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Kolena

ML testing platform for rigorous model evaluation and failure analysis.

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About

Kolena is a machine learning testing platform that helps teams rigorously evaluate model behavior by identifying and tracking failure modes across scenarios, delivering dashboards and reports that reveal performance gaps to engineers, leaders, and customers. It focuses on high-resolution evaluation rather than aggregate accuracy, plus test automation and deployment workflows.

Founded in 2021 by Mohamed Elgendy (ex-Amazon, Rakuten), it closed a $15 million Series B in 2023 bringing total funding to $21 million, and its Python client is actively maintained (v1.69.0, January 2026). It holds SOC 2 and HIPAA certifications.

It is a paid, subscription platform with no free self-serve tier of note, and as a ~28-person startup its sales expansion is resource-constrained. Some analysts note recent messaging drift from ML testing toward AI document extraction.

What it can do

  • High-resolution model evaluation and failure-mode tracking
  • Behavioral regression tracking across model versions
  • Customizable test cases and scenario analysis
  • Dashboards communicating model risk to stakeholders

Setup

Request access at kolena.com; pip install kolena for the Python client.

Prerequisites

ML models to evaluate and test datasets; a paid Kolena subscription.

Use cases

model-testingmodel-evaluationfailure-analysisml-quality

Works with

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 72; Trending score 74/100 from researcher assessment.

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.