STX Next

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Overview

$50,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

250 - 999

Employees

2005

Year Founded

ABOUT STX NEXT

AI and Data Solutions built on Python heritage

STX Next is the largest digital engineering partner in Europe with a focus on Python, specializing in Data, AI, and Cloud solutions that enable organizations to derive business value from their data. With delivery centers located in Poland and Mexico, we blend extensive technical skills with a flexible nearshore approach that clients in various sectors—including Industrial, Financial Services, Technology, Energy & Utilities, and Healthcare—trust. Our teams create and implement modern data platforms (such as Snowflake, Databricks, Apache Iceberg), AI-driven applications and agents, and cost-effective cloud infrastructures on AWS and Azure, all rooted in practical delivery and measurable returns on investment. Our nearly 20-year strong foundation in Python has facilitated our expansion, allowing us to connect software engineering with data science and AI advancements. As an ISO-certified AWS partner, we uphold stringent data security and compliance standards, assisting clients in scaling through automation, intelligent workflows, and AI capabilities. At STX Next, we focus on developing technology that is effective in real-world applications, transforming complex systems into straightforward, scalable, and impactful solutions. Contact us today!

Tech Stack

PythonC#Django.NET

Languages Spoken

EnglishSpanishGermanPolish

HIGHLIGHTS

$50,000+

Min Project Size

$50 - $99/hr

Avg Hourly Rate

250 - 999

Employees

2005

Year Founded

Services

Focus

Industries

Clients

Services Provided

23% Custom Web Application Development

10% API Development & Integration

20% Business Intelligence (BI) Dashboard Development

13% Data Strategy Consulting

17% AI Strategy & Roadmap Consulting

17% Generative AI

About the Team

OUR STORY

Our Journey STX Next was established in 2005 and evolved from a Python-focused software firm into a worldwide technology partner for companies in finance, technology, manufacturing, energy, adtech, and healthcare. As we broadened our offerings to encompass AI and Machine Learning, Data Engineering, Cloud services, and Product Design, our global presence also grew. Currently, with over 500 specialists and more than 1,000 completed projects, we assist clients in the US, UK, DACH region, Poland, and Benelux.

TEAM PHOTOS

Portfolio

Wunderman Thompson: Transforming Brand with AI

Wunderman Thompson

Wunderman Thompson (currently known as VML), a rapidly growing company focused on leveraging data, required a machine learning solution to assess the quality of their assets more efficiently on a larger scale. Their current method of data collection was a major hindrance, causing delays and necessitating a revamp of their system architecture. In response, they created The WPP Open Brand Guardian, an AI platform designed to integrate seamlessly into their existing production workflow to facilitate brand governance. They were in search of a dependable partner to help in its development. To meet the client's requirements, we established a sophisticated architecture that enabled the reuse and large-scale execution of existing models and algorithms. Our comprehensive work included: 01 Redesigned Architecture: Our team restructured the current architecture by implementing ML-driven microservices with clearly defined responsibilities. This modification allowed for easier auto-scaling through an independent set of computing units in Kubernetes. 02 Enhanced AI Microservices: We proposed a messaging system that enables multiple Celery workers to run the majority of Machine Learning and computer vision tasks in parallel. 03 Image Processing Pipelines: We tackled the issue of recognizing undefined, custom image elements (like logos, fonts, and specific objects) and developed a framework for creating new training datasets through data augmentation and synthetic data methods. 04 WPP Open Brand Guardian: Our team built an AI-based platform that ensures brand governance, adheres to legal and industry standards, promotes inclusivity, and maintains creative excellence. It evaluates creative assets and delivers valuable insights quickly.

Podimo: Transforming search with Machine Learning

Podimo

Podimo, a leading Danish company in the podcast and audiobook sector, aimed to transform its search functionality to better cater to its varied user audience. With an emphasis on rewarding content creators and ensuring a smooth listening experience, Podimo sought to improve the precision and relevance of search results based on user preferences. However, the existing search system struggled to meet user expectations, often yielding irrelevant results due to its limited ability to comprehend queries and the semantics of content. To tackle this issue, STX Next suggested implementing advanced approaches such as Learning to Rank (LTR), semantic search, and conversational search to enhance the user experience. Additionally, we chose to introduce Machine Learning models to analyze user interactions, interpret their intent, and enable a conversational search interface. By merging Machine Learning with semantic search models, our dedicated team proposed new features tailored to customer needs, including: - A Machine Learning model: A dynamic model trained on user interactions to adjust podcast and audiobook rankings, ensuring search results align with user preferences. - A semantic search model: An advanced language model that understands the context and semantics of user queries, allowing for content discovery that goes beyond mere keyword matching. - Conversational search: The introduction of a conversational search assistant to facilitate user interactions with the search engine and gather feedback for continuous improvements. - Combined search results: Integration of both lexical and semantic search results through an ML model to refine results for better accuracy and relevance. These enhancements brought substantial advantages to both Podimo and its users.

appliedAI’s Use Case Management Tool

appliedAI

Responding to the EU AI Act Regulations As the regulatory environment in the European Union transformed with the implementation of the EU AI Act, businesses sought effective strategies to manage their AI applications to ensure compliance and fully leverage their tools. Understanding the importance of this challenge, appliedAI collaborated with STX Next to provide companies worldwide with a competitive advantage through an innovative Use Case Management Tool. This solution acts as a strategic resource, enabling not only risk assessment but also optimization of AI portfolios and advancement of AI projects. Compliance, Transparency, and Data-Driven Planning To tackle the potential issues and uncertainties surrounding the EU AI Act, our all-encompassing product offers businesses a clear view of their AI applications. Here’s how our solution empowers organizations: 01 Comprehensive Compliance Monitoring Our platform features a centralized dashboard that provides a complete overview of all AI applications within your organization, ensuring compliance with the EU AI Act. It simplifies tracking, auditing, and reporting, assisting legal and compliance teams. 02 Data-Informed Decision-Making Utilizing extensive research and innovative design, our platform includes powerful data analytics tools. These tools equip companies with valuable insights to optimize AI strategies and improve return on investment. 03 Strengthening European Industry Leadership Targeted at AI and legal departments, our platform promotes innovation while ensuring regulatory compliance, positioning the European industry as a frontrunner in AI on the global stage.

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