2026 Panel Book · network Explorer
The Human Network Behind AI
Meet the 7.6 million people providing the data, judgment, and expertise that help companies train, evaluate, and improve AI.
Network Overview
Our human network is built for quality, expertise, and integrity at scale
AI is only as strong as the human input behind it. As the pace of building accelerates, fast access to the right people, judgment, and expertise matters more than ever.
Network Scale
7.6M
Unique people within the network
3.2M
Professionals working in 140 industries
34
Core countries, plus custom sourcing for additional markets
5.3M
Sessions completed in the last 12 months
18.6%
Annual growth rate of the network
Quality and fraud statistics reflect the network where our proprietary matching and fraud-prevention systems currently operate, forming the quality foundation for the broader Auros network.
Network Integrity
98.6%
Positive post-session ratings
7.3%
No-show rate for moderated sessions
0.6%
Of sessions reported for suspected fraud
0.2%
Of sessions confirmed as fraudulent
<1hr
Median time to first qualified match
Quality and fraud statistics reflect the network where our proprietary matching and fraud-prevention systems currently operate, forming the quality foundation for the broader Auros network.
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Geographic breakdown
Reach the right people across 34 core markets
Source human data, judgment, and expertise across 34 core markets, with custom sourcing available for specialized audiences and additional geographies.
Country
Consumers
Professionals
🇺🇸 United States
3,365,962
2,211,798
🇨🇦 Canada
294,493
189,700
🇧🇷 Brazil
99,531
51,210
🇲🇽 Mexico
29,672
16,750
🇨🇱 Chile
8,302
5,179
🇦🇷 Argentina
7,141
4,256
🇵🇷 Puerto Rico
6,534
4,296
Country
Consumers
Professionals
🇮🇳 India
276,727
101,958
🇦🇺 Australia
103,120
65,866
🇳🇿 New Zealand
12,138
7,950
🇲🇾 Malaysia
10,976
5,607
🇸🇬 Singapore
10,483
6,271
🇯🇵 Japan
3,891
2,557
Country
Consumers
Professionals
🇿🇦 South Africa
202,362
92,847
🇬🇧 United Kingdom
185,410
128,804
🇫🇷 France
74,869
31,558
🇪🇸 Spain
63,929
25,559
🇩🇪 Germany
59,006
28,958
🇳🇱 Netherlands
28,258
13,059
🇸🇪 Sweden
16,167
6,998
🇵🇱 Poland
15,542
7,961
🇮🇹 Italy
13,128
6,465
🇵🇹 Portugal
13,108
7,567
🇮🇪 Ireland
12,388
8,203
🇷🇴 Romania
9,579
5,283
🇧🇪 Belgium
7,932
3,627
🇬🇷 Greece
7,259
4,143
🇦🇹 Austria
6,226
2,810
🇨🇭 Switzerland
5,241
2,899
🇧🇬 Bulgaria
4,839
2,752
🇨🇿 Czechia
4,490
2,188
🇩🇰 Denmark
4,401
2,605
🇳🇴 Norway
4,129
2,491
🇫🇮 Finland
3,675
1,961
Network overview
Who’s in the network, and how to target them
Target by demographics, devices, behaviors, product usage, professional background, and more.
Network overview
Human data and evaluation in practice
Case study: Data Collection
Large-scale physical data collection
Audience
10,000+ technology participants across major U.S. metros
Work
Three-hour onsite data collection and physical-device testing
Customer
Research agency on behalf of a major technology company
Case study: AI Outputs
Expert evaluation of AI-generated financial outputs
Audience
30 CFOs and senior finance leaders
Work
One-hour sessions across five iterative cycles reviewing financial reports and forecasts
Customer
Fintech company
Case study: Agent Building
Agent onboarding evaluation
Audience
Engineers who build and deploy AI agents
Work
One-hour think-aloud evaluation covering onboarding and building a first agent
customer
AI infrastructure startup
Case study: Professional Expertise
Studying AI in dentistry
Audience
Dentists who use AI in their clinical practice
work
45-minute sessions exploring AI use across diagnostics, imaging, treatment planning, and patient monitoring
customer
Dental product manufacturer and technology company
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Professional network breakdown
Access verified professionals across 140 industries
Access 3.2M professionals with targeting by role, skills, industry, seniority, and company size. Nearly half of applications include professional verification.
