In the first post in this series, we made the case that threat intelligence has a relevance problem.
Security teams have access to more threat intelligence than ever before. But knowing that a vulnerability is being actively exploited, a threat actor is targeting your industry, or malicious infrastructure has appeared is different from knowing whether any of it actually affects you.
Does the affected technology exist in your environment? Are any of your assets exposed? Has related activity already appeared in your telemetry? Is this something your team needs to investigate now or another signal that can safely be deprioritized?
Relevance is inherently specific to the organization. Threat intelligence needs to be, too.
Client-Tailored Threat Intelligence (CTTI) is designed around that premise. It combines Dataminr’s external threat intelligence with the customer’s own security environment, then delivers that context directly into the workflows analysts already use. The result is intelligence that doesn’t simply tell you what’s happening externally, but helps answer what that development means for your organization.
So what actually happens between Dataminr detecting an emerging external signal and an analyst receiving intelligence that already understands their environment?
It happens in four continuous steps.
Step 1: Detect and Assemble External Threats Continuously
Before intelligence can be tailored to an organization, the underlying threat has to be detected. And when threats are moving quickly, the timing and breadth of that detection matter.
Start with the earliest possible threat signal
Many threats don’t begin with a neatly packaged advisory. They emerge as fragments: a piece of code, infrastructure activity, an image, a conversation, an indicator, or another seemingly isolated signal.
Dataminr’s Multi-Modal Fusion AI continuously processes text, images, machine signal spikes, and generative anomaly detection across more than 1.3 million public sources. More than 100 specialized AI models work in parallel to identify and connect low-signal fragments while threats are still forming.
That allows Dataminr to surface indicators earlier in the threat lifecycle, rather than waiting for a threat to become widely known or appear in downstream reporting.
Earlier detection matters because every additional minute can create more time to investigate and prepare. But speed alone isn’t enough. The next challenge is understanding what those early signals add up to.
Assemble the threat picture automatically
A single indicator rarely provides everything an analyst needs to understand an emerging threat.
Dataminr Intel Agents continuously assemble an evolving intelligence picture around incoming signals, correlating actors, indicators of compromise (IOCs), tactics, techniques, and procedures (TTPs), CVEs, MITRE ATT&CK mappings, infrastructure, exploitability, and other available context.
Instead of requiring an analyst to discover a signal and then manually research what surrounds it, CTTI begins building that context as the situation develops.
The progression looks less like: Detect signal → Send alert
And more like: Detect fragments → Correlate them → Assemble an evolving threat picture
More Than a Decade of Data
That detection and assembly capability is built on a broader Dataminr for Cyber Defense foundation, not CTTI alone.
Dataminr processes more than 43 TB of public data each day across more than 1.3 million sources, with its AI trained on more than a decade of historical event data. That combination of real-time signals and historical intelligence helps the platform recognize patterns, connect fragmented information, and surface emerging threats earlier.
CTTI builds on that foundation, because detecting and assembling the external threat is only the first step. The next question is the one traditional threat intelligence often leaves to the analyst: What does this mean for our environment?
Step 2: Tailor to Your Environment Automatically
This is where external threat intelligence becomes client-tailored threat intelligence.
CTTI brings together what’s happening externally with what’s known internally about the customer’s environment.
YOUR ENVIRONMENT = Assets + Controls + Identities + Alert history
Instead of treating organizational context as something an analyst adds after receiving intelligence, CTTI uses that context to help determine whether the intelligence is relevant in the first place.
Bring internal context into the intelligence
Security teams already have much of the information needed to establish relevance. The problem is that it’s distributed across the stack.
A SIEM may contain relevant alert activity. An EDR platform knows what’s happening at the endpoint. A vulnerability management tool knows which assets are affected by a CVE. Identity, network and cloud tools contain still more pieces of the picture.
Traditionally, analysts have had to move among those systems themselves, searching for evidence and manually connecting what each tool knows back to the original threat.
CTTI connects to the existing security environment so that internal context can inform the intelligence automatically. Signals can be evaluated against the organization’s technology and telemetry, while predictive assessment of how activity is changing, such as acceleration, spread and shifting targets, helps elevate urgency as a situation develops.
Filter for relevance, not just severity
This distinction matters because a threat’s importance in the broader security landscape doesn’t necessarily determine its importance to a particular organization.
Consider an actively exploited critical vulnerability. If your organization doesn’t use the affected technology, the threat may warrant awareness but little immediate action. If the vulnerable technology supports a critical system, exposed assets are running the affected version, and related activity appears in your environment, the same external intelligence means something very different.
