Challenge
Where work slows down
Security operations products need fast access to fragmented alerts, identity, cloud, endpoint, runtime, and SaaS data. The product experience slows down when every pivot depends on brittle infrastructure glue.
Workload
Security operations experiences need product-grade data infrastructure.
Mach5 powers the data layer behind triage views, investigation timelines, alert enrichment, and customer-facing security operations experiences.
Mach5 workloadsearch, streaming, analytics
Search
low-latency customer-facing queries
Streaming
ingest, transform, enrich, and backfill
Analytics
tenant-aware dashboards and timelines
Derived data
fresh product-serving tables
How it works
A clear path from infrastructure pain to production workload.
Gap
What legacy stacks miss
Dashboards, SIEM searches, ticketing systems, and enrichment jobs often live apart. Product teams end up building one-off pipelines and query paths for each new experience.
Mach5
How teams move faster
Mach5 gives product teams one infrastructure layer for search, analytics, streaming enrichment, derived context, and product-serving query paths.
Outcomes
What teams get.
Speed
Faster product pivots
Serve related entities, timelines, and context from a product-ready data layer.
Quality
Consistent customer experiences
Use repeatable data paths instead of custom glue for every workflow.
Scale
Handle growing telemetry
Keep operations experiences fast as event volume and retention needs grow.
Common workflows
Work your team can run.
Alert
Alert context pages
Join alert data with host, identity, cloud, SaaS, and historical context.
Timeline
Investigation timelines
Serve ordered event views across multiple data sources and derived outputs.
Enrichment
Customer-facing findings
Transform raw events into context-rich findings for product users.
Related workloads
Explore the related security data workloads.
Start with one workload.
Bring Mach5 the infrastructure pain your team wishes it did not own.
Start with one search, analytics, streaming, backfill, or derived-data workload and prove value before expanding.