Spotlight on professional verification
LinkedIn & work email verification
Know who is behind the judgment. See whether a contributor’s work email or LinkedIn profile has been verified, with additional LinkedIn identity and workplace verification signals where available.
3.2M
professionals
140
industries represented
73k+
unique job titles
23k+
targetable skills
246K
participants have already verified their work email or LinkedIn profile
49%
of project applications come from participants with professional verification
Network overview
Professional expertise in practice
Case study: Business owners
Mapping the buyer journey for POS systems
Audience
Restaurant owners and managers
Study
30-minute interviews about the POS evaluation and decision process
Team
Point of Sale technology provider
Case study: Technology segment
Developer onboarding study
Audience
Engineers who build and deploy AI agents
Study
1-hour “think out loud” study going through the onboarding flow and building a first agent
Team
AI infrastructure startup
Case study: Finance segment
Redesigning an investor portal
Audience
10 investment professionals in specific markets
Study
15-minute website usability test with integrated tool
Team
Financial services and technology company
Case study: Healthcare segment
Studying AI in dentistry
Audience
Dentists who use AI in their clinical practice
Study
45-minute interviews about how AI is used for diagnostics, imaging, treatment planning, and patient monitoring
Team
Dental product manufacturer and technology company
Go Deeper
Get the full 2026 Panel Book – every chart, every cut, every use case.
HUMAN DATA INTEGRITY
Fast matching. Strong human data integrity.
AI-powered matching helps surface the right people fast, while multi-layer fraud defenses help protect the integrity of human input.
How matching works
AI-powered matching, built on years of network data
Our matching goes beyond hard filters, balancing speed, network health, fit, and fraud risk to surface qualified contributors.
01
Hard filtering
Structured criteria (age, location, role) immediately exclude anyone who doesn't qualify.
02
Screener success prediction
AI models analyze past responses and rank participants by likelihood of qualifying.
03
Re-ranking
Balances fulfillment speed, panel health, and fraud risk, prioritizing trusted participants for the most vulnerable studies.
04
Notify & measure
We source applications via targeted notifications and on-platform listings, with continuous measurement of fill rate, speed, and quality.
Matching efficiency
<1hr
to first qualified match
<1 day
to first scheduled session
1 day
median to fill a project
What's new
AI-based embedding models capture the nuance of project requirements beyond keyword matching, while automated tagging helps sharpen targeting precision.
Multi-layer fraud defense
Built to protect human authenticity as fraud evolves
As AI-generated noise rises, our defenses operate at four levels to help ensure the people contributing data and judgment are real, qualified, and trustworthy.
Layer 1
Participant-level detection
At signup, every new participant is automatically evaluated against 50+ fraud signals.
Layer 2
Project-level protections
Higher-risk studies (short screeners, broad criteria) are flagged and routed toward more trusted participants.
Layer 3
Quality & verification signals
Quality signals surface at review: flagged copy-paste responses, activity and ratings history, video screening, and verification badges.
Layer 4
Human oversight
Experienced coordinators investigate suspicious profiles, replace contributors when required, and resolve quality issues.
NETWORK INTEGRITY
98.6%
positive post-session ratings
0.6%
of sessions reported for fraud
0.2%
of sessions fraudulent
What's new
Better occupation-pattern detection, automatic removal of AI-generated screener responses, third-party IP signals, and tighter fraud thresholds as new patterns emerge.
The full report
Get the 2026 Panel Book
Explore the Auros human network: global, deeply profiled, and built for AI.
what's inside
Global consumer and professional network coverage
Targeting, screening, and professional verification
AI training, evaluation, and expert use cases
Human data integrity, matching, and fraud prevention
