Stop guessing where AI fits. Get a diagnostic that tells you exactly where to invest.
A structured AI readiness assessment that identifies your highest-ROI opportunities, builds the business case, and delivers an implementation roadmap in 14 days. For mid-market companies with $2M+ revenue.
The Problem
AI enthusiasm without AI clarity is expensive
Everyone has an opinion, nobody has data: Your engineering team wants a chatbot. Your COO wants to automate approvals. Your CEO read about agentic workflows on LinkedIn. Nobody has run the numbers on which initiative will move the P&L.
Strategy decks that collect dust: You've already paid a Big 4 firm or a niche consultancy for an 'AI strategy.' What you got was 80 slides about industry trends and a recommendation to 'explore AI-driven customer insights.' No specifics. No business case. No roadmap anyone can execute. That deck is on a shared drive somewhere, unread since the executive presentation.
Pilot projects that never reach production: Over 80% of AI projects fail to reach production (per Gartner). The most common reason: picking the wrong problem. When you choose a use case based on what's trendy rather than what's valuable, you get a proof-of-concept that impresses in a demo and dies in procurement.
The cost of waiting is compounding: Every month you spend in analysis paralysis, a competitor ships something that raises customer expectations in your market. The operational savings you could be capturing bleed out as manual labor costs.
Our Approach
14 days. Four phases. One definitive answer. A disciplined diagnostic that produces a scored, prioritized roadmap your team can act on the day we hand it over.
Phase 1 — Discovery & immersion (Days 1-3): Structured interviews with 6-10 stakeholders across leadership, operations, and technical teams. Full audit of data infrastructure and tech stack. Core workflow mapping end to end. Competitive AI review. We want to know where you lose time, where you lose money, and where your data is strong enough to support an AI system. Deliverable: Process audit document with annotated workflow maps and data readiness assessment
Phase 2 — Analysis & AI opportunity matrix (Days 4-8): The analytical core. Every potential AI use case from Discovery gets scored on business impact (revenue uplift or cost savings), technical feasibility (data availability, integration complexity, model maturity), and time to value (how fast it reaches production). The output is the AI Opportunity Matrix, replacing opinion with structured evaluation. Deliverable: AI Opportunity Matrix: scored and ranked opportunities with detailed evaluation criteria
Phase 3 — Recommendation & ROI quantification (Days 9-12): We build the business case for your top 3-5 opportunities: projected cost savings or revenue impact across three scenarios, estimated implementation cost and timeline, resource requirements, risk factors with mitigation plans, and a phased roadmap that sequences initiatives so each builds on the last. Every number is backed by methodology, not optimism. Deliverable: Business case document with financial projections, implementation roadmap (phased), and risk assessment
Phase 4 — Presentation & handoff (Days 13-14): We present findings to your executive team in a session built for decision-making. The deck answers one question: 'What do we build first, and why?' We walk through the Opportunity Matrix, defend our ranking, and present the business case. You leave with everything you need to brief your board, secure budget, and start -- with us or on your own. Deliverable: Executive presentation deck, complete documentation package, and proposal for build engagement (if applicable)
Deliverables
Discovery & Analysis (Days 1-8)
- Process audit document with end-to-end workflow maps for every department assessed
- Data readiness assessment covering infrastructure, quality, accessibility, and governance
- AI Opportunity Matrix with every use case scored across impact, feasibility, and time-to-value
Recommendation & Handoff (Days 9-14)
- Business case with projected savings/revenue for top 3-5 opportunities (three scenarios each)
- Phased implementation roadmap with sequencing, dependencies, resource requirements, and milestones
- Executive presentation deck built for board-level decision making
Bonus (if proceeding to build)
- Proposal for build engagement with fixed scope, timeline, and pricing based on diagnostic findings
Who This Is For
Right for you if: You're a mid-market company (50-500 employees, $2M+ revenue) that knows AI matters but hasn't committed to a specific initiative yet. You want a structured way to decide, based on data rather than best guesses.. You've tried an AI project before that stalled or underdelivered, and you want to understand why before investing again.. Your board, CTO, and operations lead all have different AI priorities. You need an outside assessment to get everyone on the same page..
Not right if: You already know exactly what you want to build and just need a development team. Go directly to our Custom AI Tool Development service.. You're looking for a free or low-cost AI 'audit' with no commitment. We invest significant senior time in every diagnostic, and our pricing reflects that..
Use Cases
Financial Services: A payments company with 300+ employees was evaluating AI across five departments at once: underwriting, collections, customer service, compliance, and marketing. Each department head had a different priority. The CTO was fielding vendor pitches weekly with no framework for comparing them. — Ran the full diagnostic. Interviewed 12 stakeholders, audited data across all five departments, and scored 18 potential AI use cases through our Opportunity Matrix. Underwriting automation had 4x the ROI of the next-best option and could be deployed in 8 weeks using existing data.. Outcome: The executive team agreed on underwriting automation within a week of our presentation. The build engagement began 10 days later. Estimated annual savings: $220,000.
