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SPECIFICTION
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NannyML vs Opik

NannyML

nannyml.com

Opik

comet.com

Side by side

FigureNannyMLOpik
Price from$99/mo$19/mo
Free planYesYes
Free trialYesYes
Open sourceYesYes
WebYesYes
Windows—Yes
macOS—Yes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published74
Spec score · Machine Learning Model Monitoring Software8.8 (#3)8.8 (#4)
Spec score · Model Monitoring Software8.7 (#8)8.8 (#7)
FoundedBelgian company records state that NannyML was established on 19 March 2020.2017
FundingAn October 2024 European Innovation Council list names NannyML NV's EU-AURA project for blended finance funding consideration.TechCrunch reported a $50 million Series B in November 2021, bringing Comet's reported total raised to almost $70 million.
IntegrationsNannyML Cloud is offered through both Azure Marketplace and AWS Marketplace.The integration catalog covers TypeScript, Python, Java, .NET and Ruby ecosystems plus no-code tools and OpenTelemetry.
PurposeNannyML monitors deployed machine-learning models and estimates model performance even when ground truth is delayed or absent.Opik logs agent actions and provides automated evaluation workflows to find and fix errors across development, testing, and production.
Rating on G2No public NannyML rating; 0 reviews listedNo rating; 0 reviews listed for Opik
SupportThe pricing page lists email support for Starter, private Slack for Scale, and 24/7 support for Enterprise.The pricing page lists community and self-service support across plans, email support for Pro and Enterprise, and dedicated support and SLAs for Enterprise.
System requirementsThe published PyPI package requires Python 3.9 or newer and below Python 3.13, with an optional db extra.The documented local setup assumes Git and Docker; Linux, macOS and Windows installation scripts are provided.
What it doesNannyML monitors production machine-learning models, estimates performance when labels are delayed or absent, detects drift and links alerts to performance changes.Opik records agent interactions, retrieval, tool calls and model responses, then evaluates and monitors them across development, testing and production.

Plans

NannyML

  • Open SourceFree
  • Starter (beta)$99 a month
  • Starter$399 a month
  • Scale$999 a month
  • Pro (beta)$3,800 a month
  • EnterprisePriced on request
  • Enterprise (beta)Priced on request

NannyML pricing →

Opik

  • Free CloudFree
  • Open SourceFree
  • Pro Cloud$19 a month
  • EnterprisePriced on request

Opik pricing →

In their own words

NannyML

NannyML monitors deployed machine-learning models and estimates their performance when ground truth is delayed or unavailable. It detects concept drift as well as multivariate and univariate data drift, and connects alerts to changes in model performance. Data-quality checks and ranked drift alerts can help teams investigate features associated with performance issues. Users can relate model performance to monetary or other business outcomes. NannyML Cloud supports webhooks for retraining actions and an SDK for automating monitoring-data ingestion. Cloud is available through Azure and AWS marketplaces as SaaS or a managed application. With the managed-application option, the application and required infrastructure are provisioned within the customer's cloud subscription. For its Azure managed application, NannyML documents encrypted traffic and disks, but says automated backups were still being implemented and advises customers to safeguard model inputs and outputs elsewhere. The open-source library installs with pip or conda. Direct local dataset uploads through the Cloud UI must be smaller than 100 MB. Plans include a free self-managed Open Source option, Starter at $399 a month, and Scale at $999 a month.

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Opik

Opik helps teams building applications or agents that call an LLM log actions and evaluate behavior across development, testing, and production. It captures and visualizes traces, supports annotation, and provides audit logs. Its evaluation tools include more than 30 metrics for outcomes such as answer relevance, context precision, task completion, and hallucination. In production, Opik can evaluate traces in real time, alert when criteria fail, and track token use and model costs. Test Suites offer pass/fail assertions, an Agent Playground supports end-to-end tests, and a Prompt Optimizer provides six algorithms. Core observability and evaluation features are available as open-source code for local use. Opik includes a REST API and Python client, with Python and TypeScript SDKs listed, and integrations with more than 40 frameworks, model providers, and gateways. Free Cloud allows up to 10 team members, 25,000 spans per month, and 60-day retention. Pro Cloud costs $19 a month and lists up to 50 team members and 100,000 spans monthly.

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