NannyML
NannyML is a Belgian AI monitoring company providing post-deployment ML model monitoring through an open-source Python library and a cloud SaaS platform. It serves data science teams at enterprises across finance, retail, healthcare, and technology sectors.
- Company typePrivate
- Founded2020
- HeadquartersLeuven, Belgium
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What NannyML does
NannyML is a Belgian AI monitoring and observability company, founded in 2020 and headquartered in Leuven, that builds technology for post-deployment machine learning model monitoring. Its core product is a Python-based open-source library that estimates ML model performance even when ground truth labels are delayed or absent, using proprietary algorithms including Confidence-Based Performance Estimation (CBPE), multivariate drift detection via PCA reconstruction error, Bayesian data drift testing, and concept drift analysis. The company targets data science and ML engineering teams at enterprises that need to detect model degradation, prioritize retraining triggers, and translate model behavior into business outcomes through cost-benefit matrix configuration.
The commercial offering is NannyML Cloud, a managed SaaS platform built on top of the open-source library that automates data ingestion, alerting, and infrastructure management, with webhooks for triggering model retraining and a Python SDK for integration. Distribution is hybrid: an open-source self-serve path via PyPI/GitHub paired with a product-led free trial, AWS SageMaker Marketplace listing, and direct enterprise sales through founder-led demo booking. Pricing is not publicly disclosed, and the offering is positioned as freemium with a paid cloud upsell. Notable named users referenced on the company website include Walmart, Allianz, UBS, DeepMind, TUI, Razorpay, Yellow AI, Arise Health, Risika, and Euroclear.
In June 2025 NannyML was acquired by Brussels-based data quality platform Soda, integrating its ML monitoring capabilities into Soda's broader data quality stack. At the time of acquisition the company remained an early-stage venture-funded private company with 11-50 employees, having raised approximately $3.64 million in disclosed funding across seed (Lunar Ventures, Volta Ventures in 2020), a follow-on round with Id4 Ventures and Lunar Ventures in 2023, and an EIC Accelerator tranche in February 2025.
NannyML firmographics
Firmographics- Name
- NannyML
- Legal name
- NannyML
- Website
- https://nannyml.com
- Company type
- Private
- Founded year
- 2020
- Operating status
- Acquired
- Headcount range
- 11–50 employees
- Short description
- NannyML is a Belgian AI monitoring company providing post-deployment ML model monitoring through an open-source Python library and a cloud SaaS platform. It serves data science teams at enterprises across finance, retail, healthcare, and technology sectors.
- Ownership category
- akta.pro rank
NannyML industry classification
Industry- Product category
- MLOps / Machine Learning Monitoring
- NAICS
- Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Model Testing, Validation & Quality Assurance (HDAAABAH)
- akta.pro secondary industry
- End-to-End MLOps & ML Platform Suites (HDAAABAA)
Keywords
Where NannyML is headquartered
LocationHeadquarters
- HQ city
- Leuven
- HQ country
- Belgium
- HQ region
- Europe
Offices1 record
Markets served
NannyML business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Infrastructure, Operations
Revenue model
- NannyML Cloud Subscription: Cloud-hosted subscription service for ML model monitoring with infrastructure handling, offering performance monitoring, drift detection, and alerting capabilities.
- Open Source (Freemium): Free open-source library available for self-hosting, with commercial cloud version as upsell opportunity.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Free trial and open source tier available for evaluation |
Go-to-market motion2 records
Distribution channels4 records
Marketing channels9 records
NannyML product offering
Product offeringCore offering
NannyML builds software for monitoring machine learning models in production. Its flagship capability is the CBPE algorithm that estimates model performance without ground truth labels, paired with data drift and concept drift detection. The technology is delivered as a free open-source Python library and as NannyML Cloud, a managed SaaS offering that adds infrastructure handling, intelligent alerting, and webhook-driven retraining automation for enterprise data science teams.
Product overview
NannyML is an AI monitoring and observability company offering a dual-product portfolio: (1) NannyML OSS, an open-source Python library for post-deployment data science with performance estimation and drift detection capabilities, and (2) NannyML Cloud, a managed SaaS platform that provides the same functionality without infrastructure management. An additional NannyML Sagemaker offering targets AWS-hosted models. The company was acquired by Brussels-based Soda in June 2025 to enhance Soda's data quality platform with NannyML's ML monitoring technology.
Differentiator
Problem solved
Functional benefit
Brands
- NannyML Cloud: Cloud-based SaaS platform for monitoring ML models in production with performance estimation and drift detection capabilities.
- NannyML OSS
- NannyML Sagemaker
Products and services
- NannyML Cloud Cloud-hosted SaaS platform for post-deployment ML model monitoring, offering performance estimation (including CBPE), multivariate and univariate drift detection, concept drift analysis, intelligent alerting, webhooks for retraining automation, and a Python SDK for automated data ingestion. Built for enterprise data science teams needing to monitor production ML models.
- NannyML OSS Open-source Python library for post-deployment data science providing performance estimation (CBPE), drift detection (multivariate PCA-based and univariate), concept drift analysis, and model monitoring capabilities. Available via PyPI and GitHub for self-hosting and evaluation by data science teams.
