Enterprise Pricing
ZHIMINDS pricing is structured for enterprise rollout. Start with a scoped pilot, then scale by data sources, tenants, workloads, and production service levels.
Pilot
4-8 weeks
Focused scope for source connection, dashboard, and one AI workflow.
Scale
Usage-based
Data volume, tenant count, AI calls, and integration complexity drive the quote.
Enterprise
SLA + Private
Dedicated deployment options for regulated or mission-critical environments.
Packages
The packages below are commercial starting points. Final pricing depends on tenant model, ingestion scope, AI workload, and deployment requirements.
Starter
For teams validating a business case with limited data sources, governed dashboards, and one decision intelligence workflow.
Growth
For companies expanding from a pilot to multiple departments, governed metrics, forecasting, and reusable data services.
Enterprise
For mission-critical workloads requiring multi-tenant governance, private deployment options, security controls, and production support.
Infrastructure
For customers needing managed full-node runtime, tenant access, indexed chain data, telemetry, and quota management.
Operating Model
We avoid one-size-fits-all pricing because enterprise data platforms vary heavily by integration scope and operating requirements.
Scope
We identify systems, data freshness, source ownership, metric scope, and users.
Workload
We size ingestion, storage retention, BI concurrency, AI calls, and model-routing needs.
Delivery
We align on milestones, deployment model, monitoring, security controls, and support expectations.
Pricing Dimensions
These dimensions make pricing transparent before a formal proposal is created.
Source type, CDC requirements, streaming latency, transformation logic, and data-quality controls.
Number of tenants, role hierarchy, data isolation, audit requirements, and user access patterns.
NL2SQL usage, report generation frequency, long-context analysis, RAG retrieval, and model routing.
Included Services
A production rollout includes more than software access. It includes architecture, governance, integration, and operational readiness.
Target architecture, AWS service mapping, data flow design, and security control planning.
Pipeline setup, metric modeling, dashboard/report configuration, AI workflow setup, and launch support.
Share your data sources, priority scenarios, expected users, and deployment constraints. We will respond with a practical rollout and pricing structure.
