We transform and operate your data and AI stacks, offering comprehensive end-to-end services. From cloud data warehouses and lakehouse architectures to production-ready AI agents. Our services include strategic consulting, data engineering and modeling, platform operations, and AI implementation. Governance, analytical methods, and 24/7 support are, of course, all part of the package.
We provide you with pragmatic, outcome-driven data and AI strategies that align your business priorities, regulatory expectations, and business roadmaps. We define the target operating model, the funded roadmap, and the initial initiatives—from data strategy through AI integration and pilots to proof-of-concept and proof-of-value. We also optimize your data preparation for state-of-the-art ESG reporting and integrate AI into your business processes.
The Challenge
Two major German banks were faced with the task of updating their digital transformation programs. They needed a strategy for leveraging Snowflake, decommissioning legacy systems, and meeting compliance requirements.
The solution
We offered comprehensive consulting services, developed strategic roadmaps, and planned Snowflake use cases. We supported investment decisions and ensured compliance with regulatory requirements.
Client
: Two leading banks in the DACH region
We are experts in modern data platforms, high-performance and scalable solutions, as well as data management and analysis. As specialists in cloud data warehouses (including Snowflake, Azure, and Google Cloud), lakehouse architectures (including Databricks), and modern data stacks, we build future-proof data infrastructures. We combine technical excellence with smart solutions for EU-wide hybrid environments. This includes streaming, real-time processing, and FinOps cost controls.
The Challenge
Nonprofit organizations face the challenge of effectively managing their data to understand and engage with donors. They need a solution that enables them to generate reports and analyses and gain valuable insights.
The solution
We develop customized data platforms tailored to the specific needs of non-profits. Our platforms leverage advanced technologies such as Snowflake, DataFactory, Python, and Power BI to create an integrated data hub that enables an optimized customer journey and effective marketing.
Client
: A major humanitarian nonprofit organization
We establish ownership, stewardship, and discoverability through operational data catalogs, lineage, and data quality SLAs. Our governance and catalog services significantly reduce analysis time and improve audit readiness. Our Data Architecture Advisory service delivers target-state architectures, integration patterns, and migration lanes—with a clear focus on balancing cost, resilience, and compliance.
The Challenge
The bank needed to comply with the GDPR by automatically deleting personal data from its databases to prevent data breaches.
The Solution
An API-based privacy broker service solution has been implemented to act as an intermediary for data deletion. This solution enables the automatic removal of data in accordance with the GDPR and supports manual deletion processes carried out by bank staff.
Client
Offers a wide range of financial products, including loans, cards, insurance, and deposit accounts
Our data engineering services include technical consulting, implementation services, and the provision of tools and infrastructure. Our expertise also includes database development for cloud and on-premises environments (Oracle, SQL Server, PostgreSQL), ranging from data modeling to performance tuning. We specialize in modernizing legacy systems and use AI-powered automation to optimize data processing and analysis. This enables you to overcome complex data challenges and future-proof your data architecture.
The Challenge
Our client faced the challenge of operating a third-party bank following a merger. Our task was to migrate all of the third-party bank’s core banking data into our client’s own core banking system and complete this process by January 1—in just a few days.
The Solution
We created an optimized data mapping between the core banking systems. The data migration went smoothly, and after the go-live, we ensured business continuity.
customer
A German bank with a focus on investment portfolios.
We offer ETL/ELT standardization through pattern libraries, templates, and governance, ensuring consistent transformations with significantly reduced maintenance efforts. Our APIs and integrations—featuring governed interfaces, schema versioning, and lifecycle management—ensure that data is securely available to applications and partners. Our cloud migration expertise also enhances the agility and scalability of your IT infrastructure.
The Challenge
The client needed software that would enable car dealers to sell insurance products to their end customers. To this end, it should be possible to calculate and offer insurance policies from various insurance companies at the dealership’s point of sale.
The Solution
We have developed a Java backend application that orchestrates insurance APIs and enables data mapping via a graphical user interface. Thanks to the development of this application, which is integrated with the necessary APIs from insurance companies, car dealers can expand their product portfolio by offering their end customers insurance policies from various insurance companies through their point-of-sale applications.
Client
, an IT service provider specializing in the development and support of software solutions specifically for the automotive industry
Make data-driven decisions with our modern reporting solutions and self-service BI tools. From management dashboards to data visualization, we offer IT solutions that enable users with little prior knowledge to create reports and analyses on their own. Companies using Sage b7 ERP benefit from Sage BI and Microsoft Power BI. These tools transform ERP data into real-time insights through dashboards and automated reports. This is complemented by AI-powered analytics, anomaly detection, automation, and natural-language analysis. All of this is based on trustworthy, quality-assured business data, ensuring governance in every form.
