Specialists in artificial intelligence applied to business
At Avanzia we transform business operations with artificial intelligence built to solve real problems. From chatbots that serve customers 24/7 on WhatsApp, Instagram, and Facebook Messenger — answering the direct messages your business receives with AI and handing them to your team when needed — to facial recognition systems for access control.
Our team combines machine learning, natural language processing, and computer vision to deliver solutions with measurable results from the first month of implementation.
AI solutions we implement
Artificial intelligence adapted to the specific needs of your company
Chatbots 24/7
Intelligent virtual assistants that serve your customers 24 hours a day, 7 days a week, on WhatsApp, Instagram, Facebook Messenger, and your website.
Specialized AI Agents
Autonomous agents that run complex tasks: message classification, report generation, and decision making.
Predictive Analytics
Machine learning models that anticipate trends, demand, and customer behavior for proactive decisions.
Process Automation
Intelligent workflows that remove repetitive tasks and reduce human error in critical operations.
Natural Language Processing
Systems that understand and process text and voice in Spanish and English for classification, summaries, and automatic replies.
Facial Recognition
Computer vision for access control, identity verification, and workplace security.
Casos de Éxito
Real projects where artificial intelligence changed how our clients operate
CentroMed 360
WhatsApp chatbot with AI that classifies incoming messages and routes them to the right area.
Automatic message classification and routing
Vive la Baja
CRM with WhatsApp automation, AI voice calls, and NetSuite synchronization.
Fully automated CRM
Servicio en tu Compañía
Access control with facial recognition, 80+ operating modules.
80+ modules with AI built in
Preguntas Frecuentes
Lo que más nos preguntan empresas al evaluar este servicio.
What kind of AI can my company implement today?+
What is already mature and running in production: WhatsApp chatbots with intent classification (customer service, appointment booking, collections), voice agents for outbound calls, automatic report generation from conversations, OCR to process invoices or documents, semantic search over your internal documents, and facial recognition for access control. Creative generative cases (images, video) are still experimental for business use.
Do I need large amounts of data to use AI?+
Not for most cases. Models like Claude and GPT come pre-trained; you only need your data for context, not for training. A WhatsApp chatbot works with 20-50 example conversations. An agent that knows your catalog works with your current product database. Only cases such as demand forecasting or fraud detection require large histories (12+ months of transactions).
How much does an AI project cost?+
A WhatsApp chatbot with conversational AI runs $80,000-$250,000 MXN to implement plus $3,000-$15,000 MXN/month to operate (Anthropic/OpenAI APIs and infrastructure). A voice agent for calls: $150,000-$400,000 MXN of setup. More complex systems (facial recognition, multi-channel agents) run from $400,000 to $1,500,000 MXN. More detail by case type in our blog post "Cost of implementing AI in a mid-size company in Mexico".
How long does it take to implement an AI chatbot?+
A working MVP for WhatsApp takes 3-5 weeks: 1 week defining flows and connecting to your systems, 2-3 weeks building and training with your data, 1 week testing with real users. More complex agents (multi-step, calling internal APIs) take 8-12 weeks. We work in weekly sprints so you see continuous progress instead of waterfall.
How do we measure the ROI of an AI project?+
Before starting we define 2-3 observable metrics: average response time, % of queries resolved without a human, tickets handled per agent, cost per interaction. You get a dashboard with those metrics in real time from day one. We would rather you measure return against your own baseline than against the average of another client: that is why the baseline is captured before anything is switched on.