STX Next Technology Stack
Your business goals define the solution, not the other way around. STX Next works directly within your current stack while designing for the technologies you plan to adopt.
Backed by 20 years of engineering experience, we bring AI, cloud, and data expertise to complex production environments.
Years
of Python and data engineering experience
technical projects
delivered globally
engineers, data scientists, and cloud architects
Advanced Partner
with verified infrastructure expertise
& TISAX Certified
for enterprise security
Core frameworks & tools
We match technology directly to your infrastructure, data needs, and team capabilities - giving you a production-ready, easily managed environment with zero unnecessary lock-in.
AI, ML & intelligent automation
- Amazon Bedrock & AgentCore. A secure, managed gateway to foundation models. It can be used alongside the AgentCore runtime to give you AI agents that connect securely to your enterprise data.
- Azure AI Foundry & Copilot Studio. Microsoft’s enterprise stack for building and managing AI applications and agents, built for organizations running directly on Azure and Office 365.
- n8n. A workflow automation platform. As an official partner, we help you handle high-volume connected tasks while keeping the setup aligned with your security and procurement requirements.
- Frontier models & AI engineering tools: Production integration of leading commercial LLMs (OpenAI, Anthropic Claude, Google Gemini) paired with agentic developer tools (Cursor, Claude Code, GitHub Copilot) to speed up software delivery and code intelligence.
Our AI and ML stack includes: LangChain, LangGraph, PyTorch, TensorFlow, SKLearn, XGBoost, Polars, YOLO, ResNet, DenseNet, OpenCV, and MLflow.
Read more about our AI development services
Data engineering
- Snowflake. Our Snowflake consulting services help you build a governed, cost-efficient cloud data warehouse with independently scalable storage and compute, cross-cloud flexibility, and workload isolation.
- Databricks. A data lakehouse platform. Your engineering teams can use it alongside Unity Catalog to run complex analytics, governed data platforms, and heavy machine learning workloads.
- Microsoft Fabric & Azure Synapse. A unified data and analytics platform for Microsoft-first environments. Deployed alongside OneLake and dbt to combine data engineering, lakehouses, and Power BI reporting into a single governed system.
- Amazon Redshift. Fully managed, petabyte-scale cloud data warehouses. Ideal for large-scale analytics and BI workloads that process high-volume data on AWS infrastructure.
- Apache IcebergApache Iceberg & Delta Lake. Open table formats for managing large analytical datasets. We use them to improve query performance and make data pipelines easier to maintain.
- Orchestration & Infrastructure. We use Apache Airflow to schedule and monitor complex data pipelines, relying on relational and time-series foundations like PostgreSQL and TimescaleDB to handle structured transactional data.
For streaming and data-intensive systems, our stack can include: Scala, Kafka, Flink, Kinesis, Fivetran, Great Expectations, Google Cloud Pub/Sub, Bigtable, Elasticsearch, PySpark, Plotly, and Streamlit.
Read more about our data engineering services
Backend
- Python:Python: Our core language since 2005, providing the foundation for advanced data science, custom machine learning pipelines, and AI integration work.
- Frameworks & ecosystem: Django, Django REST Framework, FastAPI, Flask, Celery/RQ, SQLAlchemy, Pydantic, LangChain/LangGraph, and pytest.
- Node.js & TypeScript: An event-driven backend environment. It allows your data-intensive applications to handle large numbers of concurrent user connections, while TypeScript adds stronger safety across the codebase.
- Frameworks & ecosystem: NestJS, Express/Fastify, tRPC, OpenAPI-first APIs, BullMQ/queues, and Prisma/Drizzle.
- Databases & messaging infrastructure: We implement high-availability architectures using PostgreSQL, Redis, Elasticsearch/OpenSearch, RabbitMQ, Kafka, and cloud-native queues.
- Observability & quality: OpenTelemetry, Sentry, structured logging, contract testing, API test automation, and strict CI quality gates help you catch failures early and gain visibility into production systems.
- Enterprise integration & client alignment: We deploy .NET / C# and Java / Spring Boot when critical business operations demand legacy modernization, ecosystem integration, or direct alignment with a client's internal tech stack to support stability and uptime.
Frontend & mobile development
- React + TypeScript: Our default web development services stack for complex product interfaces, dashboards, SaaS platforms, internal tools, and AI-enabled applications.
- Next.js / React Router / Vite / TanStack Ecosystem: Used depending on product shape for SEO/SSR, app-shell dashboards, full-stack TypeScript, and routing or data-loading needs.
- Design systems & UI delivery: Built via Tailwind CSS, shadcn/ui, and Storybook using component libraries, accessibility checks, and design-token-driven implementation.
- State, data & UI tooling: Powered by TanStack Query, TanStack Table, Redux Toolkit, or Zustand where needed, with form validation via Zod and React Hook Form.
- Testing & quality assurance: Playwright and Cypress for web E2E and component testing, with Vitest, Jest, and Testing Library for unit and integration testing.
- React Native + Expo: Deployed for cross-platform mobile development services where shared product velocity matters, with access to native platform capabilities.
