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AI adoption: Cybersecurity

AI adoption in Cybersecurity

Security teams face more alerts than they can investigate. AI helps analysts triage and respond faster, and has to be secured like any other system.

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Use cases

Where AI pays off first

  • 01

    Alert triage

    Summarising and prioritising alerts with the evidence attached.

  • 02

    Investigation assistants

    Natural-language queries over logs and past incidents.

  • 03

    Detection

    Models that spot unusual behaviour across users, devices and networks.

The path

The path for Cybersecurity

Four stages, each ending with a decision. The first line of every stage is specific to your industry.

Step 1: Assess

Find where AI is worth it

  • Measure alert volume, time to triage and the share of false positives
  • List the work that is repetitive, slow or stuck in documents
  • Score each use case by value, feasibility and risk

Use case scoring

12 assessed
Use caseValueFeasibleRiskAlert triageInvestigation assistantsDetection

Owner: SOC manager

Measure: minutes per alert

Step 2: Pilot

Prove one use case

  • Add AI summaries to one alert type and compare analyst handling time
  • Build one narrow use case with real users and real data
  • Write evaluation tests before the first prompt

Pilot: alert triage

Week 4

Analyst decides every alert

Analyst time per phishing alert

Baseline22 min
Pilot6 min

Decision: continue

Reviewed with the owner

Step 3: Integrate

Put it where work happens

  • Embed in the analyst console with strict controls on data and actions
  • Connect to the systems people already use, not a separate tool
  • Add access control, logging and data protection

Connected systems

  • SIEMAlerts
  • EDREndpoint data
  • TicketingCases
Access controlLoggingData protectionUsage policy
Step 4: Scale

Make it routine

  • Automate response for well-understood incidents, with approval steps for the rest
  • Reuse the same platform, patterns and guardrails for the next use case
  • Move from assistants to agents where the evidence supports it

AI use cases

This quarter
  • Alert triageLive
  • Investigation assistantsLive
  • DetectionPilot

3.5x alerts

Handled per analyst

Cybersecurity

Product engineering for security companies.

Security products process huge volumes of data and are held to a higher standard than the software they protect. We build the consoles, pipelines and integrations behind them.

What we buildWhat we build

Find your first AI use case

Tell us about your business and where the time goes. We will come back with the use cases we would assess first and how we would test them.

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Your project plan

Ready five days after the first call

Share plan

Approach

Fixed scope
  • Start with sign-up and onboarding, the riskiest flow
  • Ship to a pilot group every week from week three
  • Add the invoice reading agent once data is flowing
First release
Week 4
Demos
Weekly
Code
Yours

Team

5 people
  • PLProduct lead
  • SESenior engineer
  • SESenior engineer
  • PDProduct designer
  • AIAI engineer

Timeline

10 weeks
Discovery
Design
Build
Launch