AI Enablement

AI Enablement

Most companies trying to act on AI run into the same wall: their data isn't ready for it. Siloed systems, inconsistent records, and no unified source of truth mean AI tools return unreliable answers, and the problem gets blamed on the model when it's really the foundation. Our AI Enablement engagement starts with an assessment of your current data ecosystem: where it lives, what shape it is in, where the gaps are, and what a realistic path forward looks like. That assessment produces a clear roadmap, a risk and gap analysis, and a scoped estimate for the next phase, so you know what to expect before you commit. Beyond data readiness, we work with clients on AI feature integration, secure architecture design, model API connections, and the practical question of where AI belongs in your product and where it does not.

Start with the Problem

Before we talk about AI, we talk about the real problems you are trying to solve. That conversation shapes everything. Sometimes AI is the right tool, but sometimes a simpler solution gets you there faster and cheaper. We will tell you which is which, not just sell you a build.

Data Assessment

When AI is the right direction, we'll assess whether your data is ready for it. Siloed systems, inconsistent records, and no single source of truth make AI outputs unreliable regardless of which model you use. We assess your data ecosystem and share what the next phase looks like based on our findings.

Build on Solid Ground

Disconnected spreadsheets, stale exports, and inconsistent records don't just slow reporting, these speed bumps make AI results untrustworthy. We normalize and centralize your data before a model ever touches it, because the quality of what goes in determines the quality of what comes out.

Stay in Control

AI integrations that are not designed with data boundaries from the start create security and compliance exposure. We build governance in from day one: what the model can see, what it cannot, how that gets enforced technically, and who maintains accountability for it all.
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When we saw the new DIBS for Kids software application, it was clear from design to development that Volano Software had listened to us.”

— Marie Kovar, DIBS for Kids

How the Volano Process Works

Discovery and Solutioning

  • Understand and document the current state.
  • Ideate and develop future narrative.
  • Sales team creates narrative and estimates based on client needs.
  • Deliverable: Statement of work (SOW)

Project Kickoff

  • Sales team hands off to the software development team.
  • Our team meets you and your team.
  • Deep dive into our build process.
  • Deliverable: Project begins.

Iterative Development (Building Starts!)

  • Plan what will be included in the next 2-week sprint.
  • Design, code and test.
  • Team Communication to build the project, based on client needs.
  • Deliverable: Iteration meeting w/demo & next sprint planning.

Internal System Testing

  • Create test plan based on requirements in the SOW.
  • Volano team follows plan and completes testing.
  • Development team ensures SOW requirements have been met.
  • Deliverable: Deliver custom test plan.

User Acceptance Testing

  • Utilizing the test plan, the client completes their testing.
  • Ensure requirements outlined in SOW match the project.
  • Client and Development team collaboration.
  • Deliverable: Sign-off on acceptance.

Software Go Live

  • Review go-live plan.
  • Launch software (implement the plan).
  • Communicate and plan next phase.
  • Deliverable: Present plan for ongoing support and augmentation.

Solving challenges is best done with a team.

Whether a small project or a large scale adoption, we have handled it all. Choose the path best for your schedule.

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