Frequently Asked Questions

No. You do not need technical skills, coding ability, or familiarity with AI lexicon to work with us. In most engagements, your role is to bring business context, goals, and operational knowledge, not technical depth.

The strength of modern AI is that it delivers value without requiring teams to understand underlying mechanics or write code. Our job is to translate your goals into practical solutions and handle the technical details for you.

In some specialized cases, such as advanced integrations or complex data environments, we may collaborate with your technical staff if you have them, but it is never a prerequisite.

Yes. We offer AI Enablement Workshops ranging from 1-hour introductory sessions to multi-day deep dives. Topics include AI fundamentals, prompt engineering, responsible AI practices, tips and tricks for effective use, and practical business applications.

Workshops are ideal for teams exploring AI's potential and building foundational skills before committing to full implementation. They can be delivered virtually or in-person and are customized to your team's experience level and industry context.

If you're interested in a workshop or want to discuss what format would work best for your team, schedule a discovery call and we'll design something that fits your needs.

You do not need a fully documented plan or a mature AI program to begin, but there is a minimum level of clarity and access that helps ensure a successful engagement. We need to understand the specific goals, problems, or opportunities you want to address, even if they are not formally written down.

A baseline level of data organization, accessibility, and cleanliness is also important. Our SkyeStaq Assessment Snapshot identifies any gaps. If the gaps are significant, we may recommend a broader AI Readiness Assessment to set the right foundation.

There are no strict technical prerequisites for most engagements. The exception is our AI Launchpad offering, which relies on connectivity to Microsoft 365 or Google Workspace for building the knowledge base.

You do not need AI governance policies in place before starting. Many clients do not. Governance guidance is part of our work and can be integrated at any stage.

We will also need clarity on roles, responsibilities, and key people involved in the area we are addressing. Identifying AI champions early is an important part of our process. Finally, having a general sense of your desired investment helps us right-size the scope and recommend a starting point that can expand over time.

Overall, if you have clear goals, accessible data, and engagement from the right people, you have everything needed to begin.

Absolutely. In fact, we prefer starting small to prove value, validate ROI, and build confidence before expanding and scaling. This approach reduces risk and keeps the work aligned with real business outcomes.

That said, we do not require a small start. If your organization already has momentum or needs support within a more AI mature environment, we can begin at the scale and depth that fits your current stage.

Data security and privacy are foundational to every engagement. AI introduces new considerations for information assurance because of how models process and move data, so we make sure you understand exactly where your information goes and what controls apply.

We design and architect solutions that protect your data, align with your policies, and fit your regulatory environment. We also stay current with the security and privacy standards of leading AI model providers and apply proven information security best practices across all supporting systems. Our goal is to ensure you can adopt AI responsibly without compromising trust or compliance.

Every engagement is customized to the needs of your organization, but we follow a consistent framework that ensures a structured and repeatable path to strong outcomes.

We begin with a discovery call and our SkyeStaq Assessment Snapshot, a short readiness assessment that helps us understand your goals, current capabilities, and where AI can create immediate value. From there, we define scope, deliverables, timelines, and required participation so expectations are clear before any work begins.

Depending on the engagement, we may run a brief kickoff with a smaller group of champions to align on direction and support organizational change. The work itself follows the approach outlined in our How We Work section, with phases designed to understand the business, validate opportunities, design the solution, and deliver a working outcome.

Throughout the engagement, we establish a communication plan to set touchpoints, share progress, and ensure feedback loops are built in. At handoff, you receive the working solution, documentation, training, governance guidance, and a prescriptive plan for operationalizing and adopting the AI capabilities we deliver.

Post-engagement support varies by engagement model, and we define those options up front. Overall, the process is designed to be structured and methodical, keeping you informed at every step and focused on measurable outcomes.

The time required varies by engagement, but effective enablement, learning, and problem definition always need some participation from your team. The level of time and input we ask for depends on where you are in your AI journey and how much feedback is needed to shape the right solutions. We cannot design meaningful outcomes without your insight into the business.

Before we begin, we outline exactly what level of involvement will be required from leadership and key team members. Our goal is to set clear expectations upfront so you can plan with confidence.