How to Choose a Threat Intelligence Company: Questions to Ask in Your RFP

Author : oliver tree | Published On : 14 Oct 2026

Choosing a threat intelligence company is one of the few security decisions that shapes every alert, investigation, and board report that follows. A weak choice leaves analysts sorting through noise, while a strong one gives them early warning they can act on.

The challenge is that every threat intelligence company claims broad coverage, real-time data, and AI-driven insight. Without a structured RFP, those claims are hard to compare, and the loudest pitch often wins over the best fit.

This guide gives you the questions to put in your RFP, grouped by what matters most, so you can evaluate each threat intelligence company on evidence instead of marketing language.

Why Your RFP Decides Which Vendor Fits Your Team

An RFP makes every vendor answer the same questions in the same format, which is the only reliable way to compare them. Without one, “dark web coverage” can mean a handful of public paste sites for one vendor and thousands of closed sources for another.

A good RFP also protects your time. Vendors that cannot answer specific questions about sources, methods, and integrations tend to reveal that early, before you invest in demos.

What to Define Before You Approach a Threat Intelligence Company

Your questions are only as sharp as your requirements. Settle these internally first:

• Primary use cases: dark web monitoring, brand protection, attack surface management, vulnerability prioritization, or executive risk reporting
• Who consumes the intelligence: SOC analysts, threat hunters, fraud teams, or leadership
• Your existing stack: SIEM, SOAR, ticketing, and endpoint tools the intelligence must feed
• Success metrics: faster detection, fewer false positives, reduced time to takedown, or compliance evidence

Data Source and Coverage Questions to Ask Every Threat Intelligence Company

Coverage is the foundation, so start here. Ask each vendor:

• Which source types do you collect from: dark web forums, marketplaces, Telegram channels, stealer logs, ransomware leak sites, and open sources?
• How do you access closed or invite-only communities, and in which languages?
• How quickly does new data appear in the platform after it surfaces?
• Which data is collected first-hand, and which is licensed or aggregated from third parties?
• Can you show sample alerts relevant to our industry and region?

Vague answers to these questions usually mean thin collection behind a polished interface.

Analysis, Context, and AI Questions for a Threat Intelligence Company

Raw data is not intelligence. The value lies in how it is filtered, enriched, and explained. Ask:

• How do you turn collected data into prioritized, actionable alerts?
• Where is AI used in the workflow, and where do human analysts review the output?
• How do you measure and reduce false positives?
• Do you map findings to frameworks such as MITRE ATT&CK?
• Can the platform explain why an alert received its risk score?
• How do you profile threat actors and track their activity over time?

Integration and Delivery Questions to Ask a Threat Intelligence Company

Intelligence that sits in a separate portal rarely changes outcomes. Ask how it reaches your team:

• Which SIEM, SOAR, and ticketing integrations are supported out of the box?
• Is there a documented API, and are standard formats such as STIX/TAXII supported?
• Can alerts be routed by asset, severity, or team?
• What reporting is available for executives and auditors?

Analyst Support and Service-Level Questions

Platforms are only part of the offer. Ask whether you get direct access to analysts, what response times are guaranteed, and how requests for custom research are handled. Also ask what takedown support is included for phishing sites, fake domains, and impersonation accounts, and what onboarding looks like for the first 90 days.

Security, Compliance, and Trust Questions for a Threat Intelligence Company

You are trusting this vendor with sensitive information about your organization, so apply the same scrutiny you would to any critical supplier:

• Which certifications and audits does the vendor hold?
• Where is customer data stored, and who can access it?
• How are sensitive findings, such as leaked employee credentials, handled and shared?
• How does the vendor collect data legally and ethically?
• Can you speak with reference customers in your industry?

Pricing and Proof-of-Concept Questions

Ask what the pricing model is based on (assets, users, modules, or data volume) and what is excluded from the base price. Clarify renewal terms, overage charges, and exit conditions. Then request a proof of concept using your own domains, brands, and executives, with success criteria agreed in advance. A vendor confident in its intelligence will welcome that test.

How to Score Responses From Each Threat Intelligence Company

A weighted scorecard keeps the decision objective. The weights below are a starting point; adjust them to your priorities.

Score every vendor against the same table, and have at least two stakeholders score independently before comparing notes.

Why Teams Evaluate Cyble as a Threat Intelligence Company

Cyble is an AI-native cybersecurity company that delivers threat intelligence through Cyble Vision, covering areas such as dark web monitoring, brand intelligence, and attack surface visibility. Teams add Cyble to their shortlist when they want AI-assisted analysis that turns large volumes of underground data into prioritized, explainable alerts.

The most useful way to evaluate Cyble is the same way you would evaluate anyone else: send the RFP questions above, ask for sample alerts for your sector, and run a proof of concept against your own assets.

Conclusion

The right threat intelligence company is the one that answers your RFP questions with evidence: real sources, explainable analysis, clean integrations, and terms you can verify in a proof of concept. Use the scorecard above, insist on testing with your own assets, and include Cyble in the comparison to see how an AI-native platform performs against your criteria.