B2B SaaS: A SaaS company in logistics had flat growth and rising support costs. The CEO wanted to 'add AI to the product' to justify a pricing increase and reduce churn. No concrete idea of what that meant in practice. — Ran discovery focused on the product roadmap, support ticket analysis, and competitor positioning. The Opportunity Matrix showed that the highest-impact use case was internal, not product-facing: an AI-powered support triage system that could cut first-response time by 70% and free the support team to focus on expansion revenue.. Outcome: Client moved from a vague 'AI product feature' plan to a focused support automation initiative. Implementation cost was one-third of the original product AI estimate, with faster time to value.
Healthcare / Healthtech: A diagnostic chain with 50+ centres was losing operational efficiency as it scaled. Report turnaround times were growing, radiologist utilization was low, and patient communication was entirely manual. — Mapped the full patient flow from booking through report delivery. Identified six AI-applicable touchpoints. The Opportunity Matrix ranked AI-assisted preliminary report generation and automated patient communication as the top two initiatives -- both high-impact, both feasible with existing data.. Outcome: The chain greenlit both initiatives in sequence. Combined projected impact: 35% reduction in report turnaround time and $110,000 annual savings in patient communication costs.
Results
A recent diagnostic project
Fintech — Mid-Market Lending Platform: $220,000 projected annual savings identified in 14 days. A lending platform with 200+ employees and $50M in annual loan disbursements came to us paralyzed by choice: five departments, eighteen potential AI use cases, and a board that wanted a defensible investment thesis before committing budget. We ran the full diagnostic in 14 days. The Opportunity Matrix scored underwriting document automation as the standout winner: high data readiness, proven model availability, 85% of the workflow automatable, and a projected $220,000 in annual savings from reduced manual processing. The executive presentation got the board on the same page in a single session. The build engagement started within two weeks.
Frequently Asked Questions
How long does the AI readiness assessment take?
14 calendar days, from kickoff to executive presentation. That's 3 days of discovery and stakeholder interviews, 5 days of analysis and opportunity scoring, 4 days of business case and roadmap work, and 2 days for presentation prep and delivery. We stick to this timeline because it forces focus on both sides.
What does the engagement look like week by week?
Week 1 is intensive on your side: we'll need 60-90 minutes with 6-10 stakeholders, access to your tech stack and data documentation, and a tour of your core workflows. Week 2 is intensive on ours: we build the Opportunity Matrix, quantify the business case, and prepare the executive presentation. You'll have a mid-point check-in on Day 7 to preview initial findings and flag gaps before we go deep on recommendations.
What does my team need to provide?
Time from 6-10 key stakeholders (one 60-90 minute interview each), access to your tech stack documentation, any existing process docs or workflow maps, financial data on operational costs for the departments we're assessing, and a point of contact for logistics. We send a preparation checklist before kickoff.
What if the diagnostic finds that AI isn't the right investment for us right now?
We'll tell you that directly, with specifics. In roughly 15-20% of our diagnostics, we find the highest-value next step is data infrastructure cleanup, process standardization, or a non-AI automation rather than an AI build. We'd rather give you an honest answer that saves you from a bad investment than sell you a build you don't need. The diagnostic fee is the same either way.
How is this different from a free AI assessment or audit offered by other firms?
Free assessments are sales tools designed to find an excuse to sell you something. Our diagnostic is the product. We charge for it because it takes significant senior time, uses a structured scoring methodology (not a checklist), and produces deliverables with standalone value. Many clients use the Opportunity Matrix to secure internal budget and then build with their own team. That's a fine outcome for us.
Can we use the diagnostic deliverables to build internally or hire another firm?
Yes. The deliverables are yours. The Opportunity Matrix, business case, and implementation roadmap are built to be useful regardless of who does the build. We believe we're the best team to execute on the findings, and our build proposal reflects diagnostic insights in ways no outside vendor can match. But there's no lock-in.
What's the minimum engagement, and can we start with just one department?
Single-department diagnostic starting at $5,000. The majority of our clients get more value from a cross-functional assessment, since that's where overlooked AI opportunities tend to appear. But a focused single-department diagnostic is a valid starting point if you already know which area has the most pain.
Do you sign NDAs and how do you handle sensitive business data?
We sign mutual NDAs before every engagement. All client data is handled under strict confidentiality terms, stored on encrypted infrastructure, and deleted within 30 days of engagement completion unless you request otherwise. Our team has worked with regulated industries including financial services and healthcare.
