Velocity & Convergence
Obsolescence is a choice. While the market analyzes the past linearly, we map the exponential convergences in your sector.
You think you have a strategic 5-year window. The market says yes. The reality says you have 18 months.
The convergence of multiple technology lines has collapsed time. Leaders treating AI as a \"cost-cutting tool\" or \"disposable prototype\" are already dead. They just don't know it yet.
Why Context Engineering is the only real barrier against hallucination in production. The end of \"Magic Prompts\".
Data structuring engine. Transform free text into validated JSON/XML to integrate legacy systems without friction.
The new critical role between Dev and Business that will reshape your company's workflow in the next 18 months.
AI that becomes capability, not a project
A working pilot is the start, not the finish. We build the structure that turns AI into reliable, governed operation across the whole company: standards, guardrails, and teams that own their own outcomes. The organizational layer that sustains the transformation after the technology works.
Discover where AI creates real value
Don't know where to start? In 3-8 weeks, we map where AI delivers real returns in your operation. Stakeholder interviews, data analysis, prioritized roadmap. You leave with an actionable plan.
Prove it works before you invest
Have a hypothesis? We test with your data, on your infrastructure. In 4-16 weeks, you see AI running in your context. If it works, the technical foundation is ready for production.
Working prototype in one week
Clear problem, authority to act, real urgency. In 3-7 days, we deliver a working prototype, a board demo, and a go/no-go recommendation with data. Zero bureaucracy.
Every engagement leaves capability behind
Transformation without vendor lock-in. We teach your team to work AI-first day to day: the patterns, the guardrails, the way of operating. You end up autonomous, not dependent.
Each phase delivers independent value. Together, they change how your company operates.
How We Work →Capiva is a boutique artificial intelligence consultancy founded in Brazil in 2025. It combines business strategy, software engineering, and education to transform entire operations with AI. In our experience, the model delivers in weeks what traditional agencies take months to implement: specifically, prototypes validated with the client's real data.
Capiva operates in Brazil, the United States, and the United Kingdom. Our team built and runs an AI Center of Excellence for a global consumer goods company. We tested every hypothesis with real data before recommending any larger investment.
The Capiva Framework organizes AI adoption into four sequential phases. First, the Strategic Diagnosis maps opportunities; second, Technical Validation proves feasibility with real data; third, the Innovation Sprint delivers a functional prototype; finally, the Evolution phase scales what works. Each phase has a clear deliverable and a defined timeline.
The Capiva method is grounded in market research on AI adoption. According to McKinsey, 72% of organizations have adopted AI, but only 21% report measurable impact in more than one function. Deloitte finds that 88% of companies use AI while only 29% get real returns. In our experience, the difference is the infrastructure around the model: that is why Technical Validation proves feasibility with real data before the full investment.
Sources: McKinsey — The state of AI · Deloitte — State of AI in the Enterprise · Gartner — AI adoption research · Harvard Business Review
Capiva is a boutique artificial intelligence consultancy. It helps companies move from the intention of using AI to having AI running and delivering measurable results. Specifically: the team combines business strategy with technical execution, serving clients in Brazil, the US, and the UK.
Capiva serves mid-size and large companies in consumer goods, healthcare, energy, and financial services. The typical profile is an organization that has identified the need for AI but requires a strategic partner to define priorities and execute. The requirement is having a concrete operational problem with data available for validation.
Capiva operates as a strategic partner inside client operations, not as an external vendor. The structure is lean with specialists mobilized per project, ensuring direct founder involvement in every engagement. The company's AI-first methodology compresses project cycles from months to weeks, as validated in implementations with a global enterprise.
Capiva serves active clients in the United States and the United Kingdom, in addition to Brazil. Current work includes an AI Center of Excellence for a global consumer goods company operating in both countries. Communication happens in English and deliveries follow the client's timezone.
The investment in a Capiva project is bespoke and depends on scope, complexity, and duration. Projects start from R$25,000 (about US$5,000). Before any proposal, the team understands the client's scenario to size effort and impact precisely.
The Strategic Diagnosis is a directed 3-to-8-week investigation. It maps where artificial intelligence creates measurable value in the operation. First we interview stakeholders and analyze data; then we deliver a roadmap prioritized by return and feasibility.
The Strategic Diagnosis is for companies that know AI matters but do not know where to start. When leadership asks for an AI plan and nobody knows how to build one, the Diagnosis solves that. It works as a concrete starting point, prioritized by impact and feasibility.
The Diagnosis delivers a prioritized AI roadmap and an opportunity map by area. It includes analysis of existing data and infrastructure, with effort and impact estimates for each initiative. Everything is documented and presented to leadership, so you leave knowing what to do first and why.
The Strategic Diagnosis takes between three and eight weeks, depending on the size of the operation. It includes stakeholder interviews, process and data analysis, and prioritization sessions. It is fast because the focus stays on what truly creates value, with no unnecessary phases.
Technical Validation is the phase where we test whether an AI idea works in practice. We use the client's real data and infrastructure to prove feasibility before the full investment. When the board needs evidence, Validation turns we think it works into we tested and it works.
Technical Validation makes sense when a company has identified an AI opportunity but needs evidence before investing. Research from Gartner indicates that 85% of AI projects fail without prior technical validation using real data. Validation transforms assumption into concrete proof, reducing risk and providing data for board-level decision-making.
Validation delivers a functional proof of concept with your data and a technical feasibility report. It includes the proposed architecture for implementation and an analysis of risks and dependencies. You see AI running in your context before approving the larger investment.
Technical Validation is a proof of concept that uses real data and considers existing infrastructure. Unlike an internal PoC, which typically uses sample data and ignores integration, it already plans the path to production. It is not a throwaway prototype: it becomes the foundation of the real implementation.
The Innovation Sprint is the delivery of a functional prototype in 3 to 7 days. You bring a clear problem and receive a board demo and a data-driven go or no-go recommendation. It is intense and focused: clear problem, authority to act, and fast results.
The Innovation Sprint is for companies that have already validated an AI opportunity and want to implement fast. It also works for those with a clear use case and urgency for results. It is not for those still exploring: it is for those who have decided to act.
From an Innovation Sprint come a functional prototype, a demo for leadership, and a data-driven go or no-go recommendation. When the path makes sense, the technical foundation is already ready to evolve. The solution stays with the client, running, rather than being abandoned.
The Innovation Sprint lasts 3 to 7 days up to the functional prototype. It is an intense and focused cycle: clear problem, authority to act, and fast results. Each sprint delivers functional value, so you do not wait months to see results.
The AI Visibility Assessment evaluates how your brand appears in the answers of tools like ChatGPT, Gemini, Perplexity, and Copilot. Today many people search via AI, not only on Google. When your brand does not appear in those answers, you are invisible to a growing share of the market.