AI Integration in Burgos — AI That Works Inside the Tools You Already Use

Manually using AI: you open ChatGPT, paste in some text, get a response, copy it somewhere else. Integrated AI: a new lead arrives in your CRM, AI automatically enriches the profile, writes a personalised follow-up email and schedules it — without anyone touching it. Same AI capability, completely different business impact.

Your CRM contains years of customer data. Your ERP has complete operational history. Your e-commerce platform knows exactly what customers buy and when. AI integration unlocks that data — making it queryable, actionable and automated in ways that were previously only possible with large data teams.

There are three main approaches to connecting AI to your systems, each with different trade-offs between speed, flexibility and cost.

If your AI writing tool does not know what is in your CRM, your AI chatbot does not know your product catalogue and your AI email tool does not know your customer history — each tool is starting from zero on every interaction. Integration is what turns a collection of AI tools into an intelligent business.

AI is only as good as the data it has access to. When customer data lives in the CRM, order data lives in the ERP, support tickets live in a helpdesk and financial data lives in accounting software — and none of these talk to each other — the AI cannot reason across them. Integration eliminates those silos.

Building integrations without a strategy leads to a tangle of point-to-point connections that is expensive to maintain and breaks whenever a single system changes. We design an integration architecture upfront that is maintainable, scalable and built on standard patterns.

Before writing a single line of code, we map your existing technology stack, understand how data flows between systems today and identify where AI integration would have the highest impact on your specific business.

We produce an integration architecture document that defines: which systems connect to which, what data flows where, how authentication and authorisation are handled, and what the fallback behaviour is when any component is unavailable.

We build custom middleware, webhook handlers and API connectors. Where off-the-shelf n8n connectors exist, we use them. Where custom development is needed, we build it to production standards — with error handling, logging and retry logic.

Every integration goes through functional testing, load testing and a security review before deployment.

Lead enrichment, automatic qualification, personalised follow-up generation, call summary writing, deal probability scoring and customer churn prediction. AI turns your CRM from a database into an active sales assistant.

Natural language queries over operational data, automatic report generation, anomaly detection in financial data, inventory optimisation recommendations and predictive maintenance alerts.

AI-generated personalised email content, automated segmentation based on behaviour, subject line optimisation, send-time optimisation and campaign performance analysis with actionable recommendations.

AI-generated product descriptions, automatic category tagging, personalised product recommendations, customer review sentiment analysis, inventory demand forecasting and automated customer service for order status queries.

Internal AI assistant that answers employee questions from your knowledge base, automatic meeting summaries, escalation routing for customer messages and notification enrichment with contextual business data.

A B2B services company integrated Claude into their HubSpot CRM to automatically enrich incoming leads (company size, industry, recent news) and generate personalised first-contact emails. Sales conversion from lead to meeting increased 30% in the first quarter. The sales team now spends time on conversations, not research.

A logistics company was manually entering data between their transport management system and their accounting ERP — a process that generated an average of 12 errors per week. We built a bidirectional integration with AI-powered data validation. Manual errors dropped to zero. The team member doing the data entry was reassigned to higher-value work.