Avik Roy
Former Advisor to Marco Rubio
Kevin McCarthy
Sports AnalFormer Republican Speaker of the Houseyst, former NFL player, author
Hon. Ivan Duque Marquez
Former President of Columbia
Jackie Reses
Chair and CEO Lead Bank
Sir Niall Ferguson
Historian, Author, Senior Fellow Hoover Institute, Stanford
Vuk Jeremic
Former President UN General Assembly
Dr. Jordan Shlain
Physician, Private Medical
Larry Summers
Former US Treasury Secretary
Scott Jennings
Republican Political Strategist
Kristen Soltis Anderson
Republican Pollster
Elizabeth Economy
Senior Fellow Hoover Institute, Stanford (China)
Emmanuel Acho
Sports Analyst, former NFL player, author
Emmanuel Acho
Sports Analyst, former NFL player, author

Leading experts in the loop, for the most important topics

Our systems scale the judgment of world-leading experts to help AI teams evaluate and improve their models in areas that demand careful oversight.
PROBLEM

Some areas of AI development require nuanced oversight from trusted experts to get it right...

News
& Current Events

Mental
Health

Culture
& Society

Ethics
& Safety

Education
& Guidance

Finance
& Economics

At Forum AI, we build systems to scale trusted expert judgement for AI evaluation, focused on the areas where expert insight matters most.

network

Our network includes the world’s leading minds and institutions

Forum AI’s network includes former Cabinet officials, Fortune 500 executives, leading researchers, and the analysts who move markets.

Apply to the network
Apply to the network
Larry Summers
Former US Treasury Secretary
Hon. Ivan Duque Marquez
Former President of Columbia
Dr. Yen Pottinger
Infectious disease specialist
Kevin McCarthy
Former Republican Speaker of the House
Scott Jennings
Republican Political Strategist
Vuk Jeremic
Former President UN General Assembly, former Serbian Foreign Minister
Fareed Zakaria
Author and host, CNN
Rich Goldberg
Former Trump administration foreign policy advisor
Kristen Soltis Anderson
Republican Pollster
Sebastian Kurz
Former Chancellor of Austria
Michael McFaul
Former US Ambassador to Russia
Avik Roy
Former advisor to Secretary of State Marco Rubio
Elizabeth Economy
Senior Fellow Hoover Institute, Stanford (China)
We also work with several
leading institutions
our mission

Our mission is to ground AI's understanding of the most complex topics in human expertise, not algorithms.

Something about what DIFFERENTIATES US → the complex things like bias, accuracy, tone… high stakes scenarios

Our mission is to make human expertise— not algorithms—the foundation of real-time knowledge in the AI era.

how it works

We turn expert insights into game-changing intelligence

Our expert-guided process delivers precision data and AI models for news and complex topics.

1. Expert Inputs
Our network of world-leading experts share critical insights and label news sources for bias and other critical factors
2. Data Optimization
Our sophisticated systems transform these raw expert inputs into structured data products and AI models
3. AI System Delivery
Leading AI companies use Remark’s data and labeling models to improve how their systems handle news and sensitive topics
Offerings

We scale the judgement of world-leading experts to evaluate and improve AI

Our systems scale expert judgment for repetitive tasks while engaging them directly for high-leverage work like defining success criteria.

Model Evaluation
Data QA
Data to Fill Gaps

Hands-on Human Evaluation Reports

We evaluate model performance end to end, delivering detailed, expert-backed reports and recommendations. Our expert-trained AI systems handle repetitive annotations at scale, while experts focus on high-impact work—reviewing results and shaping recommendations.

Benchmarks

Prompts sets and evaluation rubrics to support internal evaluation efforts, custom built with experts for your use cases.

Expert-trained LLM Judges

Access Forum AI’s judges via API, fine-tuned for your use cases, built for auto evals and reward modeling.

Training Data Annotation

We partner with your team and our experts to define an evaluation strategy, conduct a comprehensive evaluation of model performance, and then provide detailed reports with expert-backed recommendations for the team.

Retrieval Source Annotation

Forum AI integrates into the search & retrieval stack to label sources with nuanced details to improve LLM prioritization and interpretation of real-time sources.

Licensed Retrieval Packs

Licensed retrieval sources to ensure you have reliable, comprehensive coverage of news and evolving topics.

SFT Data Packs

Expert-designed packs of prompt-response pairs, targeted at addressing specific gaps or issues.

Evaluation

We partner with teams to evaluate their models, offering bespoke support from start to finish

Benchmarks

Prompts sets and evaluation rubrics to support internal evaluation efforts, custom built with experts for your use cases.

Expert-trained

Access Forum AI’s judges via API, fine-tuned for your use cases, built for auto evals and reward modeling.

"In an era where AI can generate infinite content but lacks the wisdom to prioritize truth, Forum AI offers a vital platform: one where real expertise reclaims its voice."

Fareed Zakaria
Author, CNN Anchor

"In an era where AI can generate infinite content but lacks the wisdom to prioritize truth, Forum AI offers a vital platform: one where real expertise reclaims its voice."

Kevin McCarthy
Author, CNN Anchor

Lorem ipsum cursus viverra porttitor porttitor quisque massa consectetur ante pellentesque nibh laoreet mi vitae ac lacinia id ultrices lectus.

First Last
AI Researcher
BENEFITS

Remark has partnered with teams to improve AI system accuracy, tone, depth, and more

Blog

Read our articles

See All
See All
Learn more
THE NUMBERS

Labs working with Remark have been able to improve AI system outputs across several critical dimensions.

+99%
Human preference for Remark-supported responses in blind tests
25%
Reduction in response bias
20%
Improvement in response depth
15%
Overall improvement in AI response quality
Eval results showing how Remark annotations on retrieval data improve Perplexity model responses.
Book a demo
Book a demo