Forest AI

What Forest AI does

Forest AI builds AI validation infrastructure that addresses structural failures in how AI models and agents are benchmarked, including contamination of evaluation data, cherry-picking of favorable results, bias, noisy metrics, fragmentation, restricted access, and lack of fairness. The company is based in New York, was founded in 2024, operates with 1-10 employees, and is led by CEO Ruben Wolff, CTO Mikołaj Glinka, and CFO Laurence Lewandowska. Its product portfolio combines live, sealed proprietary evaluation datasets in insurance, medical, and other high-value domains with an open-source JavaScript SDK and the PeerBench Platform (peerbench.ai), which together enable creation, execution, and consumption of trustworthy AI benchmarks using a NeurIPS 2025-validated sealed-execution methodology (arxiv.org/abs/2510.07575).

The company's commercial offering centers on an Enterprise White-Label Platform that lets large organizations run private, internal validation of their AI and agentic systems via a demo-driven consultative sales motion. An AI Marketplace for validated AI solutions with transparent performance metrics and automated routing is announced as 'Coming Soon', signaling intent to evolve from tooling into transaction-layer distribution. Distribution runs through GitHub (peerbench/peerBench) for developer-led adoption, the self-serve PeerBench platform for researchers, and direct enterprise field sales for regulated-industry buyers in insurance and healthcare.

Revenue mechanics are largely unproven: pricing is not publicly disclosed, no customer logos or ARR are provided, and revenue streams include a subscription Enterprise White-Label Platform, a SaaS PeerBench tier, transaction-fee potential from the upcoming marketplace, and a freemium/open-source SDK flywheel. The company has disclosed one funding event (2025-09-15) with SMAPE Capital, no parent company, no subsidiaries, and operates as an independent private entity with global ambitions inferred from its open-source presence and NeurIPS positioning.

Name

Forest AI

Legal name

Forest AI

Website

https://forest-ai.org

Company type

Private

Founded year

2024

Operating status

Operating

Headcount range

1–10 employees

Short description

Forest AI builds AI validation infrastructure combining proprietary evaluation datasets in insurance and medical domains with an open-source SDK and the PeerBench Platform, serving enterprises deploying AI systems and AI researchers via NeurIPS 2025-validated methodology.

Ownership category

akta.pro rank

Product category

AI Evaluation and Benchmarking Software

NAICS

Testing Laboratories and Services (541380), Computer Systems Design Services (541512)

SIC

Services-Testing Laboratories (8734), Services-Computer Programming Services (7371)

akta.pro industry

PRIMARYHDAAACAH

Evaluation, Benchmarking & Observability (Evals, Monitoring, Tracing)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/Foundation Models & Generative AI (LLMs, multimodal)

SECONDARYHDAEANAF

AI Observability, Monitoring & Evaluation Platforms (Drift, Quality, Safety)

Hardware, Technology & Telecom/Enterprise Platforms & Databases/Artificial Intelligence Platforms for Enterprise

SECONDARYHDAAAMAE

Regulatory Readiness & Audit Automation (e.g., EU AI Act, NIST AI RMF, ISO/IEC 42001)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Ethics & Compliance Solutions

SECONDARYHDAAAKAL

Audit, Explainability & Accountability Tooling (traceability, reporting)

Hardware, Technology & Telecom/Artificial Intelligence & Machine Learning/AI Security, Privacy & Model Governance

Keywords

• AI model evaluation
• AI benchmarking tools
• AI validation infrastructure
• Agent performance monitoring
• ML model assessment

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure

Revenue model

1. Enterprise White-Label Platform Subscription: Annual or multi-year subscription to the internal AI/agent validation suite for enterprise deployments, likely sold as a per-deployment or organization-wide license with premium support.
2. PeerBench Platform (SaaS): Platform-as-a-service model for benchmark creation and execution, potentially tiered with free and paid tiers for researchers, developers, and organizations.
3. AI Marketplace Transaction Fees: Marketplace for validated AI solutions with transparent performance metrics and automated routing, generating revenue through transaction fees or take rate on validated AI solution sales (product described as 'Coming Soon').
4. AI Validation Tools (Open Source / Freemium): Open-source AI validation tools and SDK, potentially monetized through premium tiers, support, or enterprise add-ons.

Go-to-market motion4 records

Distribution channels4 records

Marketing channels4 records

Core offering

Forest AI builds AI validation infrastructure that enables organizations to evaluate the quality, performance, reliability, fairness, and drift of AI models and agents. Its product suite includes proprietary evaluation datasets in insurance and medical domains, an open-source JavaScript SDK for model evaluation, the PeerBench benchmark creation and execution platform, and an enterprise white-label platform for internal AI/agent validation. The company applies a NeurIPS 2025 validated, sealed-execution methodology to prevent contamination, cherry-picking, and bias in AI benchmarking.

