PRICING AND SUBSCRIPTION MODEL
Insight Ready Platform™ Pricing
A transparent, standardized pricing model aligned to organizational maturity — two tiers, two phases, and no hidden costs.
The Insight Ready Platform™ pricing model is designed for regulated organizations that require a governed, AI-ready analytics environment with consistent KPI definitions, semantic alignment, and continuous platform evolution. Pricing is simple, predictable, and structured around a two-phase modernization path that reduces commitment risk and ensures every organization starts on a stable, governed foundation.
Platform management, governance, BI, and AI included. One monthly number. Nothing hidden.
Phase 2 IDPaaS subscription pricing is all-inclusive — platform management, pipeline operations, semantic layer management, governance operations, BI development, AI capabilities, and continuous platform enhancements are all covered by a single monthly subscription. The Azure environment runs inside your tenant under your subscription. Organizations eliminate the unpredictable mix of staffing costs, project budgets, and platform management overhead that characterize DIY analytics builds.
PHASE 1
Governed Foundation
Fixed-scope implementation inside your Azure environment — production-ready in 6 to 12 weeks
Phase 1 establishes the governed data foundation required for a clean, confident transition to Phase 2. Every IDPaaS subscription begins with a Phase 1 engagement — it ensures the Foundation Environment, governed pipelines, semantic layer, and data quality monitoring are in place before the fully managed subscription starts. A Phase 1 implementation credit is applied toward the first months of your Phase 2 subscription.
PROFESSIONAL FOUNDATION
$135,000
One-time implementation fee
4 TO 6 WEEKS
A fully production-ready governed foundation with executive dashboards and an AI-ready semantic layer — everything needed for a clean, confident transition to Professional IDPaaS.
✓ Foundation Environment established — conformed dimensions, reconciled fact tables, semantic alignment rules, lineage capture, and AI-ready data structures
✓ Governed ingestion for 3 to 5 priority data sources
✓ Business-aligned semantic layer with initial KPI registry
✓ Executive dashboard built in Power BI on governed, consistent KPIs
✓ Data quality scorecards and automated validation rules
✓ 4 to 6 week delivery with weekly check-ins
✓ 90 days of post-deployment support and enhancements
✓ Founder-led executive briefing at delivery
Ideal for organizations establishing a governed analytics foundation before transitioning to Professional IDPaaS.
A $27,000 implementation credit is applied toward your Professional IDPaaS subscription at transition
ENTERPRISE FOUNDATION
$255,000
One-time implementation fee
6 TO 10 WEEKS
A fully governed, multi-domain foundation for complex regulated environments — built to transition seamlessly into Enterprise IDPaaS at scale.
✓ Foundation Environment established across multiple domains — conformed dimensions, reconciled fact tables, semantic alignment rules, lineage capture, and AI-ready data structures
✓ 8 to 12 data sources with complex transformations and cross-domain dependencies
✓ Department-specific dashboards and cross-functional KPI alignment
✓ Advanced compliance, audit, and governance framework
✓ Cross-functional semantic layer with governance workflows
✓ 6 to 10 week delivery with dedicated project management
✓ 180 days of post-deployment support
✓ Founder-led executive briefing at delivery
Ideal for complex regulated environments requiring enterprise-scale foundations before transitioning to Enterprise IDPaaS.
A $45,000 implementation credit is applied toward your Enterprise IDPaaS subscription at transition
PHASE 2
Insight Ready Platform™ (IDPaaS)
Fully managed, all-inclusive subscription — everything included, nothing hidden
Phase 2 is the fully managed IDPaaS subscription. On Point BI operates the platform inside your Azure tenant through the governance layer — managing pipelines, semantic models, data quality, AI capabilities, governance operations, and continuous platform enhancements. Your team focuses on insights, decisions, and AI adoption. Not infrastructure.
PROFESSIONAL
Insight Ready Platform™
$80,000/mo
Annual contract · Deployed and governed inside your Azure tenant
MONTHLY VALUE BREAKDOWN
Azure Architecture & Optimization$23,000
Platform and Management$30,000
Analytics and BI$17,000
AI and Enhancements$10,000
✓ Bronze → Silver → Gold pipeline architecture
✓ Up to 10 governed data domains (50TB total storage, 5TB monthly ingestion)
✓ 7 to 9 executive-grade Power BI dashboards
✓ Business-aligned KPI catalog with governed metric definitions
✓ Automated anomaly detection and forecasting (classical ML)
✓ Natural-language query powered by Azure OpenAI — runs entirely inside your tenant
✓ Automated data quality enforcement and continuous monitoring
✓ Azure cost optimization, reserved instance management, and security hardening
✓ Private endpoint configuration, RBAC governance, and tenant isolation architecture
✓ Audit-ready data lineage for regulated industry compliance
✓ Daily platform monitoring and 40 hours of monthly enhancements
✓ Bi‑weekly platform updates and quarterly strategic reviews
Predictable Scaling Rates
• Additional governed data domain: $5,000 per month
• Additional executive dashboard: $2,500 each
• Storage overage: $480 per TB per month
• AI Workload Overage — $1,500 per 1,000 AI‑orchestrated queries
• Additional governed forecasting pipeline: $9,000 to $12,000 per month
Built for regulated industries where data governance isn’t optional — and neither is reliability. Replaces $600K+ in annual data team costs.
