Generative AI

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By Flávia Batista July 10, 2026
Why your AI tools haven't fixed alert noise yet It's not the tools. It's everything that happens between them. By Flávia Batista
By Adriele Radmann June 22, 2026
Senior engineers lose 30% of their time to operational overhead. Discover how Agentic AI reclaims their cognitive bandwidth and prevents burnout-driven attrition.
By Ana Quaresma June 18, 2026
AI is no longer the differentiator — context is. Here's what four Atlassian ecosystem experts took from Team '26, and what it means for your team right now.
Neon AI agents icon network with glowing purple-blue lines and central “AI Agent” label on a dark background
By Ana Quaresma April 30, 2026
See how e-Core's AIOps solution helps IT teams prevent incidents, cut alert volume by 73%, and scale operations with governed, agent-driven automation.
Business meeting in a glass-walled office, with colleagues seated around a table and one person presenting.
By By the Tempo team April 9, 2026
In collaboration with Tempo, this article explores why rapid resource reallocation is now a competitive advantage, and how the most agile organizations turn planning into strategic impact.
Discover how AI-driven IT operations helped a leading on-demand delivery platform reduce MTTR by 70%
By Ana Quaresma February 27, 2026
Discover how AI-driven IT operations helped a leading on-demand delivery platform reduce MTTR by 70%
By Vando Gonçalves February 19, 2026
AI and governance must evolve as agentic AI makes autonomous decisions. Learn how organizations can balance control, observability, and scale in IT.
How Agentic AI transforms the SDLC
By Felipe Cauê Fraga Carneiro February 2, 2026
A concise look at how agentic AI evolves the SDLC from isolated tools to coordinated systems of autonomous agents, and what teams need to build this maturity.
An AI chip with a glowing brain graphic and the letters
By e-Core November 5, 2024
About the client The client is the first fintech specialized in import solutions for businesses in Brazil and Latin America that offers financial solutions in credit, financing, and currency exchange, along with technology solutions that simplify, streamline, and unify services on a single platform. The company stands out through three fundamental pillars: Technology : A team of programmers specialized in innovative solutions. Financial Expertise : Financial knowledge to identify the best products and maximize results. Import Focus : Founded in international trade with a long history in one of Brazil’s leading trading companies. The challenge The company operates through Sales Development Representatives (SDRs) who create business opportunities by contacting clients through various channels, including direct phone calls with leads. The business challenge was to extract quality metrics from these calls and ensure optimal use of the sales pitch , improving SDRs’ operational quality and increasing business opportunity conversion. Previously, all call analysis to identify service improvement points , pitch adjustments, and service quality assessments were conducted manually by the manager, who would listen to each call’s audio and perform evaluations. To help generate automated reports for analyzing these calls, e-Core offered support with a custom artificial intelligence solution using AWS resources . The solution The solution begins by using the SDRs’ phone call recordings with leads. The first step was to create a processing pipeline to convert the recordings into text. With the transcribed audio, we used Generative AI to evaluate the call. We developed a prompt to assess the dialogue between the SDR and a lead, analyzing aspects such as pitch adherence, communication skills, and presentation of the company’s product and services. The final analysis result provides constructive feedback focused on areas for improvement, development, and motivation for the SDR. We used a Generative AI model to automatically transform call transcriptions into structured data with Amazon Bedrock, extracting and organizing essential fields, and generating constructive feedback to improve SDR performance. The resulting file is stored in an AWS S3 bucket and sent to the manager’s area on the company platform via an AWS SQS queue. Below is the architecture of the custom solution developed by e-Core.

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