Product overview

Forest AI offers a comprehensive AI validation infrastructure with five interconnected products. The Private Proprietary Datasets provide protected evaluation data in high-value domains, which feed into the open-source AI Validation Tools (SDK) for evaluating model quality, reliability, fairness, and drift. The PeerBench Platform serves as the core benchmarking and execution system for trustworthy evaluations, while the Enterprise White-Label Platform extends these capabilities for internal enterprise deployments. The AI Marketplace (forthcoming) will enable distribution of validated AI solutions with transparent metrics. All offerings are designed to prevent benchmark contamination and cheating through rigorous, sealed execution methodologies validated by NeurIPS 2025.

Differentiator

Problem solved

Functional benefit

Brands

• peerbench: Benchmark creation and execution platform for trustworthy evaluations of AI models and agents.
• peerBench SDK

Products and services

• Private Proprietary Datasets Live, sealed proprietary evaluation datasets in insurance, medical, and other high-value domains that organizations and researchers can use to validate AI model quality without contamination risk.
• AI Validation Tools (SDK) Open-source collection of tools, libraries, and standards delivered as a JavaScript SDK for evaluating the quality, performance, reliability, fairness, and drift of AI models and agents.
• PeerBench Platform Open-source benchmark creation and execution platform (peerbench.ai) that lets users create, run, and consume AI benchmarks with sealed execution to prevent gaming and contamination.
• Enterprise White-Label Platform Internal AI and agent validation suite for enterprise deployments, allowing organizations to run private, cheat-proof evaluations of their AI systems with continuous monitoring under their own brand.

Segments1 record

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration1 record

AI capability3 records

Feature5 records

Scale indicators2 records

Recent moves5 records

Expansion highlights5 records

Direct peers

• Patronus AI: Patronus AI is a direct competitor offering LLM evaluation, safety, and benchmarking tools for enterprise. It targets the same AI validation problem space as Forest AI, including hallucination detection and compliance, with a comparable enterprise SaaS model.
• LangSmith: LangSmith (by LangChain) provides LLM evaluation, monitoring, and debugging for production AI applications. It directly competes with Forest AI's PeerBench Platform on benchmark creation and execution for AI model and agent evaluation.
• Arize AI: Arize AI offers an AI observability and evaluation platform with drift, quality, and fairness monitoring — directly overlapping with Forest AI's continuous monitoring and drift detection capabilities for deployed AI systems.
• Galileo: Galileo provides an evaluation and observability platform for LLM applications with hallucination detection and quality scoring. It competes with Forest AI's PeerBench platform on enterprise AI evaluation and benchmarking infrastructure.
• Braintrust: Braintrust offers an AI evaluation and observability platform for production LLM applications. It targets the same enterprise buyers as Forest AI with comparable benchmark creation, scoring, and continuous monitoring capabilities.
• WhyLabs: WhyLabs offers an AI observability platform focused on data quality, drift detection, and model performance monitoring. It directly overlaps with Forest AI's continuous monitoring and drift evaluation features for production AI deployments.

Broad incumbents

• Weights & Biases: Weights & Biases is an established ML experiment tracking, evaluation, and MLOps platform used widely by AI teams. It overlaps with Forest AI's evaluation toolset as part of a broader ML lifecycle suite rather than specializing in sealed benchmark execution.
• Hugging Face: Hugging Face operates the leading open-source ML model and dataset hub, hosting widely-used evaluation benchmarks (HELM, etc.). It is adjacent to Forest AI as a community-governed evaluation infrastructure player with vastly broader platform scope.
• Scale AI: Scale AI provides data labeling, evaluation, and AI testing services including SEAL (Safety, Evaluation, and Alignment Lab). Its evaluation and red-teaming offerings overlap with Forest AI's AI Validation Tools and fairness/drift capabilities at a much larger scale.

Emerging players

• Confident AI (DeepEval): Confident AI builds DeepEval, an open-source LLM evaluation framework, comparable to Forest AI's open-source PeerBench SDK in approach and developer audience, though narrower in agentic and sealed-execution scope.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat4 records

Key risks5 records

Key highlights5 records

Customer concentration

• Xx.com/forest_ai_
• LinkedInlinkedin.com/company/forest-ai-org

Revenue estimate

Valuation estimate

Number of profiles

Profiles3 records

Funding overview

Funding rounds1 record

Investors1 record

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Forest AI