Systems | Development | Analytics | API | Testing

Raising the Stakes for Sustainable, AI-ready Infrastructure

Recent headlines are impossible to ignore. AI adoption is driving an enormous surge in demand for energy to power data centers and the storage systems operating within them. Energy constraints have become a primary bottleneck for data center development, with long grid connection queues and capacity backlogs.

How to Automate Green Bar Report Extraction in Banking

If you work in banking operations, you know what a green bar report is. You probably have a stack of them arriving every morning: end-of-day balancing reports, settlement summaries, general ledger extracts, and transaction logs that run hundreds or thousands of pages. These reports are printed in fixed-width text with alternating green and white bands so someone with a highlighter can trace a number across 132 columns without losing their place.

Katalon Product Roundup July 2026

July was an enterprise month. Most of what shipped answers the questions that come up once a test team grows past a handful of people: how do we hand documentation to an auditor, where is the evidence for this step, who changed this result and when, and how do we run the same suite against a feature branch without rebuilding the integration every time.

How ReportMiner Processes Mainframe Reports at Enterprise Scale

Mainframe reports are one of the oldest and most persistent data extraction challenges in enterprise IT. They are generated by COBOL programs, printed by JES2/JES3 spoolers, and exported as fixed-width text files from IBM i Series, z/OS, AS/400, and similar systems. They power critical operations in banking, insurance, government, healthcare, and manufacturing. They also look nothing like the documents that modern AI extraction tools are designed for.

How to Extract Data from Fiserv Report Files and Write It to Excel

TL;DR: Fiserv platforms generate fixed-width.rpt files where every field sits at an exact character position. Astera ReportMiner maps those positions through a visual template editor, extracts the data, validates it against your business rules, and writes it directly to Excel, CSV, or 200+ other destinations. One template handles every future instance of the same report type, and the full pipeline runs unattended on a schedule.

New: Turn conversations with your AI Analyst into a polished report

Getting an answer from your data has never been faster. Turning that answer into something you can share still takes hours. Genie, our AI Analyst, made it possible for anyone to answer questions about performance. Ask “Why did conversions drop last month?” or “Which marketing channels drove the most pipeline?” and you’ll get a clear answer in seconds, with the charts to back it up. But some answers are worth more than a reply in a chat.

Comprehensive guide to working with Python markdown

If you use the Internet, you have surely come across the term Markdown. Markdown is a lightweight markup language that makes it very easy to write formatted content. It was created by John Gruber and Aaron Swartz in 2004. It uses very easy-to-remember syntax and is therefore used by many bloggers and content writers around the world. Even this blog that you are reading is written and formatted using Markdown.