- NannyML Sagemaker AWS Marketplace deployment of NannyML for ML models hosted on Amazon SageMaker, enabling native integration with SageMaker inference endpoints for enterprise AWS customers.
Quantifiable outcome
- 91% of ML models experience performance degradation in production over time
- +1 more outcomes
Companies that use NannyML
Customer profileNamed customers10 records
Segments2 records
Ideal customer profiles2 records
NannyML technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration4 records
AI capability4 records
Feature10 records
NannyML partnerships and signals
Strategic signalPartnerships
One partnership is on record.
- SodacoreSoda, a Brussels-based data quality platform company, acquired NannyML in June 2025. The acquisition aims to integrate NannyML's AI monitoring technology to improve detection of data issues, model performance, and data drift, supporting Soda's goal of providing comprehensive data quality and AI infrastructure.
Scale indicators2 records
Recent moves6 records
Expansion highlights6 records
NannyML competitors and assessment
Company assessmentDirect peers
- Arize AI: Arize provides ML observability and model monitoring (drift, performance, LLM eval). It directly competes with NannyML in production ML monitoring for enterprise data science teams.
- WhyLabs: WhyLabs offers an AI observability platform with data drift, model performance, and data quality monitoring — a direct functional overlap with NannyML Cloud.
- Evidently AI: Evidently AI provides an open-source Python library and cloud platform for ML and LLM monitoring, including drift detection and performance tracking — the closest OSS-led analogue to NannyML.
- Fiddler AI: Fiddler AI is an ML monitoring and explainability platform serving regulated industries (finance, healthcare). It competes with NannyML on model performance monitoring and governance.
- Superwise: Superwise provides enterprise ML model monitoring, drift detection, and AI governance, targeting the same data science leader buyer as NannyML.
Broad incumbents
- Soda: Soda is a data observability and data quality platform and NannyML's acquirer. It is adjacent (data quality) but increasingly overlapping as it integrates NannyML's model monitoring into its stack.
- Monte Carlo Data: Monte Carlo is a data observability platform for pipelines and now AI/ML assets, overlapping with Soda/NannyML in the broader data-and-AI reliability category.
- Datadog: Datadog offers infrastructure and APM monitoring with expanding ML/LLM observability features. As a broad incumbent, it can bundle ML monitoring alongside existing enterprise contracts.
Emerging players
- Grafana Labs: Grafana Labs integrates directly with NannyML via PostgreSQL/Grafana dashboards and is extending into ML/LLM observability. It is an integration partner today and an emerging competitor on dashboards.
- WhyLabs / LangSmith / Helicone (LLM observability tier): LangSmith (LangChain) and similar LLM-eval tools target the next-gen monitoring opportunity adjacent to NannyML's drift and performance estimation methods, especially post-Soda integration.
Market position
Strengths5 records
Weaknesses4 records
Competitive moat5 records
Key risks6 records
Key highlights6 records
Customer concentration
NannyML social profiles
Digital presenceNannyML financial estimates
Financial estimateRevenue estimate
Valuation estimate
NannyML leadership team
Management profileNumber of profiles
Profiles3 records
NannyML funding detail
Funding detailFunding overview
Funding rounds4 records
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
NannyML M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about NannyML
What does NannyML do?
NannyML builds software for monitoring machine learning models in production. Its flagship capability is the CBPE algorithm that estimates model performance without ground truth labels, paired with data drift and concept drift detection. The technology is delivered as a free open-source Python library and as NannyML Cloud, a managed SaaS offering that adds infrastructure handling, intelligent alerting, and webhook-driven retraining automation for enterprise data science teams.
Is NannyML a public or private company?
NannyML is a private company. It is classified as corporate owned and is currently acquired.
When was NannyML founded?
NannyML was founded in 2020. It employs 11 to 50 people.
Where is NannyML based?
NannyML is headquartered in Leuven, Belgium, in the Europe region.
How does NannyML make money?
Two revenue lines are on record. NannyML Cloud Subscription is the primary driver. The others are open Source (Freemium).
Who are NannyML's main competitors?
Direct peers on record are Arize AI, WhyLabs, Evidently AI, Fiddler AI and Superwise. Broad incumbents are Soda, Monte Carlo Data and Datadog. Emerging players are Grafana Labs and WhyLabs / LangSmith / Helicone (LLM observability tier).
Does NannyML have an API?
Yes. NannyML Cloud SDK for Python enables developers to automate monitoring data ingestion and integrate NannyML's ML monitoring capabilities into their workflows. The product also supports webhook-based integrations for triggering retraining actions when concept drift is detected, estimated performance degrades, or heuristic rules are met. Developer documentation is at nannyml.gitbook.io/cloud/less-than-greater-than-nannyml-cloud-sdk/getting-started.
What industry is NannyML in?
NannyML's product category is MLOps / Machine Learning Monitoring. Its primary akta.pro industry code is HDAAABAH, Model Testing, Validation & Quality Assurance, with a secondary code of HDAAABAA, End-to-End MLOps & ML Platform Suites. Its NAICS code is 518 and its SIC code is 7372.