Agents do the work. Senior practitioners own the outcome.
The agent model is how Dobler Data Solutions delivers. Proprietary agents carry the data lifecycle (ingestion, modeling, governance and operations) continuously, supervised by senior practitioners who set the architecture and own the result.
Your data work, without the headcount
The old promise was a bench of people on call. Ours is a platform that keeps running, supervised by people who own the result. Agents build pipelines, maintain models, monitor performance and resolve drift; senior practitioners set the architecture and stay accountable.
Continuous execution
Agents run the data lifecycle around the clock: ingestion, transformation, governance and operations. The work does not stop for handoffs, and knowledge does not walk out the door with a person. Your data estate is built and maintained continuously, not project by project.
Practitioner supervised
Agents do the work; senior practitioners own the architecture, enforce the standards and stay accountable for the results. You get the consistency of automation with the judgment of experienced engineers behind it.
When a situation is genuinely new (an unusual source, an ambiguous requirement, a strategic trade-off), a person decides.
Governed by design, self-healing in operation
Every pipeline is built to the same disciplined standard, with governance and lineage enforced automatically: no tribal knowledge, no drift, a full audit trail.
In operation, agents monitor, detect and resolve issues before they reach a ticket queue, so the platform keeps itself healthy instead of waiting to be fixed.
Governance by design, in depthDepartment-level output, without the department
Capability grows without headcount growing with it. We wrote down what that claim means, and where it stops.
Questions about the agent model
What is the agent model?
Instead of a team doing every step by hand, proprietary agents build and run the pipelines, governance and reporting, supervised by senior practitioners, on Microsoft Azure and Microsoft Fabric.
Is it fully automated? Who is accountable?
Agents do the repetitive build-and-run work. Senior practitioners supervise, review and stay accountable for the result. It is automation with human judgment on top, not unattended automation.
How is it different from hiring a data team?
A team means recruiting, salaries and management before the first result. The agent model starts from a proven foundation, so the work begins with the build, not with hiring.
What does it deliver?
Governed data pipelines, a single source of truth, and reports and dashboards, built and maintained on the Microsoft data stack.
See what the agent model would do with your data.
Tell us about your environment, and we will walk you through how we would build and run it.