Cybersecurity

A force multiplier for security teams

The attack surface is expanding. Talent is constrained. Alert volume is relentless. AI has the potential to change this equation, but only when it amplifies judgment rather than replacing it.

AI needs to move beyond "answering questions" and into problem solving: investigating, correlating, recommending, executing, and continuously improving.

Alert Fatigue

When teams are overwhelmed by noise, true positives get missed, response slows down, and security becomes reactive. Alert fatigue is not just a morale issue. It is a risk issue.

Talent Scarcity

A small number of senior people carry much of the organization's tacit knowledge. Security outcomes should not depend on whether the "right person" is available at the right moment.

Fragmented Tools

Cybersecurity is not a single dataset, team, or decision. It is a connected system of signals, actions, and accountability that spans the entire enterprise.

The Solution

An operating system for cybersecurity AI

Datafi enables organizations of any size to accelerate threat detection and response, reduce alert fatigue, scale scarce expertise, become more predictive and proactive, and communicate risk more effectively to business stakeholders.

10x

Faster Triage

AI assembles context across logs, endpoints, identity events, and cloud activity

80%

Less Noise

Intelligent clustering and enterprise-context prioritization cuts alert volume

24/7

Continuous Defense

AI agents that monitor, correlate, and escalate around the clock

Full

Audit Trail

Every investigation and decision traceable, repeatable, and governed

Threat Detection

Faster threat detection and response

When seconds matter, the bottleneck is rarely "lack of data." It is the time required to assemble context: what happened, where, to whom, with what business impact, and what to do next.

Gather related signals across logs, endpoints, identity events, and cloud activity

Produce coherent incident narratives with sequence, entry points, and next steps

Generate investigation paths like an experienced analyst would

Threat Investigation Suspicious login detected Unusual geolocation + elevated privilege request 0:00 AI correlates 12 related signals Endpoint logs + cloud IAM + ticket history 0:03 Incident narrative generated Timeline, affected assets, likely entry point, impact 0:05 Recommended actions ready Containment steps + escalation path + evidence bundle 0:06 Analyst approves containment Human decision, AI execution — threat contained 0:08 Total time: 8 minutes vs. 4+ hours manual
Alert Prioritization Engine BEFORE: RAW ALERTS 2,400 alerts / day Datafi AI Prioritization AFTER: PRIORITIZED P1 P2 P2 P3 2,380 auto-resolved 4 high-confidence cases for analyst review

Alert Prioritization

Reduced alert fatigue through intelligent prioritization

AI can help, but only when it has enough context to judge what matters. With Datafi, AI moves beyond generic scoring and instead prioritizes alerts using enterprise-specific context, reducing burnout and increasing operational throughput without forcing analysts to trust a black box.

Asset criticality and ownership context

Identity risk and privilege level scoring

Historical incident patterns and known business cycles

Duplicate clustering with "why this matters" explanations

Expertise at Scale

Scaling expertise and institutional knowledge

Cybersecurity expertise is scarce, and it does not scale easily. Datafi helps by turning knowledge into reusable, governed capability. Not replacing people, but ensuring that security outcomes do not depend on whether the "right person" is available at the right moment.

Codified Playbooks

Investigation playbooks executed step-by-step by AI agents

Standard Workflows

Consistency across teams, shifts, and geographies

Embedded Coaching

Less experienced analysts learn by doing inside the workflow

Continuity During Turnover

Investigations and decisions are traceable and repeatable

Knowledge Base Playbooks 47 active Workflows 23 standard Incident History Senior Analyst Knowledge captured Junior Analyst AI-assisted Consistent Outcomes
Predictive Risk Dashboard VULNERABILITY EXPOSURE TREND PREDICTED PROACTIVE SIGNALS DETECTED Privilege creep detected 12 accounts, 3 high-risk Patch latency rising Critical CVEs, 14-day avg Weak signal correlation Early IoC across 4 endpoints Control effectiveness Improving, 94% efficacy

Predictive Defense

Shifting left on risk with proactive defense

The strongest security programs do not just respond to incidents; they continuously reduce the likelihood and impact of future ones. With full access to the security and business data ecosystem, AI creates a feedback loop: the organization learns from incidents and near misses, then improves controls and priorities.

Identify trends in vulnerability exposure, patch latency, and exploitability

Surface risky identity patterns: privilege creep, unusual access, dormant accounts

Map technical risk to business services and processes

Stakeholder Communication

Turning security into shared understanding

Security teams often do exceptional technical work, but struggle to translate it into language that business leaders, product owners, and operational teams can act on. AI helps security leaders communicate with clarity and consistency, reducing friction and improving alignment.

Accurate: grounded in enterprise data and evidence

Relevant: mapped to business processes and priorities

Actionable: with clear options, trade-offs, and recommended paths

AI-Generated Security Reports BOARD Executive Risk Summary Risk posture: Improving Low overall risk OPS Weekly Ops Review 142 incidents handled MTTR: 23min (down 40%) 3 action items INCIDENT Post-Incident Debrief Root cause, timeline, remediation steps 2 policy updates COMPLIANCE Regulatory Status Report SOC 2, ISO 27001, GDPR controls mapped 98% compliant

From copilots to autonomous roles

Organizations increasingly want AI not just for isolated assistance, but for critical thinking workflow automation and analytical roles inside cybersecurity operations. For that to be safe and effective, large language models must have:

1

Full business context

Not just generic security knowledge, but deep understanding of your organization's systems, priorities, and risk posture.

2

Complete data ecosystem

Access to cybersecurity telemetry, identity, cloud, asset inventory, vulnerability data, tickets, policies, and business ownership context.

3

Safe autonomous execution

The ability to execute defined tasks, escalate decisions, and continuously improve, all within governed policy boundaries.

TODAY Copilots Answering questions Summarizing data EMERGING AI Workflows Multi-step investigations Automated playbooks WITH DATAFI Autonomous Roles Problem solving at scale Governed, auditable THE CONTEXTUAL LAYER THAT COMPLEX AGENTS DEPEND ON

Platform

A vertically integrated stack for cybersecurity AI

Cybersecurity is not a single dataset, a single team, or a single decision. It is a connected system. That is why a vertically integrated data and AI stack is essential.

From experimentation to operational impact

Transformative outcomes do not come from a model alone. They come from enabling AI to act on data, securely, responsibly, and at enterprise scale.

Faster Detection & Response

Faster triage, faster containment, while keeping humans in control of high-impact actions. AI speeds the "find and frame" phase so teams focus on "decide and act."

Reduced Alert Noise

Fewer, higher-confidence cases for analyst review. Duplicates clustered, events connected, and the "why this matters" explanation surfaced automatically.

Scaled Expertise

Institutional knowledge codified, not lost. Consistent security outcomes across teams, shifts, and geographies, regardless of staffing levels.

Proactive Defense

AI becomes part of a living defense system that continuously reduces the likelihood and impact of future incidents, not a static dashboard.

Better Stakeholder Alignment

Security translated into language business leaders can act on. Board-level risk summaries, ops reviews, and post-incident debriefs generated automatically.

Measurable ROI

Reduced costs, improved efficiency, and freed experts to focus on higher-value work. Security outcomes that align with operational goals.

Ready to move from experimentation to operational impact?

Datafi helps security teams solve problems by reducing risk faster, scaling expertise further, and improving security decision-making across the enterprise.

Interested in investing in Datafi?

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