Figaro
Scala library for probabilistic modeling and inference.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Figaro?
Figaro is a Scala-based framework that enables developers to build complex probabilistic models. It supports various probabilistic programming techniques, making it suitable for applications requiring uncertainty management and statistical analysis.
Key differentiator
“Figaro stands out as a specialized library for probabilistic modeling in Scala, offering advanced techniques and flexibility that are less common in general-purpose AI libraries.”
Capability profile
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Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
Figaro's API and documentation are deeply integrated with Scala, requiring a strong understanding of the language to effectively use its features.
As an open-source project focused on a niche area like probabilistic programming in Scala, Figaro has fewer contributors and users compared to more mainstream frameworks, which can lead to slower development of new features and limited third-party resources.
Figaro's inference methods can become computationally expensive when dealing with complex or large-scale probabilistic models, leading to slow execution times and increased resource consumption.
Due to its specialized nature, Figaro has fewer built-in integrations compared to more general-purpose frameworks, which can complicate the process of incorporating it into existing workflows or combining it with other data analysis tools.
Fit analysis
Who is it for?
✓ Best for
Scala developers building applications that require probabilistic modeling
Data scientists working on statistical inference within Scala projects
✕ Not a fit for
Projects not using the Scala programming language
Applications requiring real-time probabilistic inference without significant setup overhead
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
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Ecosystem
Relationships
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Works well with
Integrations
Next step
Get Started with Figaro
Step-by-step setup guide with code examples and common gotchas.