AI operations transformation
AI that tells your staff what to do next
We design AI prompt frameworks that turn your operational and quality data into prioritized, role-specific tasks. Your staff move from reading dashboards to doing the next step, without hiring data scientists or learning new software.
The problem
Your teams spend hours working out why a number moved before anyone acts on it. Quality analysts pull the same spreadsheet every Monday. You can see what AI could do, but a chatbot is not an operating model.
What we do
We build an AI operations analyst: a framework of prompts on top of your data that looks for the likely cause behind a metric and writes SMART tasks for each role, from front desk to operations leader. The tasks land in the tools your team already opens every day.
Ben Miller architected and validated this kind of framework on an athenahealth-based analytics warehouse at a multi-clinic primary care group, scoped for an operations team of about 100, and deployed LLM tooling for code generation and contract review.
What you get
Deliverables you own
AI operations analyst framework
Prompt architecture built for your workflows, metrics and staff roles. Your team gets prioritized tasks, not raw data.
Daily task delivery
Analysis that reaches staff each morning inside the reporting tools they already use, such as Tableau, with no manual step.
LLM productivity tooling
Language-model help for high-friction work: writing SQL, reviewing contracts, drafting data dictionaries.
Related reading
Questions we answer in depth
FAQ
Common questions
- How can AI help a medical practice's day-to-day operations?
- The practical wins are in work that repeats: prioritizing outreach lists, flagging claims likely to be denied, summarizing reports and drafting routine documents. Practice administrators get the most from starting with one high-volume task, piloting it, and measuring the result before expanding.
Source: Physicians Practice: 8 ways practice administrators can harness AI today
- Do we need data scientists to use AI in our practice?
- No. We build for operational, non-technical users. The prompts, data connections and outputs are set up for you, and the results show up in tools your staff already use. Someone on your team needs to own the process, not the code.
- How do we use AI safely with patient data?
- Treat AI like any other system that touches protected health information: limit the data it sees to what the task needs, keep a human reviewing its output, log what it does, and check vendor agreements. The NIST AI Risk Management Framework gives a plain structure for mapping and managing those risks.
- How long does an engagement take, and what does it cost?
- It depends on your data, your goals and how much your team wants to own. We scope every engagement in a free strategic assessment and give you a fixed plan before any work starts. Contact us to set one up.
Find your first AI use case
In a free assessment we look at your data and pick the one task where AI will save your team the most time.