Applied Artificial Intelligence
Endorsement from global leaders
We build MaIA on the most robust AI platforms on the market, selecting the best technology for each use case and environment. We are platform agnostic: we work with on-premises, cloud, or hybrid architectures, depending on the operational reality of each client.
Does your company generate data but does not generate value with it?
It goes from scattered data to Applied intelligence with real impact in business.
Without a clear AI strategy:
Data that exists but They are not translated into decisions
AI pilots no clear return no prior validation
Slow decision-making, fragmented or based on intuition
Critical processes that They depend on people, Not of systems
Initiatives of Dispersed AI and without governance
With MaIA:
You identify where it is Real value before investing
You convert scattered data into one a single, clean and governed source
Unfold trained AI agents with the knowledge of your company
Tomas' decisions with reliable, real-time information
Scaling artificial intelligence in a controlled way and with measurable ROI
MaIA transforms your operation into a strategic advantage
DISCOVER THE VALUE BEFORE INVESTING
We validate technical and business feasibility before building any model.
DATA READY FOR AI
We integrate, clean, and govern your data so that artificial intelligence can operate on a solid foundation.
AGENTS WHO KNOW YOUR BUSINESS
Copilotos are trained with your processes, data, and real knowledge — not generic models.
REAL-TIME DECISIONS
Dashboards, traffic lights, and predictive models that anticipate, do not react.
RESULTS IN SEASONS
Methodology focused on quick wins and controlled scaling from the first cycle.
AI does not start with technology. It starts with understanding where the real value is of your operation.
WHAT WE DO
(in the order that really matters)
1. AI Value Discovery
➤ We identify where the real value of AI lies in your operation — before investing a single penny in technology.
Accelerate digital transformation with a technology foundation that is scalable, reliable and ready to evolve.
We analyze your critical processes and prioritize use cases based on their real business impact. We validate two dimensions: whether the data is sufficient and reliable to build predictive models, and whether the cases that use language models have a viable return on investment before committing budget to technology. The result is a clear roadmap with defined quick wins and use cases with confirmed technical and financial feasibility.
We facilitate sessions with business leaders, analyze key processes, and identify opportunities where AI can automate, anticipate, or assist. This phase typically takes 3 to 5 weeks, at the end of which we deliver a prioritized portfolio of use cases with confirmed technical and financial feasibility.
85%
Of the AI projects that fail, it is due to a lack of quality data, not the chosen technology.
Gartner, 2023
Success story:An industrial company avoided investing in premature automation after discovering that its production data had 40% inconsistencies. With the right roadmap, it launched its model with positive ROI from the first quarter.
2. Data Ready & Business Insights
➤ We prepare your data for AI and convert it into decisions with real impact
We work the entire data chain. In the ingestion layer, we connect dispersed sources—on-premise, cloud, or hybrid—and apply quality, cleansing, and governance to build a reliable and traceable foundation. In the exploitation layer, we enable a semantic Data Warehouse where teams and systems can consume information independently, predictive models that anticipate critical business behaviors, and LLM agents that enable querying information in natural language without relying on manual reports.
We design a unified semantic layer that acts as a golden source of reliable consumption—both for Business Intelligence tools and for cognitive agents that consult in natural language. The result is a self-consumption model governed by IT, but with operational independence for the user areas.
Success story:A consumer company with 500K SKUs reduced its forecast error from ±40% to less than 20% by integrating Sell In/Sell Out data with a predictive model per point of sale.
60%
Operational staff time is spent preparing data rather than analyzing it.
Forrester, 2023
3. Corporate AI Assistants
➤ AI agents trained with your company’s real knowledge, processes, and data
We develop specialized copilots built on the market-leading language models — Claude, OpenAI, Microsoft Copilot, Amazon Q, and others— configured and trained with your company’s real knowledge, processes, and data. They respond in natural language, assist key teams in critical decisions, and integrate with your existing systems. They are not generic chatbots: they are agents with the specific context of your operation.
These copilots can draft reports, answer questions, assist in decision-making, and automate repetitive, low-value tasks. In this way, AI becomes another member of the team: contextualized, reliable, and always available—freeing up time, reducing errors, and expanding the capabilities of each collaborator without technological friction.
28%
Organizations that deploy specialized AI agents report a 35% reduction in operational decision time and a 28% increase in productivity.
McKinsey, The State of AI, 2024
Success story:An industrial plant implemented a copiloto trained with technical manuals and historical production data.
Results: -40% in time of diagnosing faults.
How do we use artificial intelligence?
At MaIA we don't talk about AI as a promise, but as a concrete practice. These are the capabilities we apply in each project:
- Computational Vision: Smart cameras and AI models to capture data from images — production monitoring, quality control, shift validation, and detection of abnormal conditions without relying on traditional sensors.
- Machine Learning for data quality: Algorithms for detecting anomalies, atypical values, and predicting missing values — improving the reliability of the data before feeding it into any model.
- LMs for Copilot agents: Generative models trained with the customer’s knowledge, policies, and context — capable of writing reports, answering questions, and supporting decisions in natural language.
- Clustering and AI for MDM: Aggregation techniques to detect duplicates, correlations, and hidden patterns — key to ensuring consistency, uniqueness, and traceability in master data.
- Advanced predictive models: Predictive imputation, automated feature engineering, anomaly detection, and intelligent encoding — so that each model learns from clean and contextually valid data.
HOW DO WE DO IT?
➤ Methodology oriented towards real value, not technology per se
We don't start with the model. We start with your operation. Our methodology combines strategic vision, technical expertise, and a focus on measurable results from the very first weeks:
- Understanding where the value is We verify that the data is sufficient and of quality to build AI models. We analyze patterns to predict, automate, or detect anomalies — before committing budget to technology.
- Enabling intelligence with data We transform scattered data into a single, clean, and governed source. We enable decisions with accessible, connected, and understandable data for the entire organization.
- Activating intelligence in daily work We deploy copilots and AI agents trained with your company’s knowledge. They assist teams with accurate responses using natural language and real data.
- Measuring, evolving and scaling We monitor performance, document ROI, and expand capabilities based on value delivered—from point solutions to a truly intelligent operation.
We do this so that AI stops being a project and becomes a new way of operating.
RESULTS
that speak for themselves
%
REDUCTION IN TIME REQUIRED FOR DIAGNOSTICATING PLANT FAILURES
%
REDUCTION IN RESOLUTION TIME IN SUPPORT PROCESSES
%
INCREASED PRODUCTIVITY OF FIELD EQUIPMENT
%
MINIMIZATION OF FORECAST ERROR IN CONSUMER COMPANIES
Some clients with whom we have already transformed operations
Why MaIA?
MAIA is the Data Intelligence initiative of Grupo Scanda — more than 30 years of experience in technology solutions, now applied to artificial intelligence practice with measurable results.
Proven experience:
Success stories in manufacturing, retail, and consumer goods with AI applied to critical operations.
World-class certifications:
Microsoft AI Engineer, Azure ML, AWS Machine Learning Specialty.
Leading allies:
Claude, OpenAI, Microsoft, AWS, Google Cloud, NVIDIA.
Integral vision:
From validating the value with IA Value Discovery to operating cognitive agents with Corporate AI Assistants.
Ready to boost your business?
We have the solution for youContact by telephone
(55) 1251-2700
Location Mexico City
Miguel Laurent #804, Col. Letrán Valle, Alc. Benito Juárez
Español 
English