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NannyML: The ML Ops Safety Net
How a 44-person team is solving the hardest problem in AI deployment
Most ML models die in production. Not because they're broken, but because no one noticed they stopped working. NannyML is building the safety net that data science teams desperately need, turning silent model decay into actionable alerts.
"NannyML isn't just monitoring models—they're monitoring the business impact of model drift."
The Concept Drift Gold Rush
While the ML monitoring space explodes with tools, NannyML carved a niche by focusing on the invisible killer: concept drift. Their top organic keywords reveal a sophisticated audience—'kolmogorov smirnov test' (7,540 monthly searches) and 'concept drift' (1,230 searches) aren't casual queries. These are engineers and data scientists actively diagnosing production problems, and NannyML is positioning itself as the definitive answer.
Open Source as a Trojan Horse
The GitHub repository isn't just a marketing tool—it's the product. With 44 employees and $10.9M in revenue, NannyML is executing a classic developer-first playbook. The open-source core builds trust and community, while the Cloud offering removes infrastructure friction. This dual approach explains their 43% organic traffic: developers find the repo first, then migrate to the managed service when scaling.
Their traffic distribution tells a story of a product in early adoption. 8,122 monthly visits is modest, but the 38% direct traffic suggests strong word-of-mouth among data science teams. The top countries are anonymized, but the pattern suggests a European-heavy user base (CEO Hakim Elakhrass and team are EU-based), with early traction in US tech hubs.
- Targets the post-deployment blind spot where most ML projects fail
- Leverages open-source community for product-led growth
- Focuses on statistical rigor (KS tests, ADF tests) over dashboard fluff
- Monetizes infrastructure pain, not just monitoring features
The Bottom Line
NannyML is betting that as ML models become business-critical, teams will pay for specialized monitoring over generic observability. With $10.9M in revenue and a focused product, they're proving the market for ML-specific safety nets is real—and growing.
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NannyML Cloud — A Better Way to Monitor ML Models
Where data science teams monitor their models. Meet the standard for post-deployment data science. The power of NannyML Open Source without the infrastructure hassle.
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About nannyml.com
Where data science teams monitor their models. Meet the standard for post-deployment data science. The power of NannyML Open Source without the infrastructure hassle.
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nannyml.com uses 24 technologies across their website including Font Awesome, Google Fonts, HSTS, Sentry, and more.
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nannyml.com receives approximately 8.1K monthly visitors and ranks #2,768,684 globally. The website has a bounce rate of 42% with visitors viewing an average of 1.5 pages per visit. Users spend an average of 0:09 on the site.
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