01
Context is scattered
An alert alone does not explain asset relevance, related intelligence or what happened next.
INTELLIGENCE FOR THE SOC. ACCOUNTABILITY FOR AI.PRAJNERA / SECURITY OPERATIONS
See the risk.
Understand the why.
Own the response.
Connect security investigations, exposure intelligence and AI oversight. Give analysts the evidence to move forward—and the control to decide.
YOUR NEXT DECISION
Analyst reviewFrom signal to context.
OBSERVESecurity signalSource + asset context
UNDERSTANDAI investigationEvidence + explanation
DECIDEHuman approvalPolicy + recorded outcome
Unusual activity on a critical asset
IN REVIEWCorrelate observations before choosing a response.
Observation receivedRecordedInvestigation contextAvailableResponse recommendationReview required
An illustrative product story based on demo workflows. No live customer data or response actions.
CONNECTED SECURITY OPERATIONSInvestigatePrioritiseGovernExplain
THE OPERATIONAL CHALLENGE
Your tools have signals.
Your team needs answers.
Alert queues, vulnerability findings and AI recommendations compete for the same attention. Bring their context into the decision—not another disconnected report.
02
Risk changes faster than queues
Severity is one input. Exploitation evidence, probability and exposure help shape the next review.
03
AI needs oversight
Know which agent contributed, what policy applied and where a person needs to intervene.
EXPLORE THE PLATFORM
One connected picture.
Four ways to act on it.
Choose an area to explore the workflows demonstrated in the product.
01 / PRAJNERA
Investigate with context
Follow the case from observation to recovery, with evidence and analyst decisions in view.
Explore capability ↗02 / PRAJNERAFocus on meaningful exposure
Review NVD, CISA KEV and EPSS context alongside assets, priorities and remediation.
Explore capability ↗03 / PRAJNERAConnect intelligence to the case
Bring indicators and CVE context into investigations, with source and freshness visible.
Explore capability ↗04 / PRAJNERAMake AI activity accountable
Explore agent inventory, policy decisions, pause controls and human approval boundaries.
Explore capability ↗FOLLOW A CASE
The next step should
have a reason.
Explore the five-stage lifecycle. Each stage connects evidence with an explicit analyst decision.
DETECT / CONCEPTUAL WALKTHROUGH
Start with the observation.
Review the signal and its available evidence before deciding what needs attention.
- Evidence to review
- Observation, source and initial context
- Analyst decision
- Triage the signal and identify the next question
INVESTIGATE / CONCEPTUAL WALKTHROUGH
Build a defensible explanation.
Connect observations with relevant context. Keep AI-assisted interpretation separate from deterministic checks and analyst conclusions.
- Evidence to review
- Related observations, context and investigation notes
- Analyst decision
- Assess the explanation and identify missing evidence
MITIGATE / CONCEPTUAL WALKTHROUGH
Consider the available response.
Review the proposed measures, their scope and the policy considerations that affect the decision.
- Evidence to review
- Proposed mitigation, rationale and review status
- Analyst decision
- Decide what is appropriate and what requires approval
CONTAIN / CONCEPTUAL WALKTHROUGH
Track the containment decision.
Record the decision, approval and action status. A recommendation or approval does not establish that an external system executed an action.
- Evidence to review
- Approval, action status and recorded outcome
- Analyst decision
- Confirm authorisation and check the reported result
RECOVER / CONCEPTUAL WALKTHROUGH
Review the outcome and retain evidence.
Follow recovery status and preserve the evidence needed to understand the case and the decisions made along the way.
- Evidence to review
- Recovery status, case record and supporting evidence
- Analyst decision
- Review closure and carry forward relevant lessons
Illustrative workflow. These controls explain the process; they do not connect to live systems or execute response actions.
OUR DIFFERENCE / AI GOVERNANCE
AI can recommend.
Accountability stays visible.
See the agent, its purpose and the policy behind a decision. Explore oversight within the SOC, and discuss the integration scope for enterprise AI agents.
Explore AI oversight ↗ILLUSTRATIVE POLICY TRACE
Recommendation → Review
- Agent
- Investigation assistant
- Policy check
- Human approval required
- Decision
- Awaiting analyst review
- Execution
- Not dispatched
Keep intent, authorisation and execution separate.
INTELLIGENCE YOU CAN INTERROGATE
More than a severity score.
Examine the source, exploitation context and freshness behind a vulnerability record.
NVDCVE details & severityCISA KEVKnown exploitation contextFIRST EPSSExploitation probabilitySource healthFreshness & missing fields
These are intelligence sources, not endorsements or partnerships. Source availability and coverage vary; probability is not proof of exploitation.
OUR VISION
Trust in every
digital action.
A world where organisations can understand and trust actions taken by people, systems and AI agents.
OUR MISSION
Connect intelligence
with accountability.
Help security teams investigate risk, govern AI-assisted decisions and carry evidence through the response.
Meet the Prajnera approach ↗SEE THE WORKFLOW IN CONTEXT
Bring your questions.
Follow the evidence.
Request a guided walkthrough around your SOC priorities. We’ll discuss the scope and arrange demo access separately.
BEFORE YOUR WALKTHROUGH
Start with the right questions.
What does the demo show?
Security investigation and response workflows, vulnerability intelligence, threat intelligence, detection review, asset context and AI governance. Agree the data and actions in scope before the walkthrough.
Can Prajnera monitor our enterprise AI agents?
The demo includes agent inventory and bounded controls for supported agents. Enterprise agent coverage depends on instrumentation, connected control points and permissions. We scope those requirements with your team.
Does AI execute every response automatically?
No. Recommendations, approvals, simulated outcomes and externally executed actions are different states. Live dispatch requires the relevant adapter, permissions and approval.