NannyML is a technology company.
NannyML has raised $1.0M across 1 funding round.
NannyML has raised $1.0M in total across 1 funding round.
NannyML is a Belgian technology company founded in 2020 that builds an open-source Python library and software platform for monitoring machine learning (ML) models in production.[1][4][7] It serves data scientists and business stakeholders by estimating post-deployment model performance without access to targets, detecting data drift, and linking drift to performance changes, solving the problem of AI systems degrading due to shifting real-world data and making unreliable decisions.[2][4][5] The company bridges the gap between AI technical teams and business outcomes, ensuring ML adds ongoing value amid increasing AI automation in processes.[1][2][7] With €1.06M raised in pre-seed funding in 2020 from Volta Ventures, Lunar Ventures, and angels, and estimated revenues around $3M, NannyML has grown to 11-50 employees as a mature early-stage startup headquartered in Leuven.[4][6]
NannyML was founded in 2020 by Hakim Elakhrass (American, CEO), Wojciech (Polish), and Wiljan Cools (Belgian), who met over five years earlier while studying at KU Leuven and at a Brussels hackathon.[1][2][3] Before NannyML, the trio ran a machine learning consultancy, where they encountered real-world AI deployment challenges: models trained on static data often failed as the world and data evolved, leading to poor decisions.[1][2] This realization—that AI needed continuous monitoring—sparked the idea for NannyML, supported early by Belgium's Start it @KBC accelerator.[2] Pivotal early traction came from their €1M+ pre-seed round, validating their vision to make production AI safer.[1][2]
NannyML stands out in AI observability through these key strengths:
NannyML rides the explosive growth of AI/ML adoption, where enterprises deploy models for critical decisions but face "silent failures" from data drift amid volatile real-world conditions like economic shifts or pandemics.[1][2] Timing is ideal as regulations like the EU AI Act demand AI governance, and businesses automate more processes, creating urgent need for tools that prevent costly errors without constant retraining.[1][2] Market forces favoring NannyML include rising MLOps demand (projected multi-billion market) and open-source trends, positioning it to influence Europe's AI ecosystem by enabling safer, scalable production AI—much like smoke alarms for algorithms.[2][4] As an early innovator from Leuven's tech hub, it contributes to Belgium's startup scene while addressing global challenges in trustworthy AI.[1][3]
NannyML is poised for expansion by evolving its open-source core into enterprise cloud services, capitalizing on AI trustworthiness as a competitive edge amid maturing MLOps markets.[4][7] Trends like multimodal AI, stricter regulations, and edge computing will amplify demand for advanced drift detection and automated corrections, potentially driving Series A funding and global scaling.[1][2] Its influence could grow by setting standards for post-deployment monitoring, empowering more reliable AI across industries and solidifying its role as Europe's AI sentinel—bridging technical innovation with business reality from day one.[5][7]
NannyML has raised $1.0M in total across 1 funding round.
NannyML's investors include Alpaca VC, Grace Beauty Capital, Highland Capital Partners, Lunar Ventures, Second Century Ventures, SoftBank Investment Advisers, Spark Capital, The Hit Forge, Balaji Srinivasan, Jonathan Cornelissen, Lieven Danneels.
NannyML has raised $1.0M across 1 funding round. Most recently, it raised $1.0M Seed in October 2020.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Oct 1, 2020 | $1.0M Seed | Alpaca VC, Grace Beauty Capital, Highland Capital Partners, Lunar Ventures, Second Century Ventures, SoftBank Investment Advisers, Spark Capital, The Hit Forge, Balaji Srinivasan, Jonathan Cornelissen, Lieven Danneels |