One governed outcome chain
Connect commercial context to order, engineering, procurement, production and shipment evidence.
Cross-system industrial intelligence
Turn ERP, CRM, CPQ and engineering data into one outcome-led operational view.
PulseIQ sits above approved read-only enterprise systems and connects the commercial and operational evidence needed to understand customer commitments, execution risk, recovery priorities and later business outcomes.
Approved read-only accessTarget activation: 1–2 days after genuine prerequisites are readyCustomer leadership retains go-live and operational decision authority
The management problem
The business outcome crosses systems even when each application is working as designed.
CRM may hold the opportunity and customer context, CPQ the approved commercial output, ERP the order and material picture, and SharePoint or engineering systems the handoff evidence. PulseIQ discovers and maps the approved structures underneath so business users do not have to become integration specialists.
Less customer preparation
Avoid table-name workshops, source-to-target spreadsheets and separate KPI-design projects for business users.
Faster activation
Use automated metadata discovery, mapping and best-practice KPI packs where the approved source interface supports it.
Controlled production truth
Keep read-only boundaries, tenant isolation, customer approval and verification gates intact as the intelligence layer goes live.
Works above the systems you already run
Connect the operational chain instead of building another isolated dashboard.
Salesforce / CRMIFS / ERPSAP / Oracle reportingApproved CPQ outputsSharePoint metadataPostgreSQL / SQL ServerSecure Read Relay
Minimal customer preparation
Business users validate outcomes. PulseIQ owns the technical work.
Customer teams approve the read-only scope, confirm the priority business outcomes, validate the proposed baseline and representative outputs, and retain final go-live authority.
PulseIQ handles
discover approved source objects, tables, views and metadata
identify fields, keys, aliases and cross-system relationships
map data into the industrial canonical model
apply best-practice operational KPIs and evidence rules
generate baseline, risk, recovery and reconciliation outputs
run technical verification before customer-controlled go-live
Explore related operational intelligence problems
Start with one measurable outcome