Abstracta AI-powered quality engineering company that helps enterprises release critical software with confidence today introduced Quality Intelligence as emerging practice for software quality in AI era. Quality Intelligence connects systems context and human judgment to understand risk of every change and decide with confidence where to invest effort. Co-CEO Sofia Palamarchuk presents vision and first version of Quality Intelligence Manifesto in today opening keynote at Quality Sense Conf 2026 in Montevideo Uruguay announced Oct 13 2026 San Francisco.
AI has changed how fast teams build software. Writing code is no longer what slows delivery down hard part is making sure software has quality business needs at pace it needs it. More code also means more changes and each change can introduce risk.
Organizations that speed up development while keeping same validation and control mechanisms end up creating major bottleneck. In banking that risk weighs even more because software error can affect money personal data or thousands of customers. Question for engineering leaders is how to understand risk and make sound release decisions at same speed they now build.
In 2025 Abstracta named Quality Intelligence Gap disconnect between what AI produces and what teams need to understand to make safe release decisions. For years quality meant testing build something then check whether it works. When organization ships hundreds or thousands of changes that is no longer enough. Quality Intelligence closes gap by using everything teams know about software from requirements code and tests to incidents and production behavior to continuously understand risk of each change and whether they have evidence to ship.
Approach shares principles of US Department of Treasury Financial Services AI Risk Management Framework released February 2026 managing AI risk according to each institution stage of adoption and embedding accountability into AI decisions. Abstracta Quality Intelligence Maturity Model places organizations on five stages from exploration and individual adoption to AI-assisted release decisions.
Abstracta Intelligence helps teams validate changes at same pace they build them. Its agents built on Tero connect to systems banks already run from Jira and CI/CD pipelines to AS/400 and core banking platforms and prepare release decision System Understanding explains how feature flow or business rule works across docs tickets code and tests Change Impact shows what changed and which areas may be affected Risk Assessment flags risks based on history defects weak coverage and incidents Release Readiness summarizes evidence for go/no-go decision that person signs off on Knowledge Capture turns expert knowledge into reusable auditable context Testing Maturity DORA metrics and Release Readiness dashboards give QA engineering and leadership shared baseline for each release while audit trails defined roles and human approval keep people accountable for every go/no-go call.
A Track Record in Banking
Abstracta has spent nearly 20 years improving software quality in business-critical systems including work with global banks such as BBVA and Santander. With Bantotal R&D team and Microsoft AI Co-Innovation Lab Abstracta built generative AI copilot to help teams understand core banking system made up of hundreds of thousands of programs.
Across engagements Abstracta approach delivered 40% reduction in production defects in under six months regression cycles cut from days to about 30 minutes and more than 2000 hours saved per month through AI agents built on Tero.
Executive Perspective
Producing software is no longer bottleneck. AI lets produce software much faster but more code also means more changes and more potential risk. In banking software error can affect money personal data or thousands of customers. Conversation should go beyond how to build faster with AI to how understand risk and make better decisions at that same speed.
Quality Intelligence brings together technical context business rules and knowledge of experienced testers and analysts so teams can base release decisions on evidence. Framework gives people visibility and context when they need it and decision about what ships stays with people responsible for it. That is how organizations running critical software can adopt AI to ship faster with confidence.
Availability
Abstracta Intelligence engagements start with Abstracta 90-Day Quality Intelligence Framework which defines what to prioritize what changed what evidence missing what impact AI having and what to scale. Tero is free and open source on GitHub.
About Abstracta
Abstracta is an AI-powered quality engineering company that helps organizations release critical software with confidence. Founded in Uruguay in 2008, Abstracta works with banks, fintechs, insurers, and global enterprises where software quality directly affects revenue, risk, and customer experience, including Santander, BBVA, Broadcom, Pernod Ricard, and Shutterfly.
