OpsWerks runs the data infrastructure behind AI, so your teams can focus on models, products, and insights.
OpsWerks’ 2026 survey found that 22% of practitioners would direct more capacity to AI/ML infrastructure and tooling—even as operational demands strain their teams.
AI depends on reliable data pipelines, orchestration, storage, and compute. When these systems require constant attention, data and ML teams lose time for models and products.
Industry research reveals an operations gap: 56% of organizations have deployed or plan to deploy agentic AI within 12 months, yet 46% of practitioners lack confidence in monitoring AI/ML reliability in production. Reliable data, orchestration, and infrastructure are more critical than ever.
Your data and ML teams own models, architecture, governance, tooling, and roadmaps. OpsWerks runs the agreed operational layer with purpose-built automation, keeping the platform available, observable, maintained, and production-ready.
OpsWerks maps platform dependencies through discovery, shadowing, documentation, and readiness checks before taking operational ownership.
OpsWerks manages enterprise data platform operations across streaming, orchestration, storage, observability, and production pipelines.
“Upgrading 21 Airflow clusters in 2 days while keeping both teams in sync is genuinely not an easy thing to pull off.”
“They were incredibly good at writing their own documentation and runbooks.”
“Give them a problem statement... they'll go figure it out.”
Our managed services model: predictable pricing, aligned incentives, and a strict focus on operational outcomes, not headcount.
Full accountability for results, not just tasks. No pile-up of tech debt or stale tickets; issues get resolved, not recycled.
Self-managing teams that don't drain your engineering bandwidth. Eliminate the management overhead and micro-coordination that comes with contractors.
No contract churn. No retraining every 6 months. A stable, embedded team with consistent output and pricing.
Shift recurring pipeline monitoring, data service maintenance, upgrades, observability, and environment support to a dedicated team, while your engineers retain control of architecture, governance, and the roadmap.