Our privacy practices comply with data protection laws, including the EU data protection regulatory framework, GDPR, and the California Consumer Privacy Act of 2018 (CCPA) – respecting requests to exercise privacy rights and more.
Monitor and influence what AI systems say about your brand
Systematically query AI assistants, audit LLM accuracy, and track your brand’s share of voice in AI-generated answers, before your competitors do.
- Structured LLM response collection
- Cross-model brand tracking
- Integrated API delivery
- 100% compliant data
Brand & Marketing Teams
Know what AI systems are saying about your brand right now
Systematically collect and analyze AI-generated responses about your brand, products, and competitors across ChatGPT, Gemini, Claude, and Perplexity to understand your AI share of voice and track how it shifts over time.
Regulated Industry Compliance Teams
Verify what AI says about your products before it causes harm
For pharma, finance, and healthcare brands, public LLMs must give factually correct answers about your products. Systematically audit AI responses at scale to surface inaccuracies, outdated information, and compliance risks before they reach patients or customers.
Trusted by 20,000+ customers worldwide
AI monitoring and LLM auditing popular use cases
Track LLM Brand Mentions at Scale
Systematically query ChatGPT, Gemini, Claude, Perplexity, and other AI assistants with prompts about your brand, products, and competitors. Collect and structure responses at scale for analysis, giving you a continuously updated picture of how AI represents your brand across every major model.
Audit AI Accuracy for Regulated Industries
For pharma, finance, and healthcare brands, verify that public LLMs are giving factually correct answers about your products, dosages, indications, and services. Surface inaccurate, outdated, or potentially harmful AI responses before they reach patients, customers, or regulators.
Competitive AI Share of Voice
Understand how often and how favorably your brand appears in AI-generated answers compared to competitors. Track your AI share of voice over time as models are updated, retrained, and supplemented with new web data, and act on shifts before they affect customer acquisition.
LLM Response Change Detection
Run scheduled queries against AI assistants and detect when responses about your brand, products, or industry change. Surface model updates, knowledge cutoff effects, and emerging misinformation early so your team can respond with corrective content or direct data interventions.
AI-Driven Competitor Intelligence
Collect and analyze how AI assistants describe, recommend, and compare your competitors across thousands of prompts. Identify positioning gaps, surface competitor narratives being amplified by AI, and use structured response data to sharpen your own messaging and content strategy.
AI Brand Safety and Misinformation Monitoring
Detect when AI assistants generate inaccurate, misleading, or brand-damaging responses about your organization. Build systematic monitoring pipelines that surface misinformation risks across models and geographies, giving your brand protection team early visibility and time to act.
Ready to start collecting structured LLM responses at scale? Explore our AI data infrastructure
Industry Leading Compliance
Why 20,000+ Customers Choose Bright Data
100% Compliant
All data collected and provided to customers are ethically obtained and compliant with all applicable laws.
24/7 Global Support
A dedicated team of customer service professionals is available to assist you at any time.
Complete Data Coverage
Our customers can access over 400M+ monthly IP addresses worldwide to query AI assistants and collect structured LLM responses across any model, geography, or prompt set.
Unmatched Data Quality
With our advanced technology and quality assurance processes, we ensure structured, consistent, and accurately captured LLM response data ready for analysis and longitudinal tracking.
Powerful Infrastructure
Our infrastructure supports systematic, high-volume querying of AI assistants at scale, with scheduled pipelines that deliver fresh structured response data to your team without manual effort.
Custom Solutions
We provide tailored LLM monitoring and auditing solutions to match your brand's specific models, prompt sets, geographies, and compliance requirements.
Frequently Asked Questions
Is systematically querying public AI assistants for brand monitoring allowed?
Yes. Querying publicly accessible AI assistants such as ChatGPT, Gemini, Claude, and Perplexity is permissible under applicable legal and terms-of-use frameworks when done for legitimate brand monitoring, auditing, and research purposes. Bright Data's infrastructure supports compliant, structured collection of publicly accessible AI-generated responses at scale.
Read more: Code of Ethics and Conduct
Which AI assistants and LLMs can Bright Data query for brand monitoring?
Bright Data's infrastructure supports systematic querying across all major publicly accessible AI assistants including ChatGPT, Gemini, Claude, Perplexity, and others. Coverage can be expanded as new models become publicly accessible, ensuring your monitoring program keeps pace with the evolving AI landscape.
How does LLM brand monitoring work in practice?
You define a set of prompts relevant to your brand, products, competitors, or industry. Bright Data's infrastructure runs those prompts across selected AI assistants on a scheduled basis, collects the structured responses, and delivers them to your team for analysis. Changes in responses over time are tracked and surfaced automatically.
Why is LLM auditing particularly important for pharma, finance, and healthcare brands?
In regulated industries, AI assistants are increasingly being consulted by patients, consumers, and professionals for product information, dosage guidance, and financial advice. Inaccurate or outdated LLM responses in these contexts carry real compliance and reputational risk. Systematic auditing gives regulated brands visibility into what AI is saying and the evidence needed to act on inaccuracies.
How does Bright Data measure AI share of voice?
By running structured prompt sets at scale and collecting responses across multiple AI models over time, Bright Data enables teams to analyze how frequently and favorably their brand appears in AI-generated answers relative to competitors. This data can be tracked longitudinally to surface shifts as models are updated or retrained.
How does Bright Data ensure compliance when collecting LLM response data?
Bright Data collects publicly accessible data only and operates in full compliance with GDPR, CCPA, and SOC2. All customer relationships are KYC-verified to ensure our infrastructure is used exclusively for legitimate monitoring and auditing purposes.
Bright Data has designed a detailed Privacy Policy to provide all required information about its privacy practices.
What security measures does Bright Data have in place?
Bright Data manages data for over 15,000 organizations around the world. Our security model is based on international standards including ISO 27001, ISO 27018, CSA Star level I, SOC2, and OWASP Top 10, as well as best practices for data encryption, infrastructure security, and external security audits.
How frequently can LLM queries be run for ongoing brand monitoring?
Query frequency is fully configurable. Pipelines can be scheduled to run daily, weekly, or at custom intervals depending on how closely you need to track LLM response changes. For fast-moving brand situations or regulated industries requiring continuous oversight, higher-frequency monitoring can be configured.
Can I get a sample of structured LLM response data before committing?
Yes, we can provide samples for evaluation; please contact our sales representatives.
Can Bright Data monitor LLM responses across multiple geographies and languages?
Yes. With access to over 400M+ monthly IP addresses worldwide, Bright Data can query AI assistants from any geographic location and collect responses in multiple languages, giving global brands a complete picture of how AI represents them across markets.