The Challenge
A major sports league needed a central data platform for real-time analytics that would serve clubs, fans, and the media. The complexity lies in selecting the tech stack, data migration, integration with the web and APIs, and replacing legacy systems.
The Solution
We are implementing a robust data hub in the Azure cloud that uses Microsoft Fabric, Data Factory, and Power BI. This solution enables seamless data flows and analytics that deliver value to all stakeholders.
Client
: A leading national sports league
We optimize operations and MLOps through a holistic approach that encompasses DevOps & Managed Cloud Services, 24/7 data operations, change management, cost control, and advanced data quality and observability solutions. We rely on proven cybersecurity and Data Loss Prevention (DLP) best practices to ensure the protection of your data and systems. Through comprehensive model lifecycle management and database administration, we ensure the performance and reliability of your data models and infrastructures.
The Challenge
The requirement was to provide account-related information based on transaction data sufficient for analyzing an individual's lifestyle and preferences, for example, to create insurance offers.
The solution
We have developed a Java API for data intelligence that uses machine learning to analyze banking information for personalized offers. It helps insurance companies and financial institutions with quote generation and credit checks.
customer
Germany's leading provider of open banking and open finance solutions
The Challenge
The challenge was that a bank wanted to migrate its reporting and business analytics from SAS to Python. An internal implementation was almost impossible due to high effort estimates and resource constraints.
The solution
We combined our LegacyLift tool with our IT resources and a small banking team to achieve significant savings. For low-complexity projects, we achieved a 60% improvement, for medium-complexity projects 50%, and for high-complexity projects 40%. We also achieved a 20% improvement in SAS-generated ETL processes and 50% overall savings compared to a fully human-led code migration.
customer
A well-known banking group.
The Challenge
: Car dealerships had to connect customers quickly and directly with insurance providers when purchasing a new car, while taking into account various offers and products and correctly handling the insurers’ non-standardized, frequently changing interfaces.
The solution
We implemented the Amonga solution, which acts as an intermediary between the POS application of car dealerships and insurance companies. Amonga enables flexible customer data mapping and simple GUI-based maintenance of the mappings to the insurers. Hosted and managed by Specific-Group, the application processes approximately 60,000 requests to insurers weekly.
Client
The client is in the automotive industry.
We plan and execute complex migration and optimization projects. These range from AI-assisted code migration to database upgrades and platform consolidation. AI-assisted code migration enables guided refactoring of legacy SQL/PL-SQL to modern platforms. Database migrations for Oracle/SQL Server estates—including license optimization, workload offloading, and right-sizing to reduce TCO—are also part of our service offering. No matter what the project is, our approach combines automation with human expertise—taking your business goals to the next level.
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Data engineering refers to the technical work of transforming raw source data into reliable, analyzable pipelines. Without this foundation, BI dashboards provide outdated figures and AI models are trained on flawed data. Data engineers design data architectures, implement ETL processes, and integrate cloud platforms such as Snowflake, Azure, or Google BigQuery. The effort involved varies greatly depending on the system landscape: A company with dozens of source systems and real-time requirements needs a fundamentally different platform than one with just a few structured data sources.
A data warehouse stores processed data for defined reporting and analytical applications, is optimized for query speed, and requires predefined data models. A data lake accommodates all data types, including unstructured data, and is suitable for exploratory analysis and machine learning. The catch: without careful data management, the lake quickly turns into a data swamp. The data lakehouse combines flexible data storage with high-performance queries on a shared storage layer. Databricks and Snowflake are the most widely used platforms that implement this model in production today.
AI agents perform tasks autonomously: they access data, call upon external services, and act based on defined goals. The most common reason for failed AI projects is an inadequate data set. The model itself is rarely the problem. A proven architecture is RAG (Retrieval-Augmented Generation), in which the language model accesses a company-specific knowledge system rather than relying solely on general training. Proof-of-concept phases help validate the actual added value before a rollout and refine the use case.
The Specific Group supports companies from the initial data strategy workshop through to ongoing platform operations. Our core services include cloud data platforms on Snowflake, Databricks, and Azure; data engineering; data modeling; governance; and AI implementations, including MLOps. We specialize in complex migration projects and hybrid EU environments, where regulatory requirements such as DORA or Solvency II influence architectural decisions. In addition, we develop our own products: Amonga for API integration and Ozgar.ai for AI-powered analysis of legacy systems.
Data governance is the framework that governs who uses which data under what conditions and who is responsible for it. Without clear responsibilities (data ownership, stewardship) and operational data catalogs, quality issues arise that only become apparent in inaccurate dashboards or poor AI model results. At Specific Group, governance is an integral part of every data architecture. In projects with financial institutions or insurers, we integrate compliance requirements such as DORA or Solvency II directly into architectural decisions.