ENTERPRISE
Insight Ready Platform™
Starting at
$135,000/mo
Annual contract · Custom-scoped to your environment · Deployed and governed inside your Azure tenant
MONTHLY VALUE BREAKDOWN
Azure Architecture & OptimizationDedicated architecture team
Platform and ManagementDedicated engineering allocation
Analytics and BIEnterprise-scale dashboard suite
AI and EnhancementsDedicated AI/ML resources
✓ Semantic Drift Intelligence™ Ready — governed KPI definitions, semantic alignment rules, and lineage capture pre-configured for SDI activation
✓ Bronze → Silver → Gold pipeline architecture
✓ Enterprise-scale data domains with 100TB+ storage capacity
✓ Enterprise-scale Power BI dashboard suite across all business units
✓ Business-aligned KPI catalog with full governance automation
✓ Automated anomaly detection and forecasting (classical ML)
✓ Natural-language query powered by Azure OpenAI — runs entirely inside your tenant
✓ Automated data quality enforcement and continuous monitoring
✓ Audit-ready data lineage for regulated industry compliance
✓ Azure cost optimization, reserved instance management, and security hardening
✓ Private endpoint configuration, RBAC governance, and tenant isolation architecture
✓ Daily monitoring and dedicated enhancement team
✓ Bi‑weekly platform updates and quarterly strategic reviews
Custom Scaling
• All additional capabilities scoped and priced based on organizational requirements
• Multi-year commitments available with adjusted rate structures
• Global rollouts and multi-site deployments supported
• Enhanced SLA options available
• Semantic Drift Intelligence™ monitoring available as an add-on — contact us for pricing
Purpose-built for healthcare, life sciences, and financial services organizations where governance, auditability, and semantic consistency aren’t optional — they’re existential.
ADD-ONS
Optional Capabilities to Extend Your Platform
Each add-on is a purposeful expansion of a specific platform capability — governed pipelines, semantic coverage, or AI depth. Add-ons are scoped, governed, and delivered with the same quality and lineage standards as the base platform.
Complete Stack Option
IDPaaS + Semantic Drift Intelligence™. Organizations requiring continuous semantic monitoring across all systems — including systems outside the IDPaaS managed boundary — can add SDI as a companion subscription. Contact us for combined pricing.
Additional Data Domains
Contact for pricing
Expansion of governed pipelines and semantic models to new operational, clinical, financial, or third-party data domains. Each domain expansion includes source connection, Bronze to Silver to Gold pipeline build, semantic layer integration, KPI alignment, data quality rules, and lineage capture.
Additional KPI Families
$12,000 to $18,000 per KPI family
Expansion of the KPI registry to new metric families with full semantic alignment. Each KPI family expansion includes semantic layer changes, cross-domain logic validation, governance workflow updates, version-controlled definition documentation, and Control Panel integration.
Advanced AI Insights — Additional Forecasting Models
$9,000 to $12,000 per model per month
Additional forecasting models beyond what is included in the base subscription tier. Each model is built, trained, validated, and deployed entirely inside the client’s Azure tenant — with full lineage, audit-ready documentation, and MLOps scaffolding for model monitoring and retraining.
THREE-YEAR TOTAL COST OF OWNERSHIP
Build Versus Managed Platform — The Full Economic Picture
Traditional build-versus-buy frameworks dramatically underestimate the true cost of modern analytics in regulated environments. Beyond infrastructure and staffing, organizations absorb hidden costs through delayed time-to-value, operational drag, technical debt accumulation, compliance remediation, and the inability to deploy AI at scale. This analysis quantifies the full economic and operational impact across a three-year horizon using current market rates and real-world delivery patterns for regulated industries.
IDPaaS reduces three-year TCO by an estimated 28% to 72% depending on tier and organizational context.
Organizations shifting from capital-intensive internal builds to a fixed-fee managed platform gain financial predictability, accelerated ROI, and immediate AI readiness — without the 18 to 24 month lag and multi-million-dollar staffing burden typical of DIY approaches in regulated industries.
Methodology note: DIY cost estimates are derived from published compensation benchmarks for enterprise data roles, average Azure consumption patterns for regulated‑industry workloads, and observed delivery timelines from industry research. Actual savings will vary based on organization size, existing infrastructure, and geographic market.
IDPaaS is a managed platform subscription — not a consulting engagement. The comparison below is not build vs. buy. It is internal team and infrastructure vs. a fully operated platform.
