Devox Software is a US-based tech company founded in 2018, delivering high-load platforms and commercially viable AI, ensuring zero-downtime modernization.
Edge cases sitting in raw logs rarely make robots smarter. Robots get better when field experience becomes structured knowledge. Our CEO, Kostiantyn Gitko, shared this take with Forbes Tech Council as robotics moves into real work: "The problem is that the system cannot leverage edge cases as knowledge because most companies lack a well-thought-out data lifecycle management strategy. Teams need a structured way to capture experience instead of just logging events, since this data will train future robotic systems" https://t.co/MrnGtyY9FK
Interesting how teams can estimate sprint velocity, cloud costs, and delivery timelines with precision… yet ROI still turns into a guessing game. We built the Devox ROI Calculator to turn assumptions into numbers.
Try it and see what your next project could unlock.
https://t.co/Xm2QBRga7L
Devox Software turns 8 today 🎉 Eight years of building software, learning from real client problems, and turning messy ideas into reliable products. Same goal as day one: ship work that makes teams faster, clearer, and ready for what’s next.
Most manufacturers still treat traceability like a barcode problem. In 2026, it became the backbone of AI-driven operations. Unified Namespace, digital threads, autonomous factories — here’s what actually changed on the shop floor https://t.co/ZR5OLjsiB8
The era of leadership constrained by fear of breaking legacy systems will come to an end. Today, AI and AI-powered parallel testing reduce this complexity by mathematically verifying that new code behaves the same way as the old system. With this in mind, leaders will become visionary agents of transformation, relying on automated verification to safeguard business continuity without disruption. - Kostiantyn Gitko, Devox Software
https://t.co/vmOSiSjNwm
“AI works with data and generates solutions, but people design the environment where those solutions are governed. AI does not carry ethical or business accountability, so that responsibility will always stay with people. Seen in this light, today, engineering teams and business leaders are coming together in new ways, stepping into the role of designers of the company’s intelligence ecosystem”. - Kostiantyn Gitko for Forbes Technology Council https://t.co/u3VLg4Oa1n
Most process issues rarely start with one step. They stack between systems: small gaps, slow handoffs, missing context. Over time: margin drops, teams patch manually.
We mapped where value shows up vs leaks. Worth a look if you’re digging deeper. Download the full paper. https://t.co/en50MvC9c1
How are AI and IoT reshaping connected vehicles and revenue? In this session with AutoMobility Advisors, we break down real-world monetization, predictive analytics, and scaling beyond legacy systems. Practical takeaways for teams building what’s next 👇 https://t.co/2lO7upP8pU
AI delivers value where work actually happens — inside docs like invoices, contracts, and claims, where decisions get made. We structure and move that data fast so nothing stalls. How are you handling docs today?
https://t.co/aQca7OOTPy
Easter is all about fresh starts and renewal — something we love here at Devox! Wishing you a wonderful holiday filled with peace, joy, and new possibilities. May your holiday be filled with sweet moments and quality time with your loved ones!
Most inefficiencies live in how systems were built—focused on tracking and reporting instead of real-time decisions. That’s where AI slows down. We put real-world patterns into a research paper. Download it: https://t.co/MEokyxJf2z
AI-native ≠ adding AI on top.
It’s a full rebuild: clean real-time data, new workflows, and systems that evolve with the business.
AI becomes the core of execution — not a layer.
Full article:
https://t.co/Eeh5jRYCQo
#AINative#EnterpriseArchitecture#DigitalTransformation
The fastest AI wins come from systems thinking.
Tie decisions to measurable outcomes, connect data as events, ship governed use cases, and learn continuously.
That’s the Core AI Transformation Loop.
#AITransformation
More: https://t.co/ZFyPfWPsCi
Most AI projects in automotive fail for one simple reason:
They’re built on chaotic systems.
AI on messy data = expensive models with no real impact.
First build data pipelines.
Then deploy AI.
More details here 👇
https://t.co/5E8hf9g8Yx
Deploy predictive maintenance without stopping production.
Even on legacy equipment with limited sensors.
Custom PdM systems, engineered around your actual manufacturing environment.
Details: https://t.co/KAwJ0CCFy7