Omniwise Tech exists because institutional-grade data intelligence belongs outside institutions. Every engagement is delivered with the same rigour applied at banks and government agencies.
Daniel Bracamonte spent two decades designing and governing enterprise data systems for some of Latin America's largest financial and public institutions — building the kind of analytical infrastructure that North American organizations now take for granted, but in environments where it had to be built from scratch.
At Scotiabank — one of Canada's Big Six banks, with significant operations across Latin America — he led a Business Intelligence Team in Peru, building the data architecture, KPI frameworks, and governance processes that supported executive decision-making across a retail portfolio of millions of customers. At Compartamos Bank, one of Latin America's largest microfinance institutions, he led data governance, pricing analytics, and BI delivery — where the quality of data directly affected credit decisions for 1.4 million low-income borrowers and generated incremental annual revenue. At ESSALUD, he designed the data governance and BI strategy for Peru's national health insurer, serving 13 million citizens across 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 digital transformation and technology consulting across Peru, Ecuador, Suriname, and Belize, with a focus on agri-food systems, fisheries traceability, food safety, and rural development. That work required translating enterprise-grade analytics and AI methodologies into organizations with constrained technical infrastructure, fragmented data environments, and complex regulatory and multi-stakeholder governance structures — the same conditions that characterize many mid-market organizations across the United States and Canada today. Those engagements built deep regional expertise and cross-sector knowledge that informs every Omniwise Tech engagement.
He now operates from Atlantic Canada, where Omniwise Tech was founded to serve organizations across North America that are serious about data. Whether the client is a regional bank in the American Southeast, a federal agency in Ottawa, an agri-food exporter in the Midwest, or a fishing cooperative on the Atlantic coast — the challenge is the same: turning fragmented, underused data into decisions that create measurable value. That is what Daniel has done for twenty years, and what Omniwise Tech delivers today.
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