Comparative TCO Analysis
| Dimension | In-House Build (DIY) | Insight Ready Platform™ (IDPaaS) |
|---|---|---|
| Time to Value | 18 to 24 months to initial production | 6 to 8 weeks to full platform deployment |
| Team Composition | Data Engineer ($170K), Analytics Engineer ($160K), BI Developer ($140K), AI/ML Specialist ($200K), DevOps Engineer ($150K) — plus 6 to 12 months recruitment overhead | Zero hiring requirement — fully managed platform team |
| Operational Efficiency | 40% to 60% of team capacity consumed by maintenance, troubleshooting, and technical debt management | 100% of internal capacity dedicated to value creation and analytics delivery |
| AI Readiness | 18 to 24 months to establish requisite data pipelines, governance, and MLOps infrastructure | Production-ready AI and ML capabilities available at deployment |
| Risk Profile | High exposure to talent attrition, knowledge silos, security vulnerabilities, and budget overruns | Risk transferred to provider — guaranteed SLAs for uptime, security, and compliance |
| Three-Year Financial Outlay | $4.31M to $6.75M+ (Implementation: $250K / Annual Cloud: $250K to $600K / Annual Salaries: $820K+ / AI and ML Projects: $200K to $400K / Unplanned Costs: $650K to $1.2M) | $2.88M to $4.86M fixed — covers infrastructure, management, analytics, BI, and AI capabilities |
| Financial Predictability | Volatile CapEx combined with variable staffing costs | Fixed OpEx model with comprehensive cost containment |
| Strategic Outcome | Extended implementation timeline with elevated operational fragility | Accelerated ROI with enterprise-grade stability and scalability |
Three-Year Financial Comparison by Tier
Professional Tier
$80,000 per month — $2.88M over three years
Estimated DIY Cost:$4.31M to $6.75M
IDPaaS Cost:$2.88M
Estimated Savings:$1.43M to $3.87M
TCO Reduction:33% to 55%
Compared to hiring and maintaining a full in-house data team, BI function, and mid-scale Azure cloud environment with equivalent governed analytics capability.
Enterprise Tier
$135,000+ per month — $4.86M+ over three years
Estimated DIY Cost:$6.75M+
IDPaaS Cost:$4.86M+
Estimated Savings:$1.89M+
TCO Reduction:28% to 40%
Compared to a complex regulated multi-department build with dedicated AI and ML resources, enterprise-scale Azure infrastructure, and full governance automation.
Strategic Insights
Economic Efficiency
IDPaaS converts unpredictable CapEx and staffing volatility into a fixed OpEx model. Organizations eliminate $750K to $1.8M in cloud infrastructure costs, $2.46M to $2.85M in staffing costs, $600K to $1.2M in AI and ML project costs, and $500K to $900K in unplanned rework and technical debt. The result is multi-million-dollar savings and dramatically improved cost predictability over a three-year horizon.
Risk Mitigation and Operational Transfer
The IDPaaS subscription transfers platform performance, security and compliance, monitoring and DevOps, MLOps and AI operations, and break-fix and technical debt management to On Point BI. This removes the organization’s exposure to talent shortages, attrition, and operational fragility — risks that are structurally higher in regulated environments where data engineering talent is scarce and compliance requirements are non-negotiable.
Velocity and Competitive Advantage
With IDPaaS, organizations reach production in 6 to 8 weeks, not 18 to 24 months. This acceleration unlocks faster decision cycles, earlier ROI, rapid AI adoption on a governed foundation, and competitive differentiation in markets where data-driven operations are increasingly a baseline expectation. Time-to-value becomes a strategic asset instead of a sunk cost.
PRICING FRAMEWORK
Transparent Pricing — No Hidden Costs
The pricing framework is designed to eliminate the ambiguity that makes analytics platform procurement difficult in regulated organizations. Every cost component is documented, every commitment is explicit, and every adjustment requires advance notice.
Phase 1 Implementation
• Fixed-scope delivery inside the client’s Azure environment
• Azure infrastructure consumption billed directly to the client during implementation
• Implementation credit applied toward Phase 2 IDPaaS subscription — Professional Foundation credit toward Professional IDPaaS, Enterprise Foundation credit toward Enterprise IDPaaS
• No ongoing commitment required from Phase 1 alone
Phase 2 IDPaaS Subscription
• ll-inclusive OpEx model — platform management, pipeline operations, governance, BI, AI, and continuous enhancements in one monthly number — deployed inside your Azure tenant
• Annual commitment required
• Scaling rates published and fixed — no surprise overages
• Rate adjustments require 60-day advance notice
• Custom pricing available for multi-year commitments, global rollouts, and enhanced SLA requirements
• All deployments use identical enterprise-grade architecture — standardization eliminates variability and ensures consistent governance across all client environments
The fundamental choice is not between building and buying.
It is between delayed value creation with elevated risk versus immediate capability deployment with predictable economics. IDPaaS transforms analytics from a capital-intensive, multi-year initiative into an operationalized, value-generating capability available in weeks.
EXPLORE FURTHER
Understand What You Are Buying Before You Commit
Pricing is only one part of the evaluation. The three pages below give you the full picture — what the platform is, how it works technically, and where your organization fits on the maturity model.
Schedule a Pricing Consultation
Talk to our team about which tier aligns with your organization’s maturity level, infrastructure requirements, and budget.