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How Calibo’s IDP helps you to deploy an OpenAI Chat Bot

Calibo enables developers to create UIs and APIs in minutes and deploy them to multiple platforms, including EC2, Kubernetes, or OpenShift.   In this blog, we will go through all the steps to create a React web app and a chatbot widget, along with an API using Spring Boot that integrates with the OpenAI API…

Octavio Martin, August 7, 2024

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How to overcome challenges in data: privacy, ethics, and integration 

This blog urges businesses to take action by establishing robust privacy and ethics policies, ensuring AI models are trained on unbiased, consented data, and maintaining compliance with global regulations like GDPR.

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How to build a data-driven culture: empowering organizations with data literacy and tools 

Building a data-driven culture requires more than just access to data—it demands a strategic focus on data literacy and the right tools to empower teams.

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How to turn data into actionable insights: maximize the potential of your data

Converting raw data into actionable insights demands more than static dashboards—it requires real-time intelligence embedded into daily operations. This blog outlines a strategic framework based on building a robust analytics infrastructure, centering on insight generation, and dismantling data silos through governance and literacy.

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Tech trends we see in 2025 and beyond (including Agentic AI)

In 2025 and beyond, the adoption of agentic AI — systems composed of specialized, autonomous agents working together with minimal human oversight — is set to transform how businesses operate. These agentic systems offer human-like decision-making, contextual understanding, and adaptive behavior, enabling efficiency gains across industries like healthcare, finance, automotive, and logistics.

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How to leverage predictive analytics to make better decisions 

The blog outlines a three-step roadmap for businesses to unlock the power of predictive analytics and gain a competitive edge. First, it emphasizes the importance of gathering and preparing a diverse dataset—such as sales history, customer interactions, and external market data—to ensure reliable forecasting. Second, it explains how AI and machine learning tools can transform that data into actionable insights for demand forecasting, personalized marketing, dynamic pricing, and supply chain optimization. Third, it recommends implementing industry-specific use cases, like inventory prediction in retail, churn models in SaaS, and risk scoring in finance, to drive tangible business outcomes.

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How Enterprise Architects can get more support for technology led innovation  

Enterprise Architects are increasingly vital as guides for technology-led innovation, but they often struggle with obstacles like siloed teams, misaligned priorities, outdated governance, and unclear strategic value. The blog outlines six core challenges—stakeholder engagement, tool selection, IT-business integration, security compliance, operational balance, and sustaining innovation—and offers a proactive roadmap: embrace a “fail fast, learn fast” mindset; align product roadmaps with enterprise architecture; build shared, modular platforms; and adopt agile governance supported by orchestration tooling.

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