DataOps designs, builds, and governs the data infrastructure organizations need before they can trust AI at scale, from growth-stage companies to Fortune 500 enterprises.
We bring strategy, engineering, and adoption together so the work doesn't stall at the handoff. Every engagement is led by the strategist who does the work.
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Modern data architecture, data governance, and business intelligence, built so leaders decide from a single trusted source.
AI strategy, AI governance, and production-grade LLM, RAG, and agent systems deployed against real business problems.
Digital transformation and operational optimization that ties the data and AI agenda directly to the P&L.
Adoption, training, and enablement so the capability stays with your team long after the engagement ends.
The policies, controls, and validation that keep AI accurate, compliant, and accountable, including regulated and defense environments.
Production agent systems designed with our framework of 250+ decisions across 26 domains, from orchestration to evaluation.
AI is only as intelligent as the systems of truth and the quality of data that supports it. The DataOps operating principle
We productize what works. Every accelerator below was forged inside a live enterprise engagement, then hardened for reuse.
Our proprietary engine scans 1.17 billion data points in 23 seconds, running 200+ rules across every data quality dimension with cross-domain validation and automatic closure of remediated violations. It exceeds native Snowflake and Databricks capabilities and deploys to any environment.
Our 4-tier governance operating model, productized: enterprise, local, cross-domain, and intra-domain councils, prescribed steward criteria, and 5-step data product certification. Proven at $150M, $1.2B, and $40B scale.
Our 4-tier governance operating model is proven at $150M, $1.2B, and $40B scale. Three engagements, three sets of numbers.
Aerospace & Defense · $40B supplier
A 10-person DataOps team consolidated 7 ERPs into one governed, ERP-agnostic model, deployed our proprietary Data Quality Engine, and trained 900 employees in 2 months. The foundation now powers a supply chain control tower and multi-agent AI architecture.
The proof archive
Three case studies at $150M, $1.2B, and $40B scale, the engagement stats, and the industries we serve, all in one place.
See all results →Every AI system we design consumes only governed, certified data products. Build the foundation first and agents act on truth. Skip it and they act on assumptions.
How we work →
Automation Alley
In-house talent from Fortune 10 companies and ex-Big 4 consulting, on every engagement.
DataOps is an enterprise AI and data consulting firm. We design, build, and govern the data infrastructure organizations need before they can trust AI at scale: data governance, data and AI architecture, analytics, and the change management to make it stick.
Our governance operating model is proven at $150M, $1.2B, and $40B scale. Recent outcomes include a 99.4% reduction in data quality violations for a $40B aerospace supplier, roughly $12M in annualized impact for a $1.2B healthcare franchise, and the governance program behind a construction firm's 5x revenue growth.
The senior strategist who scopes your engagement is the one who delivers it. You get Big 4 caliber thinking without layers of junior staff, which means faster decisions and a shorter path to working outcomes.
Agentic AI architecture is the full set of design decisions that turn a capable model into a dependable system: the pattern the work follows, the data the model can reach, the guardrails around its actions, and the evaluations that gate every change. DataOps resolves these with a framework of 250+ decisions across 26 domains. Explore the framework.
Tell us the decision you're trying to make. We'll show you the fastest responsible path to making it with confidence.
