diagnostic (free, 3 minutes)](https://www.lovelaice.com/ai-eval-diagnostic): Assess your team's AI evaluation maturity. Personalized score and benchmarks against 150+ product teams.

## Company

- [About Lovelaice](https://www.lovelaice.com/about): The founding team and the mission to give every product team the freedom to experiment with AI confidently.
- [Contact](https://www.lovelaice.com/contact): Get in touch.

## Optional

- [Privacy policy](https://www.lovelaice.com/privacy)
- [Terms](https://www.lovelaice.com/terms)
- [Imprint](https://www.lovelaice.com/impressum)