It starts with a single indicator of compromise or a vague tip from a partner. Maybe it is a suspicious IP address, a hash, or a mention of a new threat actor group targeting your sector.
You open your first browser tab to check a reputation engine. Then you open a second tab to search for associated malware families. That leads to a vendor blog post, which references a technique, so you open the MITRE ATT&CK framework in a fourth tab.
Ten minutes later, you have fifty tabs open. You are frantically Ctrl+F searching through PDF reports, trying to manually stitch together a timeline that makes sense.
The problem with threat intelligence today is not a lack of data. It is the friction of consumption.
We spend more time managing our browser windows than we do analyzing the actual threat.
The Context Switch Cost
The real cost of this workflow isn't just time; it is cognitive load. Every time you pivot from a raw log to an external report, you lose a little bit of focus. You have to translate the generic language of a vendor report into the specific context of your environment.
We built ThreatLandscape.ai because we were tired of this retrieval loop. We wanted to move from "searching" to "reasoning."
When we treat intelligence as a conversation rather than a library, the workflow changes dramatically.
Moving to Interactive Analysis
Instead of gathering ten different documents to answer the question, "Is this IP related to recent ransomware campaigns in Europe?", we simply ask the question.
This is where the concept of a "Copilot" becomes more than a buzzword.
In a traditional workflow, answering that question requires cross-referencing three different data sources. In our updated workflow, the system acts as the synthesis layer. It pulls the reputation, checks the history, scans recent campaign reporting, and presents the connection instantly.
Role-Based Intelligence
The other major friction point we wanted to eliminate was generic reporting.
A Tier 1 SOC analyst needs to know if they should isolate a host. A Threat Hunter needs to know the TTPs to look for in historical logs. A CISO needs to know the business risk.
Usually, these three people have to read the same long-form report and extract different paragraphs.
By using an interactive model, we can shape the output based on who is asking. I can ask the system to "explain this threat for a detection engineer," and it will strip away the high-level fluff and focus on behavioral logic and Sigma rules.
The Result
The goal of this approach is not to replace the analyst. It is to let the analyst skip the data collection phase and go straight to decision making.
If we can reduce the time it takes to understand a threat from an hour of reading to five minutes of questioning, we are not just saving time. We are closing the window of opportunity for the adversary.
We are currently opening up access to analysts who want to test this conversational workflow against their current stack.
If you are tired of the fifty-tab investigation, come see how we are doing it.