In the world of AI and AI agents, context is everything - and more so in SOC as that determines how an analyst is going to approach a challenge. With security teams starting to give AI agents more responsibility for triage, investigation, and response, they need to work from a reliable attack context rather than another stream of disconnected alerts.
Vectra AI is trying to address this with the launch of Vectra AI Pro, a new offering built to give AI agents and human analysts more context when investigating threats inside the security operations center.
The product pulls together activity across network, identity, cloud, software-as-a-service, endpoint detection and response, and secure access service edge environments. It uses that data to identify and connect attacker behaviors, including reconnaissance, credential abuse, privilege escalation, lateral movement, command-and-control activity, and data exfiltration.
Vectra’s answer to XDR correlation
Cross-domain correlation is already part of many extended detection and response and agentic SOC platforms. Vectra says the difference lies in how it creates the signal before it reaches an analyst, agent or workflow.
Mark Wojtasiak, SVP of Market Research and Strategy, Vectra AI, told MSSP Alert, “The difference is where the signal comes from. Most XDR and agentic SOC platforms start with tool data: endpoint alerts, logs, cloud events, identity events, and whatever else is already sitting in the customer’s stack. Then they try to stitch it together, summarize it, and push it into a workflow. That can help, but it is still largely working from the outside in."
Vectra AI Pro works differently because its foundation is behavioral.
"Vectra AI Pro detects, triages, correlates, prioritizes, and contextualizes attacker behavior before it reaches the analyst, the AI agent, or the workflow. The AI agent in the SOC gets answers it needs to reason, understand, and act. Simple answers to questions like: What happened? Who or what was involved? Is this normal? Is this risky? Is this connected to a larger attack? What should we do next?"
Wojtasiak explains that the XDR connects and correlates telemetry across tools, while Vectra AI Pro connects and correlates attacker behaviors across domains.
Vectra AI Pro can be used in three ways. Security teams building their own agentic SOC can access its signal intelligence through REST APIs, a Model Context Protocol server, and a set of AI skills. Those skills cover work such as indicator enrichment, packet capture retrieval, forensic investigations, threat hunting and reporting.
Teams with an existing SOC can use Vectra’s agents to detect and correlate activity, prioritize cases, and produce natural-language investigation summaries. Vectra is also offering services to help customers connect the product to their existing tools, hunting processes, and response workflows.
More data ≠ Better decision
The bigger question for security teams and cybersec vendors is whether feeding an AI agent more security information improves the quality of its decisions. Adding data can just as easily create more noise, especially when the information is incomplete, duplicated, or missing the relationships between events.
Vectra argues that its behavioral signal has already been tested through its use by human analysts, and the company is now making that same information available to AI agents rather than creating a separate signal specifically for automated workflows.
“The evidence starts with the humans already using it. Vectra AI is trusted by more than 2,000 customers, and that trust comes from more than a decade of AI and ML innovation focused on behavioral analytics—understanding attacker behavior across network, identity, cloud, SaaS, and hybrid environments, then turning that behavior into signal analysts can act on."
Wojtasiak says that it is important because the company is not creating a new signal just for AI agents.
"We are giving AI agents the same trusted Attack Signal Intelligence human analysts already use to decide what matters, what is risky, what is under attack, and what action to take. Human analysts already trust this signal in real SOCs. AI agents now get that same decision foundation. If the signal helps human analysts make better decisions, it gives security teams building, adding, or operationalizing Agentic SOC workflows a much stronger foundation for AI decision-making at AI speed,” Wojtasiak said.
What Vectra AI Pro could mean for MSSPs
The MSSP's practical use is especially relevant because providers rarely work across a single technology stack. Each customer may use different identity platforms, endpoint tools, cloud services, and logging systems. Analysts still have to investigate consistently and explain what happened, regardless of how each customer environment is built.
Wojtasiak says that this is one of the places where the value gets very practical.
"MSSPs deal with the hardest version of the SOC problem. Every customer has a different environment, different tools, different maturity level, and different expectations. The MSSP still has to investigate quickly, reduce noise, respond with confidence, and show value."
Vectra AI Pro is designed to give MSSP analysts a common starting point. It shows which entities were involved, how the activity connects, why it matters, and what evidence supports the finding.
“Vectra AI Pro can help by acting as a trusted signal layer across those customer environments. Instead of asking analysts to rebuild the investigation from scratch every time, Vectra AI Pro gives them a clearer starting point: what happened, which entities were involved, how the activity connects, why it matters, and what evidence supports it,” Wojtasiak said.
That could reduce the time analysts spend rebuilding attack timelines from separate tools. It could also help providers create a more consistent investigation process across customers.
“That helps MSSPs standardize how they investigate across different customer stacks. It also helps them maximize the value of their human analysts more effectively,” Wojtasiak said.
For MSSPs, the margin argument also comes down to analyst time. If the platform shortens investigations and reduces low-value alert review, each analyst may be able to support more customers.
“The business impact is straightforward. Better signal means less time wasted on noise. Less time wasted on noise means faster investigations. Faster investigations mean analysts can handle more work without burning out. And when analysts can deliver better outcomes across more customers, service margins improve,” Wojtasiak said.
However, providers will still need to measure those gains rather than assume automation will deliver them. They will also have to decide how Vectra AI Pro fits into their multi-tenant operations, service packages and customer approval processes.
“Moving from monitoring alerts to delivering trusted attack signal, faster investigations, better response support, and clearer proof of value is the real opportunity for MSSPs,” Wojtasiak said.
