Applied AI # We apply AI the business can measure We identify where to apply models with verifiable ROI, validate use cases with real data, and build the capabilities, RAG, agents, personalization, human governance, that your organization operates as its own asset, not as a demonstration [ View case studies ](/en/cases-studies) [ Let's talk ](/en/contact) ## Applying AI with judgment is applying method before fashion We identify where to apply models with verifiable ROI, validate use cases with real data, and build the capabilities the business can operate. The promise of "transformation with AI" isn't built with licenses, it's built with judgment over regulated sectors, governable data architecture, and verifiable method ![Hombre usando lápiz óptico en monitor táctil, entorno de oficina](/sites/default/files/styles/large/public/2026-09serviciosinteligenciaartificialaplicada1-v1jpg.jpg.webp?itok=5j0B9DTH) ![Hombre usando lápiz óptico en monitor táctil, entorno de oficina](/sites/default/files/styles/large/public/2026-09serviciosinteligenciaartificialaplicada1-v1jpg.jpg.webp?itok=5j0B9DTH) ![Hombre usando lápiz óptico en monitor táctil, entorno de oficina](/sites/default/files/styles/large/public/2026-09serviciosinteligenciaartificialaplicada1-v1jpg.jpg.webp?itok=5j0B9DTH) ![Hombre usando lápiz óptico en monitor táctil, entorno de oficina](/sites/default/files/styles/large/public/2026-09serviciosinteligenciaartificialaplicada1-v1jpg.jpg.webp?itok=5j0B9DTH) Our engineering trajectory across regulated sectors in Latin America showed us that the difference between a technical capability and a business asset is the judgment to apply it. Models don't replace that judgment, they leverage it. And it's built on governable data architecture, not on license promises ## The value of AI isn't in the model, it's in applying it with judgment ## Applied AI that responds to every role In an enterprise organization each role puts different priorities in play when applying AI. Our model responds to all three ### AI architecture with technical governance Layered architecture, model gateway with capacity to choose or self-host models, integration with core systems, and technical governance over models active in production. Acquia Elite Partner in Latin America, Drupal Certified Partner Gold, Gold Sponsor of the Drupal AI Initiative. ### Measurable ROI with business criterion Use cases prioritized by verifiable business metrics, not by vanity model metrics. The success metric is defined before building, not after. First applied AI microsolution validated before October 31. ### Creative capabilities and AI discoverability Content optimized for AI answer engines (AEO/GEO), adaptive personalization, and digital companions that act on the editorial flow, so your brand becomes the answer AI cites. Drupal AI Initiative modules operating in production over +30 months of continuous uptime Finalist Acquia Awards 2026, Best Use of AI for Learning and Acceleration with Universidad de La Sabana [ View full case ](/en/cases-studies/university-la-sabana) ## What we build in this service Six applied AI capabilities in three groups that can be executed independently or as an integrated protocol, according to your digital ecosystem's maturity and cases prioritized by verifiable ROI. ### Content creation and optimization with AI Assisted generation integrated into the editorial flow, writing optimized for AI answer engine discoverability (AEO/GEO), curation and editing with digital companions, and automatic quality control, without losing editorial governance. ### Media and DAM with applied AI Automatic metadata enrichment, digital asset auto-tagging, accessibility compliance, and brand consistency, with AI operating on the DAM without manual review bottlenecks. ### Enterprise AI Search and RAG Semantic search that understands intent, not keywords. RAG over the client's proprietary knowledge bases so content assets become verifiable answers. First implementation in enterprise client under construction. ### Personalization, CDP, and conversational AI Adaptive experiences by profile and context, Customer Data Platform integrated into the digital ecosystem, and conversational agents that act on user service, internal support, and multichannel attention, without replacing the human voice where it makes a difference. ### Model gateway and layered AI architecture Integrations, APIs, and model gateway with the capacity to choose, swap, or self-host models according to the case. Enterprise layered AI architecture (infrastructure + models + orchestration + governance) designed not to lock you into a specific provider. ### Continuous human governance over AI Every AI action is queued for human review before reaching production. Batch approvals, audit logs, and complete review history. Your team operates at AI speed without losing control. ## Why esinergia for your applied AI We're not an agency with AI added at the end of the project. We're a technical partner that applies AI with neutral architectural judgment on the Drupal enterprise ecosystem, with continuous contribution to the global ecosystem, verifiable evidence in production, and capabilities validated internally before applying them to clients. ![Manos escribiendo código en una computadora portátil](/sites/default/files/styles/large/public/manos-tecleando-en-laptop-esinergia2026jpg.jpg.webp?itok=EwEJUSXN) ![Manos escribiendo código en una computadora portátil](/sites/default/files/styles/large/public/manos-tecleando-en-laptop-esinergia2026jpg.jpg.webp?itok=EwEJUSXN) ![Manos escribiendo código en una computadora portátil](/sites/default/files/styles/large/public/manos-tecleando-en-laptop-esinergia2026jpg.jpg.webp?itok=EwEJUSXN) ![Manos