Challenge
Where work slows down
Service teams solve similar data problems across customers, but each environment has different sources, schemas, retention needs, tenant boundaries, and handoff systems.
Workload
Deliver repeatable security analytics without rebuilding the plumbing for every customer.
Mach5 helps MSSPs and security service providers package reusable infrastructure patterns for search, analytics, enrichment, derived data, and customer-facing reporting.
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
Reusable expertise often turns into scripts, dashboards, rules, and pipelines scattered across tenants. Updates are manual, mapping is slow, and product-quality analytics require custom infrastructure per customer.
Mach5
How teams move faster
Mach5 provides a repeatable layer for source mapping, ingestion, transformations, search, analytics, derived outputs, and customer-facing workloads across environments.
Outcomes
What teams get.
Reuse
Package expertise once
Turn repeated customer needs into maintained workload patterns.
Localize
Adapt per tenant
Map local sources into stable workload shapes without rewriting the whole stack.
Scale
Deliver consistent quality
Ship search, dashboards, derived data, and enrichment paths together.
Common workflows
Work your team can run.
Onboard
Map customer data
Connect customer sources into reusable contracts and serving paths.
Operate
Run repeatable analytics
Use the same search, enrichment, and reporting patterns across environments.
Report
Serve customer outputs
Power customer-facing dashboards, findings, and long-retention analysis.
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.