EmpirioLabs AI
Specialized AI model hosting for open, proprietary, and custom stacks.
Developer Tools·AI & Machine Learning·Data & Infrastructure
About
EmpirioLabs AI is a specialized AI inference and integration provider offering hosted open-source models on their own GPUs, optimized proprietary endpoints, and turnkey deployment capabilities. The platform provides on-demand GPU Cloud instances and hosted AI agents behind a simple interface, designed for teams looking to ship AI models to real users with competitive pricing and higher rate limits.
The platform caters to developers and teams seeking reliable access to AI models with full context windows, multimodal inputs, and tuned performance. It offers pay-as-you-go usage, day-zero support for new models, and specialty tuned models with creative templates to ensure out-of-the-box reliability without locked monthly plans.
What makes EmpirioLabs AI different is its ability to deliver inference at up to 90% lower costs on open models and up to 77% below standard rates on select proprietary endpoints. It combines private data handling with flexible access options, allowing users to interact via a no-code dashboard or direct API integration.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
there are people usually get reviews on Google Play that say $1 a month for this app never... you can't look at your price leverage on Android and iOS the same right they're very different communities
Android users pay less — price platforms separately
At $0.99/month, HabitKit was already near-free, yet a Google Play reviewer complained it was too expensive. Android and iOS audiences have structurally different willingness to pay — applying identical pricing across both platforms ignores that reality and produces friction on Android without increasing iOS revenue. Test prices independently on each platform rather than setting a single global price and calling it done.
If you stacked up all the time on iteration between activation in the product and using our product and levers that we know are correlated to workout completions versus iteration on deals it would probably be 90% product 10% deals.
Spend 90% on Product Activation, 10% on Discounts — The Ratio Matters
Greg's team allocation ratio is a useful benchmark: 90% of iteration effort on product activation (increasing the percentage of users who complete their first and second workout) and only 10% on discount and coupon mechanics. Most teams invert this, mistaking conversion-rate lifts from price cuts for product-market fit. The activation-first approach builds durable retention; discount-first builds churn-prone cohorts.
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