escribiendo código en una computadora portátil](/sites/default/files/styles/large/public/manos-tecleando-en-laptop-esinergia2026jpg.jpg.webp?itok=EwEJUSXN) ## Credentials behind every delivery Four verifiable reasons on how we apply AI with judgment. ### Neutral architectural judgment We apply AI on the Drupal enterprise ecosystem with neutral architectural judgment, the technical route is chosen by the case, not by commercial bias. ### Active contribution to the global AI ecosystem Dedicated developer on the Drupal AI Initiative + continuous contribution to the drupal.org project. Official participation in DrupalCon + sponsorship of Drupal CMS Launch Colombia 2025. ### First applied AI microsolution in production Universidad de La Sabana finalist Acquia Awards 2026 in "Best Use of AI for Learning and Acceleration" category, evidence of applied AI operating over +30 months of continuous uptime. ### Capabilities validated internally before client Our roadmap prioritizes AI microsolutions validated first in internal esinergia operations, before applying them to clients with enterprise judgment. Not demonstration, operational asset. ## How we work Three lifecycle phases applied to the vertical service, because intelligent capabilities cross the full cycle: they're discovered, built, and evolve with the business. 01 ### Discover We audit AI opportunities in your ecosystem with verifiable ROI, map available data architecture, and validate technical feasibility before committing to construction. Prioritized use cases + technical prerequisites + estimated effort + realistic implementation sequence. 02 ### Build Prototype validated with real data, model chosen according to the case (pre-trained with RAG or specialized), integration with the existing digital ecosystem, and user testing before production. 03 ### Evolve Response quality monitoring, model refinement with operational feedback, expansion of use cases, and continuous ROI measurement. Intelligent capability matures with operations, it's not delivered and forgotten. ## Applied AI in production Projects with technical and business evidence. No vanity metrics. [ ![ caso de éxito universidad de la sabana estudiante mujer con libros](/sites/default/files/medios-de-contenido/2026-09casodeexitouniversidaddelasabana-v1png.png) SVG ![Logo universidad de la sabana esinergia caso de exito](/sites/default/files/medios-de-marketing-y-marca/logo-universidad-de-la-sabana-esinergia-caso-de-exitosvg_0.svg) University of La Sabana ](https://www.unisabana.edu.co/) [ ![caso de Éxito Red Salud enfermera trabajando](/sites/default/files/medios-de-contenido/2026-09casodeexitoredsalud-v1png.png) RedSalud ](https://www.redsalud.cl/) ## Frequently asked questions Direct answers to the most common questions before getting started. ## How do you identify where to apply AI in my digital ecosystem? We start by listening to your operational context. Then we identify use cases prioritized by verifiable ROI and validated technically: RAG over your own content assets, conversational agents, assisted generation in the editorial flow, experience personalization. Each case is validated with real data before committing to construction. ## What technical prerequisites does my ecosystem need to integrate intelligent capabilities? Depends on the case. For RAG and semantic search: structured and governable content architecture, Drupal is the engine that sustains it best in regulated sectors. For conversational agents: integration with core systems. For personalization: consolidated data layer. We do the technical diagnosis in discovery, before committing scope. ## How is ROI measured for these solutions? With verifiable business metrics, not vanity model metrics. Average response time, user adoption rate, reduction in editorial team load, conversion increase, perceived response quality. The metric is defined before building, not after. ## Do you work with sensitive data from regulated sectors (healthcare, financial, government)? Yes. Most of our clients operate in regulated sectors (healthcare, government, education, financial services). We apply encryption, granular access controls, anonymization, and compliance with sector-specific frameworks, over the ISMS esinergia operates. Operational continuity is a contractual obligation in those sectors; so is sensitive data handling. ## Do you build proprietary models or use pre-trained models? We combine both depending on the case. For most enterprise cases, pre-trained models with RAG over the client's own data deliver the best balance between implementation time and response quality. For specific cases with sufficient proprietary data and fine control needs, we build specialized models. We are Gold Sponsors of the Drupal AI Initiative with a dedicated developer and continuous contribution to the drupal.org project, verifiable in the global community. ## Are you tied to a specific technical stack? No. We apply AI with neutral architectural judgment on the Drupal enterprise ecosystem. The technical route is chosen by the case, full control, balance between control and speed, or maximum SaaS speed. We choose with you the one that best serves the business, not by commercial default. #### Applying AI well starts by asking where. We start by listening to what problem you expect to solve and what information assets your organization has today. Then we'll honestly tell you whether this technology fits, what use cases to prioritize, with what technical prerequisites, and with what measurable success metric. [ Let's talk ](/en/contact) ![Isotipo de esinergia en marca de agua](/sites/default/files/medios-del-sistema/esinergia-isotipo-marca-de-aguapng.png)