Pentest na era da IA: encontrar vulnerabilidades ficou mais rápido. Saber quais importam virou o problema
Encontrar vulnerabilidades deixou de ser o maior desafio da segurança. Com scanners e IA identificando falhas em escala, o problema agora é entender quais riscos realmente precisam ser corrigidos primeiro. Neste artigo, veja por que o pentest continua essencial para validar impactos reais e orientar a priorização das correções.
Vibe coding na prática: como acelerar sem abrir espaço para vulnerabilidades
O que é vibe coding? Vibe coding é uma das formas mais rápidas que surgiram nos últimos anos para transformar ideias em software. Em vez de começar por um projeto longo, com estrutura inicial pesada e múltiplas etapas manuais, o usuário descreve o que deseja e ferramentas de inteligência artificial ajudam a gerar telas, fluxos, […]
Data Lakehouse: What it is and how the new data architecture provides a competitive advantage for Enterprise AI
Understand why the merger between Data Lakes and Data Warehouses has become the standard for companies seeking efficiency, governance, and digital acceleration with Artificial Intelligence. The data challenge in the era of AI For years, companies operated with two separate models: Data Warehouses for structured data and BI reports, and Data […]
Bugmageddon: How to Protect Your Business from AI Failures
Bugmageddon: How AI is Discovering Vulnerabilities Faster Than We Can Fix Them Digital security has always been a balancing act between those who develop software and those who try to exploit it. However, this balance is rapidly being disrupted. We are entering what experts and international media are already calling Bugmageddon: a new era in [...]
RAG: How Generative AI Starts Responding with Real Company Data
What is RAG and why are companies adopting AI connected to their data? The adoption of artificial intelligence in companies is no longer just an experimental trend. Increasingly, organizations are seeking to apply AI in real processes, connecting generative models to internal knowledge bases, corporate documents, policies, contracts, systems, and operational data. [...]
Technology, data, and AI are no longer just efficiency levers—they have become strategic business risks.
The message for 2026 is direct: technology, data, and artificial intelligence continue to be drivers of competitiveness, but they can no longer be treated solely as a topic of innovation or efficiency. They have become central elements of corporate governance and risk management…
Corporate AI with intelligence, privacy, and real data control
A recent Goldman Sachs report indicates that artificial intelligence models are exhausting the main publicly available data sources.
Recruitment and Selection Automation: When HR Bottlenecks Become Cost, Risk, and Revenue Loss
With the arrival of Artificial Intelligence (AI), the way we work is changing, impacting people's behavior in various ways.
When Finance Becomes a “Spreadsheet Factory”: The Invisible Cost of Slow Decision-Making in Industry
In industry, the CFO doesn't need more data. They need fast, reliable, and traceable decisions — with lineage, clear rules, and security.
The problem is that in many companies, critical information still lives in scattered Excel spreadsheets: different versions, endless tabs, broken formulas, numbers that don't add up.
Processes: The Foundation of Quality and Scale in Technology Companies
For an IT services company, well-defined processes reduce variability, decrease operational risks, and elevate perceived quality in every customer interaction, from pre-sales to ongoing support.