AI · alternatives · 2026

24 alternatives to NannyML

OSS Python library for detecting silent ML model failure

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. NannyML launched in 2022; newer entries below may have overtaken it.

1
NannyML Regression v0.8.0▲85
OSS Python library for detecting silent ML model failure
2022 · nannyml.com · its alternatives →
2
OSS Python library for detecting silent ML model failure▲5
nannyml: post-deployment data science in python. Contribute to NannyML/nannyml development by creating an account on GitHub.
2022 · github.com · its alternatives →
3
Igel – A CLI tool to run machine learning without writing code▲405
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
4
StackML▲252
Machine Learning platform in-browser, for creators
2019 · its alternatives →
5
ZenML▲84
Create reproducible machine learning pipelines
2020 · github.com · its alternatives →
6
We made our own inference engine for Apple Silicon▲186
We wrote our inference engine on Rust, it is faster than llama cpp in all of the use cases. Your feedback is very welcomed. Written from scratch with idea that you can add support of any kernel and platform.
2025 · github.com · its alternatives →
7
MakeML▲274
Train Neural Networks without a line of code
2019 · makeml.app · its alternatives →
8SM
SpotML – Managed ML Training on Cheap AWS/GCP Spot Instances▲157
2021 · spotml.io · its alternatives →
9
Fullstack ML – From Notebooks to Deployment▲198
Contribute to xadrianzetx/fullstack.ai development by creating an account on GitHub.
2019 · github.com · its alternatives →
10
CLI for working with Apple Core ML models▲48
A native command-line interface for working with Apple Core ML models on macOS - schappim/coreml-cli
Jan 2026 · github.com · its alternatives →
11
AIRS ML▲81
Edge AI that predicts machine failures
Apr 2026 · airsml.co.uk · its alternatives →
12
ScoopML▲81
An AI assistant for machine learning engineers
2020 · its alternatives →
13SF
Smart Fruit – A Python schema-based machine learning library▲44
I've made a small Python library, designed for quick-and-easy prototyping of machine learning models. It's built on top of scikit-learn, to serialize and deserialize data from the forms you're likely to have, to the format used in scikit-learn. https://github.com/madman-bob/Smart-Fruit It's pretty bare-bones at the moment, but I thought I'd see if there was any interest before spending too much time on it. Let me know what you think.
2018 · its alternatives →
14
Machine learning automation from creating to using models in production▲72
a delightful machine learning tool that allows you to train, test, and use models without writing code - GitHub - nidhaloff/igel at v0.4.0
2021 · github.com · its alternatives →
15
Deploy ML Models on a Budget▲117
Deploy a ML inference service on a budget in less than 10 lines of code. - ebhy/budgetml
2021 · github.com · its alternatives →
16
OrchestraML▲82
From English prompt to deployed ML model with human approval
Jun 2026 · orchestra-ml.vercel.app · its alternatives →
17
Appelpy – library for easier regression modelling in Python▲56
Applied Econometrics Library for Python. Contribute to mfarragher/appelpy development by creating an account on GitHub.
2019 · github.com · its alternatives →
18
BigML▲64
Machine learning as a service - build predictive apps
2014 · bigml.com · its alternatives →
19
Continuous Machine Learning – CI/CD for Machine Learning Projects▲171
Bring DevOps practices to your projects for automatic, reproducible, and fast machine learning.
2020 · cml.dev · its alternatives →
20HP
High-performance ahead-of-time compiler for Machine Learning▲83
2018 · scss.tcd.ie · its alternatives →
21AT
A tool to benchmark LLM APIs (OpenAI, Claude, local/self-hosted)▲55
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
22
SapientML – Generative AutoML for Tabular Data▲82
Generative AutoML for Tabular Data. Contribute to sapientml/sapientml development by creating an account on GitHub.
2023 · github.com · its alternatives →
23
ZenML, extensible open-source MLOps framework for reproducible ML▲37
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io. - zenml-io/zenml
2020 · github.com · its alternatives →
24
Using ML to detect key changes to 2020 Candidates' Websites▲67
2019 · deepdiveduck.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →