Know where your data platform
actually stands on AI readiness.
A 2-minute self-assessment that benchmarks your data platform architecture, MLOps maturity, and developer experience against peer data infrastructure companies. Instant score. Actionable report. No sales call required to get it.
Five dimensions.
One composite score.
The AI Readiness Quotient evaluates the building blocks every data infrastructure company needs to ship production-grade AI — from lakehouse architecture to organizational alignment.
Lakehouse maturity, metadata management, and data discovery across your platform.
Orchestration stack maturity, streaming infrastructure, and data contract adoption.
Production ML maturity, feature store adoption, and model governance.
Self-service tooling, platform APIs, and engineer onboarding velocity.
Platform team structure, investment thesis, and infrastructure-as-differentiator strategy.
Three steps.
Under two minutes.
Built for CTOs and VP Platform who know their stack. Every question is answerable in under 10 seconds.
One question at a time. Multiple choice. Each option describes a real state of infrastructure we see across data platform companies.
Composite score from 0–100 with tier label and dimension-level breakdown benchmarked against peer companies.
3 prioritized recommendations with quantified expected impact. Something you can bring to your leadership team.
The gap between “we have a platform”
and “teams ship on it daily” is measurable.
Data infrastructure companies are built to enable others. But the companies pulling ahead aren’t just building tools — they’re building the internal platforms that let their own teams move at the speed of their ambition.
Organizations with mature MLOps deploy models 5x faster than those running ad hoc notebooks. That velocity gap compounds every quarter your competitors ship and you do not.
Developer experience is the most underinvested dimension in our benchmark dataset. Poor DX slows every team that builds on your platform and is the top driver of shadow infrastructure.
Based on our benchmark dataset. Most organizations are in the "Building" tier — strong in one or two dimensions, with critical gaps elsewhere. Knowing which gaps matter most is the first step.
Ten years building production data platforms at scale.
- Deep data infrastructure expertise: lakehouse architecture, real-time pipelines, and production MLOps at scale.
- We build the platforms that ML teams ship on — not slide decks about platforms.
- Our benchmark data comes from real engagements with 100+ data infra companies, not surveys.
- Outcome-aligned engagement model: our revenue is tied to the results we deliver, not the hours we bill.
FAQ
What is the AIRQ Data Infrastructure & MLOps Assessment?
AIRQ (AI Readiness Quotient) Data Infra Edition is a 2-minute, 10-question self-assessment for CTOs, VP Platform, and Heads of ML Engineering at data infrastructure companies. It scores your organization across five dimensions — Data Platform Architecture, Pipeline & Orchestration, MLOps & Model Serving, Developer Experience, and Org & Go-to-Market — producing a composite score from 0–100 benchmarked against 100+ peer companies.
Who is this assessment designed for?
This assessment is designed for CTOs, VP of Platform Engineering, and Heads of ML Engineering at companies that build, operate, or sell data infrastructure and MLOps tooling. It helps leaders objectively benchmark their internal platform maturity against peers and identify the highest-impact investments.
How long does the assessment take?
The assessment takes approximately 2 minutes to complete. There are 10 multiple-choice questions, each answerable in under 10 seconds. Your score and PDF report are generated immediately upon completion.
Is the assessment really free?
Yes. The assessment, your composite score, peer benchmarks, and the full PDF report with prioritized recommendations are all free. No sales call is required to receive your report.
How are scores calculated?
Scores are calculated across five weighted dimensions: Data Platform Architecture (25%), Pipeline & Orchestration (25%), MLOps & Model Serving (20%), Developer Experience (20%), and Org & Go-to-Market (10%). Your composite score is normalized to a 0–100 scale and compared against benchmark data from 100+ data infrastructure companies.
What do I get after completing the assessment?
After completing the assessment you receive an instant composite score (0–100), a tier classification (Foundational through Leading), dimension-level scores with peer comparisons, and a downloadable PDF report with 3 prioritized, impact-quantified recommendations specific to your lowest-scoring dimensions.
What is a good score for a data infra company?
The average score across data infrastructure companies in our benchmark dataset is 40, placing most in the "Building" tier. Scores above 61 are considered "Advanced" and above 81 are "Leading." Most organizations have strong performance in 1–2 dimensions and significant gaps in others — particularly in developer experience and organizational maturity.
Where can I download the State of Data Infrastructure & MLOps 2026 report?
The State of Data Infrastructure & MLOps 2026 (Q1 2026) is a free white paper published by Blue Orange Digital. It benchmarks platform architecture maturity, MLOps adoption, developer experience investment, and organizational readiness across 100+ data infrastructure companies. You can download it for free at https://blueorange.digital/pages/data-infra/ — no form or sales call required.
State of Data Infrastructure & MLOps 2026
Our Q1 2026 benchmark report analyzes platform architecture maturity, MLOps adoption patterns, developer experience investment, and organizational readiness across 100+ data infrastructure companies. Includes dimension-level benchmarks, tier distributions, and the top initiatives platform leaders are prioritizing this year.
- Average AIRQ scores by company stage and platform category
- The 3 dimensions where data infra companies are most underinvested
- What separates “Leading” platforms from the middle tier
- MLOps adoption rates and production deployment benchmarks
Benchmark your platform
in 2 minutes.
Walk away with a score, a peer comparison, and 3 prioritized recommendations. The full PDF report is yours immediately — no follow-up call required.
Get Your AI Readiness Score →