We find where it pays off
We review your processes and pick the one that combines the greatest impact with the least friction in data and integration. Not the flashiest: the one that can hold up in operation.
ARTIFICIAL INTELLIGENCE
Take artificial intelligence from pilot to results
We identify the use cases with the greatest value, build solutions connected to your data and processes, and establish the governance needed to bring them safely into production.
Explore Artificial Intelligence ↓Start with the right use case
Servinformación's AI Center of Excellence brings together strategy, engineering and operations so that every initiative has a business objective, clear owners and a sustainable adoption path. Evaluate your organization's maturity, prioritize opportunities and define a realistic path to production.
- A single team for strategy, data, engineering, integration, security and operations.
- Prioritization based on value and feasibility before committing to a build.
- Experience in geospatial data and analytics for cases where territory is a critical variable.
- Flexibility to work with Google Cloud, AWS, Azure and the existing technology ecosystem.
- Support to build internal autonomy and scale new use cases with consistent criteria.
We build end to end
With your data, integrated into your systems and with a metric defined from day one. If the metric doesn't improve, you find out early.
We measure and scale
The first case in production is what funds the second. Adoption is built on results, not on presentations.
The challenge
The challenge isn't testing AI, it's turning it into business capability
Many pilots stall because they lack a well-defined problem, available data, approval criteria or someone responsible for operating the solution. Our work begins before the model and continues after deployment.
Prioritize by impact and viability
Compare use cases by expected value, data availability, risk, effort and integration.
Design with governance and security
Define access controls, data use, human validation, traceability and approval criteria from the start.
Integrate AI into the real process
Connect models and agents with the organization's systems, knowledge sources and workflows.
Measure and improve in production
Monitor quality, adoption, cost, performance and business changes to keep the solution useful.
How we work
Our way of working
AI Advisory
We assess maturity, data, processes and risks. We prioritize use cases and define architecture, governance, metrics and a roadmap.
AI Scale
We design, build and integrate solutions with the client's team. We prepare operations and transfer knowledge to facilitate adoption.
Managed AI Services
We monitor, support and optimize solutions in production so they keep meeting business objectives.
AI Center of Excellence
We help establish roles, standards and processes so the organization can evaluate, approve, scale and govern new initiatives.
Where it applies
Artificial intelligence use cases
Customer service and experience
Assistants that query authorized information, guide requests and support teams in resolving cases.
Enterprise knowledge
Search and synthesis across documents, policies, content and internal data, with permissions and traceable sources.
Process automation
Agents and models that classify, extract, validate or generate information within workflows with human oversight.
Analytics and prediction
Demand forecasting, anomaly detection, segmentation and recommendations to support decisions.
Software development
Assistance with analysis, documentation, testing and code generation within defined controls.
Geospatial intelligence
Analysis of imagery, territory and mobility for agriculture, infrastructure, risk management, logistics and expansion.
Our own solutions
Our own solutions that speed up integration
Architecture
An architecture built to scale
We work with multicloud architectures and choose services and models according to the use case, available information, constraints and existing operations.
Data
quality, access, integration, privacy and traceability.
Models
selection, evaluation, instructions, guardrails and version control.
Applications
user experience, integrations, automation and human oversight.
Operation
monitoring, cost, performance, support and continuous improvement.
Government
roles, policies, approval criteria, security and risk management.
Frequently asked questions
How do you choose the first AI use case?
It should combine business impact, sufficient data, a clearly scoped process, manageable risk and someone responsible for adoption. The diagnostic compares these variables before construction begins.
Is it necessary to migrate to a specific cloud?
Not necessarily. We evaluate your existing architecture and tools. The solution can be designed for Google Cloud, AWS, Azure or a multicloud environment, depending on the case.
How is the data protected?
The solution defines permissions, isolation, traceability, retention and usage controls based on the sensitivity of the information and the organization's policies. Cybersecurity is involved from the design stage.
What happens after the solution goes into production?
Models and processes need monitoring. Managed AI Services covers support, evaluation, optimization and adjustments to maintain performance, cost and usefulness.
YOUR NEXT BIG PROJECT STARTS HERE
Better decisions.
New opportunities.
Do you have a data, cloud, AI or cybersecurity challenge?
Tell us and we'll suggest where to start.