AI, Cloud & Data Platforms for Secure and High-Performing Chemical Manufacturing
Chemical manufacturing runs on precision, safety, and reliability. STX Next helps industry leaders modernize their operations.
From predictive maintenance and smart utilities to cloud-native manufacturing systems and AI-powered knowledge tools, we work within your existing environment to deliver scalable, secure solutions that support efficiency, sustainability, and long-term innovation.
Our Services
By integrating resilient cloud-native infrastructure with advanced predictive modeling, we turn fragmented operational data into a unified, high-performance system for chemical manufacturing enterprises.
1. Data Engineering & Industrial Analytics
Our cross-domain teams build reliable data foundations that unify operational, sensor, and enterprise data into secure, AI-ready platforms. These solutions support your advanced analytics, forecasting, and large-scale industrial workloads.
What it enables:
- Industrial data pipelines and feature engineering.
- Time-series data processing and analytics.
- Predictive maintenance and asset performance analytics.
- Real-time monitoring and reporting dashboards.
2. AI & Machine Learning Solutions
Apply machine learning and advanced analytics to real industrial challenges – from predicting equipment failures to extracting knowledge from vast document repositories.
What it enables:
- Predictive maintenance and Remaining Useful Life (RUL) models.
- Advanced feature engineering for industrial datasets.
- Retrieval-Augmented Generation (RAG) systems for internal knowledge.
- Applied R&D, including Digital Twin concepts and simulations.
3. Cloud & Infrastructure Modernization
Move from rigid, on-premises setups to secure, scalable cloud-native environments – without disrupting critical operations.
What it enables:
- Cloud migration (AWS, Azure).
- Infrastructure-as-code and DevOps automation.
- CI/CD pipelines for industrial and internal systems.
- Secure, resilient system architecture.
4. Custom Manufacturing Software
We design and develop internal tools tailored to manufacturing workflows – improving usability, reliability, and maintainability.
What it enables:
- Backend systems for manufacturing and testing environments.
- Internal operational and monitoring applications.
- System integration with existing industrial tooling.
- Long-term maintenance and continuous improvement.
Predictive Maintenance for the Chemical Manufacturing Sector
In chemical manufacturing, the most expensive sound is the silence of an unplanned shutdown.
Traditional fixed-schedule maintenance often leads to either unnecessary part replacements or worse – unexpected failures that halt production. Transform maintenance from a cost center into a strategic advantage with STX Next.
Our predictive maintenance solutions move your operations from reactive cycles to data-driven, condition-based strategies. By analyzing real-time sensor data and historical patterns, we identify the early warning signs of equipment fatigue long before they escalate into costly emergencies.
Custom AI Claims Accelerators
Eliminate claims bottlenecks without replacing your core systems
Insurance claims teams handling hundreds of thousands of cases per year are often slowed down by manual, document-heavy processes and rigid legacy platforms. STX Next’s Custom AI Claims Accelerators are production-ready, pattern-based solutions designed to remove operational bottlenecks while integrating seamlessly with your existing systems. Delivered in just 6-20 weeks, they allow you to shorten time-to-market and bring business value much faster than classic custom software development.
How Predictive Maintenance Drives Business Value
How AI Claims Accelerators optimize your processes
Downtime Reduction
Minimize unplanned outages by up to 50%. Our ML models detect anomalies in vibration, temperature, and pressure, allowing you to schedule repairs during planned windows rather than emergency stops.
Optimized Maintenance Spending
Reduce overall maintenance costs by up to 40%. Instead of following rigid calendars, you replace components only when they actually need it, cutting down on labor and spare parts waste.
Asset Life Extension
Extend the ROI of your high-value machinery. By identifying and resolving minor mechanical issues early, you prevent the compounding damage that leads to premature asset retirement.
Enhanced Operational Safety
Early failure detection significantly reduces the risk of hazardous leaks, fires, or mechanical breakages, ensuring a safer environment for your shop-floor personnel.
Precise Spare Parts Management
Transform your inventory from guesswork to precision. Forecast exactly which components are needed and when, reducing the capital tied up in excess stock.
