We combine process engineering, AI enablement, and knowledge architecture to turn operational complexity into scalable, institutionalized systems. Not theory — working infrastructure that outlasts any individual.
Multimodal AI architecture allows us to point language models at documents, property assessments, process flows, and operational data — and extract structured intelligence at scale. The underlying architecture is the same whether you're scanning property boundaries, reading industrial blueprints, or capturing tribal process knowledge before it walks out the door.
SOPs, manuals, contracts, inspection reports — fed into AI models to extract structured data, flag inconsistencies, and build searchable knowledge bases.
Multimodal AI reads site plans, maps, and photos to generate structured property assessments, boundary analysis, and due diligence summaries at a fraction of traditional cost and time.
AI agents observe, document, and structure operational workflows in real-time — capturing tribal knowledge before it disappears, and converting it into repeatable, auditable systems.
These live Claude.ai sessions demonstrate how AI agents can conduct structured intake conversations — gathering operational context, surfacing gaps, and building structured documentation in real time.
Whitepaper: How we transformed a static Excel model into a bilingual, AI-enhanced interactive investment platform — covering 15+ financial metrics and real-time IRR calculation.
We combine process engineering, AI enablement, and knowledge architecture to turn operational complexity into scalable, institutionalized systems. Not theory — working infrastructure that outlasts any individual.
A global technology company's Costa Rica finance team operated with fragmented processes and deep individual-knowledge dependency. We mapped the full process landscape and deployed an AI-enhanced workflow — reducing cycle time and creating consistent, auditable outputs across multiple business functions.
An operations team with knowledge silos and no coherent information architecture needed a system executives could actually use. We designed and built an interactive Knowledge Management pipeline and supported it with a C-suite pitch deck that secured organizational buy-in.
"Esquivel & Company helped us see operational bottlenecks that had become invisible internally. Things we accepted as 'the way it works' were actually solvable problems."Operations Director · Technology Sector
"Their process work was practical, not theoretical. We left with systems the team could actually use — not a consulting report that sat on a shelf."Finance Lead · Free Trade Zone Company
Before investing in technology or headcount, map what actually happens versus what is supposed to happen. The gap between those two realities is where your margin improvement lives. AI amplifies good processes — but it also amplifies bad ones. The sequence matters: process clarity first, then automation, then AI. Get the foundation right and the technology returns multiply.
Who leads this practice
Industrial engineer · Operational excellence and processes
Education and certifications
Industrial engineer from the University of Costa Rica, with a master’s in Business Administration and an emphasis in Project Management. More than fifteen years in operational efficiency, process improvement and standardization in service organizations.
Since 2010 she has been responsible for implementing, managing and continuously improving the ISO 9001 Quality Management System at Costa Rica’s National Council of Rectors (CONARE), covering strategic, core and support processes. She is a certified lead auditor in ISO 9001:2015 and ISO 19011:2018.
As a consultant she has worked with boutique hotels across every operational area —front desk, housekeeping, maintenance, kitchen, food and beverage— with on-site diagnostics, staff interviews and workshops with middle managers.
Method. She combines process engineering —mapping, measurement, removing rework and bottlenecks— with the service standards of hospitality, backed by formal quality-management practice. She works closely with general management and operating teams, turning technical analysis into clear, practical and sustainable recommendations: quick-to-implement improvements, documented procedures and executive reports with findings and recommendations.
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