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AI-ready data foundations · Production DataOps & pipeline engineering · Fractional data leadership · CI/CD for data pipelines · Schema drift, caught before it ships · RAG-ready semantic layers · Infrastructure as code · North America, remote-first

Questions

Common questions

Straight answers on how Aeolus works, who it is for, and where to start.

They rarely fail on the model. They fail on the data pipeline underneath it — inconsistent schemas, missing metadata, and breakages that corrupt results without any alert. Industry research puts weekly data-pipeline failure rates at 30–40%, and roughly 46% of AI models never reach production, most often for data-readiness reasons rather than modeling ones.

It is a short, fixed-fee diagnostic of your data stack. We map your pipelines, schemas, metadata, and warehouse, then hand back a technical report and a prioritized remediation roadmap. It is the low-risk first step in every Aeolus engagement, so you can see the engineering quality before committing to a larger build.

Aeolus does not publish fixed prices because scope depends on your stack, data volume, and goals. Every engagement starts with a fixed-fee data & AI-readiness audit, so you get a concrete, bounded first step before any larger commitment. Book the audit and we will scope pricing against your actual environment.

Fractional data leadership gives you senior data engineering direction a few days a week, covering pipeline health, platform decisions, and KPI standardization, without the loaded salary or a six-month executive search. It fits companies that have real data complexity but cannot yet justify a permanent senior data hire.

Aeolus builds on the modern data stack: dbt for transformation and testing, Snowflake and Databricks for warehousing and lakehouse, Apache Airflow for orchestration, and Terraform for infrastructure-as-code. Engagements apply Big Tech engineering discipline (CI/CD, automated testing, and version control) at startup and scale-up budgets.

Seed to Series B startups and scale-ups across North America that are scaling faster than their data infrastructure, often shipping AI or RAG features on fragile pipelines, or running on spreadsheets and scripts with no senior data hire. If your reporting or AI outputs cannot be fully trusted yet, that is the profile.

You work directly with a founder on every engagement. No account managers, no junior delivery bench, no handoffs. Aeolus brings Big Tech engineering standards like automated testing, infrastructure-as-code, and versioned pipelines, usually reserved for large data teams, delivered at the speed and price a startup can absorb.

Aeolus Data Solutions has a public company address at 650 California St, San Francisco, CA 94108. It is also incorporated in British Columbia, Canada, and works remote-first with clients across North America.