- Enterprise integration & client alignment: We deploy Angular for structured enterprise applications requiring long-term consistency and large-team governance, or Vue / Nuxt as a mature, pragmatic delivery option to align directly with a client's existing stack.
Cloud & infrastructure
- Cloud architecture & modernization. AWS, Microsoft Azure, and Google Cloud. As an AWS Advanced Tier Services Partner (eligible for the AWS MAP program) and a member of the Microsoft AI Cloud Partner Program, we help organizations migrate, modernize, and optimize cloud environments. Your existing infrastructure can also be assessed for security, governance, high availability, and disaster recovery.
- Containerization & orchestration. Kubernetes is our primary orchestration platform for deploying and managing containerized applications across cloud environments. Depending on the workload, Amazon ECS, Google Cloud Run, and serverless services such as AWS Lambda, Azure Functions, and Google Cloud Functions can also be used.
- Infrastructure as code & automation. Your infrastructure can be provisioned and managed using Terraform, OpenTofu, and AWS CloudFormation, with CI/CD pipelines powered by GitHub Actions and GitLab CI.
- Sovereign & regional cloud. CloudFerro, OVHcloud, and STACKIT. European cloud providers are available when your projects require strict data residency, digital sovereignty, or regional compliance.
- Observability & FinOps. We implement monitoring, logging, and alerting with Prometheus, Grafana, Datadog, OpenSearch, and AWS CloudTrail. FinOps practices can also help you optimize cloud costs and resource utilization.
Read more about our Cloud migration services
Technology partners and platforms
Work with a team backed by partnerships with global technology leaders.
See our case studies
27% higher search rankings and 3.5% more conversions
We built context-aware AI models using Elasticsearch and Python to rank search results by user intent. This moved popular and relevant shows straight to the top of the list and increased successful search conversions, helping Podimo overcome rigid search filters and poor content discovery.
Near-zero time spent on manual file reconciliation
STX Next consolidated separate ERP, CRM, and spreadsheet files into a single, automated Microsoft Fabric platform on Azure. By using dbt to clean and transform data pipelines, we completely eliminated manual spreadsheet reconciliation and helped Agro-Sieć overcome critical data fragmentation and manual reporting challenges.
Technical alignment:
Matching tech to business outcomes
Every recommendation is built for your system's requirements and proven in real production environments.
Going beyond the code
Hidden technical debt slows engineering teams down. STX Next brings AI tools, security checks, and design guidance into the development workflow to reduce delays and improve reliability.
AI-augmented software engineering
Our AI-augmented software development services combine agentic coding tools including Claude Code, Cursor, and GitHub Copilot with established engineering workflows. AI-generated code changes go through static analysis, custom linting rules, and security checks before human review to maintain repository standards.
GenAI knowledge isolation
Squirro can be deployed to index unstructured internal documents into isolated search clusters. Your team accesses company knowledge through a private UI, keeping your proprietary data separate from public LLM training sets.
Repository & pipeline analytics
Automated code analysis tools can be connected to your repositories. The system tracks commit history and development patterns to extract metrics, identify code hotspots and track technical debt across your projects.
Product design
Our product design services connect user needs and business goals with development-ready solutions. Through UX and UI design, user research, product audits, usability testing, and implementation guidance, your team can deliver consistent, intuitive products without a disconnect between design and development.
Our design stack is built on Figma (including Figma Make) and Adobe CC. We also leverage Claude Design for creating slides, landing pages, and prototypes, Google Gemini for rapid prototyping, and Cursor for production design.
Security, governance & compliance alignment
Security and compliance are built into the code and infrastructure layer. These controls help you protect enterprise data and provide the technical evidence required during security and compliance reviews.
Global compliance
Validate that our development workflow, data handling, and code pipelines meet strict global security requirements.
Infrastructure isolation
Defined network boundaries on cloud platforms with options to connect to local sovereign networks.
Enterprise AI guardrails
Your proprietary corporate prompts and data remain isolated from public models or consumer AI tools.
FAQs
How do you choose the right technology stack for my project?
There is no one-size-fits-all stack. Technology choices depend entirely on your existing infrastructure, data velocity, and team skillset. We prioritize technologies your internal team can manage the environment without vendor lock-in.
Can you work within our existing tech stack, or do we need to migrate first?
We assess whether your current setup can support the planned solution. Migration is only recommended when your current setup genuinely can't support the outcome you need.
Do you require us to standardize on one cloud provider?
No. Your solution can be built across AWS, Microsoft Azure, and Google Cloud, and we also support sovereign and regional cloud environments like CloudFerro and STACKIT where data residency rules require it. The provider choice follows your compliance and infrastructure needs, not the other way around.
Can you integrate with our legacy systems?
Yes. Technologies such as .NET, Java, and Scala are used specifically for cases where critical business operations demand maximum uptime and architectural stability, as is often the case with legacy enterprise systems. New AI and data pipelines get connected to what's already running, not built to replace it outright.
How do you handle data security when using cloud-based AI services like Amazon Bedrock?
We keep company data within the approved cloud and network environment, using private endpoints, access controls and isolated data stores where required.