CTTI helps make that distinction by filtering signals through client-specific relevance rather than relying on pattern matching alone.
Same external threat. Different environment. Different relevance.
This also helps reduce false positives and noise. Instead of asking analysts to investigate every potentially important external development and determine whether it applies to them, CTTI uses the environment itself as part of the relevance filter.
Search across the stack without manual pivots
When deeper investigation is needed, Investigation Insights provides federated search across more than 200 connected systems, including SIEM, EDR, NDR, and vulnerability tools.
An analyst can search across the connected security stack to confirm exposure, identify prior sightings, and correlate related activity without manually querying each system or learning the query language for every tool.
That changes a familiar dynamic in security operations. Traditionally, the analyst becomes the integration layer, moving between systems and assembling the context needed to understand a threat. With CTTI, those systems instead become sources of context that can help establish whether a threat matters to the organization.
Step 3: Deliver In-Workflow Instantly
Even highly relevant intelligence can lose operational value if analysts have to leave their existing workflow to find it. That’s why the next step isn’t another portal. It’s bringing client-tailored intelligence directly to the places analysts already work.
Bring intelligence to the analyst—not the analyst to the intelligence
CTTI can appear over SIEM, EDR, ticketing and browser tools, giving analysts access to external threat intelligence and the relevant organizational context without requiring them to move into a separate interface.
The traditional process might look something like this: Alert → Open other tools → Search → Correlate → Establish relevance → Investigate
CTTI compresses that process: External signal + Organizational context → Client-tailored intelligence → Investigate
The goal isn’t to eliminate investigation. It’s to eliminate as much of the manual work required to determine whether something is worth investigating as possible.
Turn context into investigation
This is where threat intelligence becomes operational: Knowing about a threat is awareness. Knowing how that threat intersects with your specific environment creates a basis for action.
By making that context available inside existing security workflows, CTTI reduces the manual handoff between detecting a threat, establishing its relevance, and beginning an investigation.
An analyst can spend less time asking, Where do I look for the information I need? and more time answering, What do we need to do about this?
Operationalizing threat intelligence shouldn’t require analysts to manually connect every piece themselves. The intelligence should arrive closer to the point where a decision can be made.
Step 4: Predict and Update Continuously
Establishing relevance once isn’t enough, because threats evolve. New infrastructure appears. Exploitation increases. Adversaries change tactics. New external signals emerge. At the same time, what’s happening inside the organization can change.
Client-tailored intelligence therefore can’t be a static enrichment step.
Relevance isn’t static
Imagine an emerging threat doesn’t appear to affect your organization when it’s first detected.
At 9 a.m., there may be no evidence that your environment is exposed. But as the day unfolds, new information could change that assessment. Researchers may uncover additional affected technologies. Exploitation may accelerate. An actor may begin targeting your industry. Related activity may surface internally.
The original threat hasn’t simply accumulated more information. Its relevance to your organization has changed.
Dataminr Intel Agents continuously assess evolving situations and update intelligence as new signals emerge, so analysts aren’t working from the threat picture that existed when the first alert arrived.
This is an important distinction between simply enriching an alert and maintaining client-tailored intelligence over time.
Move from what matters now to what may matter next
Continuous assessment also allows CTTI to look beyond the current state of a threat.
Predictive assessment of how activity is changing, such as acceleration, spread and shifting targets, can help elevate urgency as situations evolve. Rather than waiting for every piece of evidence to arrive before reassessing a threat, analysts gain a continually updated view of what deserves attention now and what may deserve attention next.
The goal isn’t to predict every outcome. It’s to give analysts a better understanding of how a threat is developing and how its relevance to their environment is changing with it.
What the Four Steps Change for the Analyst
Each of these steps addresses a different part of the intelligence-to-action gap:
- DETECT + ASSEMBLE — What’s happening?
- TAILOR — Does it matter to us?
- DELIVER — Put that intelligence where analysts can act on it.
- PREDICT + UPDATE — How is the threat—and its relevance to us—changing?
Intel Agents continuously reassess the situation as new signals emerge.
Together, those steps change the unit of threat intelligence.
Instead of stopping at “This is happening,” CTTI moves toward “This is happening, this is how it intersects with your environment, and this is why it deserves your attention.”
Because relevance isn’t something that can be determined from the external threat landscape alone. It emerges at the intersection of what’s happening in the world and what’s true inside your organization.
And that intersection is different for every organization.
