AI-First Transformation
AI-First transformation isn't a project. It's a shift in your operating model. Your company spends 6 months and half a million to ship an AI project. Our clients do it in 2 weeks with 1 dedicated resource. The difference isn't technology. It's method.
The Framework
Diagnosis
3-8 weeks
Structured assessment mapping where AI creates measurable return in your operation. Includes 5 to 15 stakeholder interviews, data infrastructure analysis and opportunity prioritization by estimated ROI. McKinsey (2024) found 72% adopted AI but only 21% report cross-functional impact — the diagnosis closes that gap.
Validation
4-16 weeks
Proof of concept using real client data on real infrastructure, measuring accuracy, latency and integration compatibility against predefined success criteria. Gartner research indicates 85% of AI projects fail without prior technical validation — this phase eliminates that risk before significant investment.
Acceleration
3-7 days
Intensive sprint delivering a functional AI prototype from a specific business problem. Dedicated team with 4-hour feedback cycles and real-time decision-making. Harvard Business Review research shows rapid prototyping companies are 2.5 times more likely to launch successful AI products.
Evolution
ongoing
Continuous strategic advisory and operational AI reference. Capiva becomes the technical authority the organization consults before investing in new AI initiatives. Internal teams learn by seeing solutions running in production, not through presentations or training decks.
Start where it makes sense. Each phase delivers independent value. Together, they change how your company operates.
Start Where You Are
I don't know where to start
Strategic Diagnosis
In 3 to 8 weeks, the Strategic AI Diagnosis maps where artificial intelligence creates measurable return in your operation. The process includes stakeholder interviews, data infrastructure analysis and opportunity prioritization by ROI. Each initiative receives quantified return estimates, risk mapping and dependency analysis. You leave with an executable roadmap, not a report.
Learn more →I have an idea to validate
Technical Validation
Technical Validation runs your AI hypothesis against real data on real infrastructure over 4 to 16 weeks. The proof of concept measures accuracy, latency and integration compatibility against predefined success criteria. If validation fails, you save months and hundreds of thousands. If it succeeds, the technical foundation is production-ready.
Learn more →I need results now
Innovation Sprint
The Innovation Sprint delivers a functional AI prototype in 3 to 7 days with a dedicated team operating in 4-hour feedback cycles. Five deliverables: working prototype, executive demonstration, feasibility report, data-backed go/no-go recommendation and implementation estimate. Capiva's AI-first methodology runs at 3 times the speed of traditional consulting.
Learn more →Case Study
From 10 people and 6 months to 1 resource and 2 weeks
See how we transformed the AI operation of a global company with over 15,000 employees.
View case study →