Expert voice
Predictive Maintenance in Manufacturing: Benefits, Challenges, and How to Get Started
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Adam Krysztopa
Trusted By Leaders of the Chemical Manufacturing Industry
Predictive Maintenance for Large-Scale Chemical Operations
To address high maintenance costs and unexpected downtime, our team developed a predictive maintenance solution based on advanced feature engineering and machine learning. The system processes over 10 billion time-series records, enabling Remaining Useful Life predictions and early failure detection. This shift from fixed schedules to condition-based maintenance reduced costs, minimized downtime, and extended equipment lifespan – all supported by scalable analytics on Azure.
US
AI-Powered Knowledge Access for Industrial Enterprises
A RAG chatbot delivering fast, multilingual answers across global operations
A secure, multilingual Retrieval-Augmented Generation (RAG) system allows Linde’s global teams to search and query internal documentation using natural language. By combining document indexing, OCR, and large language models, the solution dramatically reduced information retrieval time while maintaining source traceability, security, and performance monitoring – critical for large, regulated industrial environments.
Germany
Challenges We Can Help You With
Chemical manufacturers often operate across fragmented systems – from sensors and utilities to maintenance logs and enterprise software.
We unify operational, time-series, and enterprise data into scalable platforms with standardized schemas, automated validation, and analytics-ready pipelines – creating a single source of truth for operations and decision-making.
Fixed maintenance schedules rarely reflect real equipment condition, leading to unnecessary costs or unexpected failures.
We build predictive maintenance solutions that analyze historical and real-time data to detect anomalies early, forecast failures, and optimize maintenance timing – reducing downtime and extending asset life.
On-premise systems and tightly coupled architectures make change risky, slow, and expensive.
We modernize systems through cloud migration, infrastructure-as-code, and DevOps automation – increasing resilience, scalability, and operational independence without disrupting production.
Critical operational knowledge often lives in thousands of PDFs, manuals, and procedures that are difficult to search and maintain.
We implement secure, AI-powered knowledge systems that allow teams to ask questions in natural language and get fast, cited answers across multilingual document repositories.
A Reliable Partner For The Chemical Manufacturing Sector
Even though we believe that our work speaks for itself, we are always grateful for words of appreciation from our clients.
Client
testimonial
What is most unique about STX Next is their commitment to Scrum and agile. Instead of just doing a project, they understand that every 2 weeks is a mini-project, and are committed to succeeding every sprint.
Their developers deliver more story points per sprint than other international contractors. Our project was completed on time and with more features than was required, due in a large part to STX Next.
Mercado Labs, US
Client
testimonial
The seamless integration of their expertise and commitment created a highly productive and positive working environment throughout the project. Their team is skilled, responsive, and easy to work with. They adapt quickly to feedback and stay on top of deadlines.
If you're looking for a reliable partner who delivers quality results, they are a great choice.
BSI, UK
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FAQs
What types of chemical manufacturing companies does STX Next work with?
We work with large industrial enterprises, technology providers, and manufacturers operating complex, data-intensive environments – including chemicals, industrial gases, utilities, and advanced manufacturing.
Can you integrate with existing industrial and enterprise systems?
Yes. We design solutions that integrate with existing databases, time-series platforms, internal tools, and cloud environments, minimizing disruption and protecting prior investments.
Do you build predictive maintenance systems from scratch?
Yes. We handle the full lifecycle – from data engineering and feature engineering to model development, validation, and production deployment.
How do you ensure data security and compliance?
We design secure architectures using cloud-native services, access controls, monitoring, and best practices aligned with enterprise and regulatory requirements.
What cloud platforms do you support?
We primarily work with Azure and AWS, selecting services based on operational needs, scalability, and security requirements.
Can you modernize legacy manufacturing software without stopping operations?
Yes. We focus on incremental modernization, parallel environments, and careful migration strategies to avoid operational downtime.
How does STX Next approach AI in regulated industrial environments?
We prioritize transparency, explainability, validation, and monitoring – ensuring AI systems are reliable, auditable, and aligned with industrial standards.
Why choose STX Next as a long-term technology partner?
We combine strong Python expertise, deep experience in data and AI, and a pragmatic, engineering-driven approach. Our teams focus on solving real operational problems – not just delivering technology.
