What We Assess
Most businesses have more AI opportunity than they realize, and lessreadiness than they assume. Our audit examines four dimensions of your organization to identify where automation and intelligence will generate measurable returns, and where the prerequisites are not yet in place.
Operations
We map your core workflows end-to-end, identifying repetitive tasks, decision bottlenecks, and manual handoffs where AI can reduce cycle time or eliminate errors. We look at volume, variability, and current error rates.
Tech Stack
We review your existing software, APIs, and infrastructure to determine what integrates cleanly with modern AI services and what creates friction. Legacy systems are not disqualifying, but they change the approach.
Data Assets
AI runs on data. We evaluate the quality, accessibility, and structure of your existing data: CRM records, transaction logs, documents, communications. We identify gaps that would block high-value use cases.
Team Capabilities
We assess your team's current comfort with AI tools, their appetite for change, and the skills that would need development. Successful AI adoption is as much about people as it is about technology.
Audit Process
Interviews
Talk to the people doing the work
Map Workflows
Document actual processes
Tech Review
Assess systems and data
Score
Rank opportunities by ROI
Interviews
Talk to the people doing the work
Map Workflows
Document actual processes
Tech Review
Assess systems and data
Score
Rank opportunities by ROI
Readiness Audit Services
The Audit Process
The engagement runs two to three weeks depending on the size of your organization. We work alongside your team, not in isolation.
- Stakeholder interviews. We talk to the people who do the work, not just the people who manage it. Operations leads, department heads, and frontline staff each see different problems and opportunities.
- Workflow documentation. We map your key processes as they actually operate today, including the workarounds, manual steps, and tribal knowledge that never make it into official documentation.
- Technical review. We examine your systems architecture, data flows, and integration points. This is where we determine what is feasible in the near term versus what requires foundational work first.
- Opportunity scoring. Every potential AI application gets scored on three axes: business impact, implementation complexity, and organizational readiness. This produces a ranked list, not a wish list.
What You Get
The output is a prioritized roadmap, not a generic report full of industry trends. Every recommendation is specific to your business, grounded in what we observed during the audit.
- Prioritized opportunity map. A ranked list of AI use cases with estimated impact, implementation effort, and dependencies. You will know exactly what to tackle first and why.
- Readiness scorecard. An honest assessment of where you stand across data, technology, process, and people. No vanity metrics. Each dimension includes specific actions to improve readiness where needed.
- 90-day action plan. Concrete next steps for your highest-priority opportunities, including vendor recommendations, resource requirements, and milestones.
- Risk assessment. Where AI introduces new risk to your business: data privacy, regulatory compliance, vendor lock-in, and organizational change management. These are addressed directly, not buried in footnotes.
Who Benefits Most
This audit is designed for organizations that are past the curiosity stage and ready to make informed decisions about AI investment.
- Mid-market companies with 50 to 500 employees who know AI is relevant but need clarity on where to start and what to prioritize.
- Operations-heavy businesses in logistics, professional services, healthcare administration, or financial services where process efficiency directly impacts margin.
- Leadership teams who have been pitched by AI vendors and want an independent, vendor-neutral perspective before committing budget.
- Companies with failed AI pilots who invested in a proof of concept that did not deliver and want to understand what went wrong before trying again.