Omniwise Tech exists because institutional-grade data intelligence belongs outside institutions. Every engagement is delivered with the same rigour applied at Latin America's largest banks and the Inter-American Development Bank.
Daniel Bracamonte Del Aguila spent two decades designing and governing enterprise data systems for Latin America's largest financial and public institutions. At Scotiabank Peru, he led the BI team serving more than two million customers — building the data architecture, KPI frameworks, and governance processes that supported executive decision-making across the bank. At Compartamos Bank, he brought the same discipline to Mexico's largest microfinance institution, where data quality and operational intelligence directly affected millions of low-income borrowers. At ESSALUD, he designed data governance for Peru's national public health insurer — 11 million beneficiaries, one of the largest institutional datasets in Latin America.
With the Inter-American Development Bank, he transitioned from institutional implementation to program-level advisory — leading technology consulting across five programs in four countries, including work in agri-food, fisheries, and rural development. That experience required translating enterprise-grade BI and AI methodologies into organizations with limited technical infrastructure, diverse data environments, and complex stakeholder structures. It also built a network across the hemisphere that Omniwise Tech now brings to every engagement.
He now operates from Stratford, Prince Edward Island, where Omniwise Tech was founded to serve Atlantic Canadian organizations. The fishing cooperatives, provincial agencies, export manufacturers, and professional services firms of Atlantic Canada face data and intelligence challenges that are not simpler than those of a Latin American bank — they are different, and they deserve the same quality of analysis and implementation.
What large institutions taught us — through years of enterprise data architecture, BI implementation, and AI governance — is that the methodology matters as much as the technology. Governance frameworks that ensure data quality. Architecture decisions that survive organizational change. Implementation processes that account for the human side of technology adoption. These are disciplines that major institutions spend decades and significant capital developing. Their value is not limited to organizations of that scale.
Small and mid-market organizations — the fishing cooperative trying to optimize its supply chain, the provincial agency managing a rural development program, the professional services firm that has outgrown its current systems — face data and intelligence challenges that are structurally identical to those of large institutions. The stakes are different. The resources are different. But the need for rigorous analysis, sound architecture, and disciplined implementation is exactly the same. These organizations deserve the same caliber of work. Most do not have access to it.
Atlantic Canada is the proving ground. The region's economy — fisheries, agri-food, tourism, public sector, and a growing technology sector — represents a concentration of organizations where intelligent use of data could produce disproportionate results. If we can demonstrate that institutional-grade BI and AI consulting creates measurable competitive advantage for a crab processing operation in PEI or a Crown corporation in New Brunswick, we can take that model to national and international markets. That is the ambition. The work is how we earn it.
Our experience is implementation experience. We have built data systems, deployed AI tools, and managed the organizational change that makes technology adoption successful. We work alongside clients through the hard parts — not from a comfortable distance.
Every engagement is designed with reuse and productization in mind. The governance frameworks, data architectures, and AI systems we build for one client are constructed to be adapted, extended, and deployed across other organizations and markets. Consulting that becomes product is the model.
We make no claims without evidence and no recommendations without analysis. Our advice is grounded in measurement — of your data, your operations, and the outcomes we deliver. If a proposed solution cannot be measured, it is not a solution. It is a hypothesis.
Two decades of enterprise implementation. Now applied to Atlantic Canada. Start with a conversation — no slides, no pitch, just clarity about what your data could be doing.
+1 (902) 916-9137 · core@omniwise.ca · Stratford, PE, Canada