Cybersecurity Workflows on BigML, Powered by AI
Cybersecurity teams use DeskFerry to turn BigML into an automation engine. Connect in minutes, save hours every day.
84 alerts triaged · 3 escalated. Top-priority case:
Customer
“Anomalous login activity flagged for 3 user accounts from a new ASN — burst of 47 attempts in 90 seconds, all from same IP block.”
Agent draft · in your tone
Auto-classified as credential-stuffing pattern (matches signature CS-441 from Jan incident). All three accounts forced to re-authenticate, IP block added to deny-list, MFA challenge logs collected for review. Ticket P1 opened in Linear; security on-call paged.
How does BigML work for cybersecurity teams?
BigML works for cybersecurity teams as the engine behind a DeskFerry agent built around the workflows that actually consume your week.
- 01
Trigger fires
The agent reads context from BigML and the other systems your cybersecurity operation depends on, runs the routine work in the background, and surfaces only the cases that need a human decision.
- 02
Triage every alert in our SIEM with @BigML
Automate repetitive tasks and free up your cybersecurity team to focus on high-value strategic work.
- 03
Classify threat level
Teams typically see lower faster anomaly identification once the agent is in production.
- 04
Attach context from prior incidents
Setup is no-code, every action is auditable, and the agent is scoped to the rules your cybersecurity team defines — not a generic template applied to your business.
- 05
You approve
Anything under your confidence bar waits for a human.
How you tell it what to do
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Triage every alert in our SIEM with @BigML
- 2Classify threat level
- 3Attach context from prior incidents
- 4Create the right ticket in @Linear
How it connects
Connect BigML. The agent does the rest.
Claude and ChatGPT are already running on our side. You connect BigML with one click, and cybersecurity runs inside it.
Claude and ChatGPT run on our keys. Nothing for you to configure.
- BigMLConnect
- LinearConnect
Runs on your data, in your apps.
Nothing to deploy. Nothing to maintain.
Actions
What BigML + DeskFerry can do
Real BigML actions your AI agent can perform automatically — no manual work required.
Create issues from alerts
Automatically open issues in BigML when monitoring systems detect errors, outages, or performance regressions.
Manage pull requests
Post review reminders, enforce labeling conventions, and auto-merge approved pull requests in BigML.
Trigger CI/CD pipelines
Kick off build and deployment pipelines in BigML when code is pushed or a pull request is merged.
Track release milestones
Update milestone progress in BigML as issues are closed and pull requests are merged toward a release.
Sync project boards
Keep issue status and priority in BigML aligned with your project management tool in real-time.
Generate changelogs
Compile merged pull requests and closed issues from BigML into formatted release notes automatically.
Assign reviewers automatically
Route new pull requests in BigML to the appropriate code reviewers based on file ownership and team rules.
Monitor repository activity
Watch for commits, branch creations, and tag events in BigML and notify the team of significant changes.
Auto-classified as credential-stuffing pattern (matches signature CS-441 from Jan incident). All three accounts forced to re-authenticate, IP block added to deny-list, MFA challenge logs collected for review. Ticket P1 opened in Linear; security on-call paged.
Customer reports a duplicate charge; refund queued, awaiting confirmation.
Customer asking what's included on the Growth plan vs. Pro.
Human in the loop
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Governance
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Production environment9:14 AM
Customer marked the resolution as helpful.
- Agent9:12 AM
Sent reply on ticket INC-2841.
Reason: Confidence above auto-send threshold; voice match passed; SLA at-risk.
- Agent9:11 AM
Drafted reply in your team's voice.
- Agent9:10 AM
Pulled customer plan, prior tickets, and account context.
- Agent9:09 AM
Triaged INC-2841 as the matching topic.
How it works
Get started in three steps
Step 01
Connect BigML
Authorize BigML and DeskFerry hooks into your issues, repos, and deployment pipelines.
Step 02
Configure Dev Workflows
Define triggers for BigML events — new issues, PR merges, build failures — and the AI actions to take. For cybersecurity teams, this typically means routing workflows from tools like Splunk alongside BigML.
Step 03
Ship Faster with Less Toil
AI automates the tedious parts of your BigML workflow. Track issues triaged, alerts handled, and developer time saved.
Start automating Cybersecurity for BigML
7-day free trial. Works with the tools you already use.
FAQ
Frequently asked questions
How does BigML integrate with DeskFerry for cybersecurity businesses?
DeskFerry connects directly to BigML to automate workflows specific to cybersecurity. Data flows in real-time between BigML and the AI agent, tasks trigger automatically based on cybersecurity events, and your team saves hours of manual processing every week.
Is the BigML integration suitable for small cybersecurity businesses?
Yes. DeskFerry scales from solo operators to enterprise cybersecurity teams. Start with one BigML-powered automation for your cybersecurity workflows and expand as you see results — pricing and capacity grow with your cybersecurity business needs.
Can I connect BigML with other tools in my cybersecurity tech stack?
Yes. DeskFerry supports 1,500+ integrations, so your cybersecurity workflows can span BigML and every other tool in your stack. A single automation can pull cybersecurity data from BigML, process it, and push results to CRMs, databases, or communication platforms.
Can I test the BigML integration with my cybersecurity data before going live?
Yes. You can run cybersecurity workflows in test mode using sample BigML data before activating on live records. This lets you verify every automation rule works correctly with your cybersecurity processes before it touches real BigML data.
How does BigML with DeskFerry help Cybersecurity teams handle alert fatigue burying real signals in analyst queues?
DeskFerry uses BigML as a structured surface for the operational work behind alert fatigue burying real signals in analyst queues. Instead of your cybersecurity team coordinating manually, the agent listens for the right BigML events, takes the next action, and escalates only when judgment is required — turning a recurring drain into a measurable workflow.
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