Driving leasing's digital future.

We create sustainable digital touchpoints and AI-powered data products with captivating customer experience and seamless product operations.

Product Engineering

Powerful tech works. Just like our team.

In Product Engineering, we design innovative digital solutions for the Deutsche Leasing AG, driving progress and impact. By harnessing cutting-edge cloud technologies and engineering expertise, we empower Deutsche Leasing Group to further strengthen its market position and growth. From concept to launch, our focus on user experience, reliability and security ensures every product is a robust and radiant success.

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Use Cases

Rockets are cool. Just like the solutions we build.

View AllDigital TouchpointData and AI

Digital Touchpoint
S-Mobilitätsportal
Empowering fleet customers
S-Mobilitätsportal
The Sparkassen Mobilitätsportal (SMP) offers small fleet customers an easier way to configure vehicles, calculate prices and create leasing contracts independently and efficiently.
vent.io provides the SMP frontend, consisting of two key components:
Frontend: The user interface designed for an intuitive experience.
Backend (Backend-for-Frontend, BFF): The system component that connects to external services to preprocess and simplify data for the frontend.
This architecture delivers an efficient and user-centric solution to meet the evolving needs of modern fleet customers.
Tech stack extract:
Frontend & Mobile Technologies: Typescript, React, Next.js
Backend Technologies: Java, Spring Boot
Infrastructure & Developer Experience: Container Apps, Azure Insights
Data and AI
Venzio
Your Intelligent Leasing Assistant
Venzio
Born out of research and development, Venzio is an GenAI Chatbot powered by OpenAI's model, operating out of the Azure Cloud. Developed as part of a feasibility study, Venzio is tailored specifically for Deutsche Leasing, leveraging a language model that has been adjusted via prompts to provide precise and insightful responses based on feedback from questionnaires.
Customized Intelligence: Venzio's core model is fine-tuned through prompts with company specific data, ensuring highly relevant and accurate interactions.
Efficient Data Analysis: Our robust backend enhances Venzio's analytical capabilities by efficiently analyzing questionnaire data, offering insights and actionable recommendations.
Enterprise-Specific KPI Calculations: Venzio includes functionalities for extracting enterprise-specific KPIs such as equity and dept ratio providing valuable financial insights.
Secure Deployment: Venzio is securely rolled out within our infrastructure, guaranteeing data privacy and compliance with industry standards.
User-Friendly Interface: Designed with a sleek and intuitive frontend, Venzio ensures a seamless user experience, making it easy for our customers to engage and get the information they need.
Experience the future of customer interaction with Venzio, where cutting-edge AI meets tailored leasing solutions, and data analysis is more efficient than ever. Stay tuned for further development!
Tech stack extract:
Frontend & Mobile Technologies: Typescript, React
Backend Technologies: Python, Azure OpenAI
Infrastructure & Developer Experience: Azure Container Apps
Data and AI
Company Profiles
Optimizing customer acquisition
Company Profiles
The “Company Profiles” tool is an innovative acquisition tool that bundles important company data and effectively supports SuM's (Sparkassen und Mittelstand) sales department in customer acquisition. With comprehensive dashboards and customized evaluations, it helps to quickly gather relevant information and make strategic decisions.
Our “Company Profiles” tool automates the collection and preparation of company information. By crawling company websites and the company register, it extracts key balance sheet figures, annual financial statements and important company data. These are processed into a clear brief description of the company and a detailed presentation of locations and contact persons. The tool also evaluates the company's annual financial statements and sustainability reports, if available, and filters topics to create summaries based on key points. This provides sales staff with all relevant information at a glance - quickly and efficiently.
Tech stack extract:
Backend Technologies: Python
Data Technologies: Pandas, Azure OpenAI
Infrastructure & Developer Experience: Azure Cloud, Docker, Container Apps
Digital Touchpoint
TCO
TCO Comparison Calculator for Vehicle Fleets
TCO
The TCO Comparison Calculator is designed to help Deutsche Leasing’s customers transform their fleets towards e-mobility, meeting CO2 goals and reducing future costs.
By calculating the total cost of ownership for various car models, including both combustion and electric vehicles, the app provides a comprehensive comparison tailored to individual conditions and fleet structures. This eliminates the need for general assumptions, reducing uncertainty and investment risk.
In addition to the core comparison feature, the application recommends comparable and suitable electric car models, as well as fuel and charging card tariffs that fit the fleet structure and planned charging behavior.
Tech stack extract:
Frontend & Mobile Technologies: Typescript, React
Backend Technologies: Python
Data Technologies: Pandas, Azure OpenAI, Postgres SQL
Infrastructure & Developer Experience: Terraform, Azure Cloud, Docker, Container Apps, AKS, Github, Github Actions, Github Copilot, Grafana, Azure Insights, Log Analytics Workspace, OpenTelemetry, SonarCloud, Snyk, Dependabot
Data and AI
Mobility Maintenance Cost Forecast
Enhancing maintenance planning
Mobility Maintenance Cost Forecast
The “Mobility Maintenance Cost Forecast” project aims to develop data-based forecasts for maintenance costs in order to enable more precise calculations. Through these forecasts, maintenance contracts can be offered with customized conditions, leading to a profitable maintenance contract business.
The “Mobility Maintenance Cost Forecast” project uses modern data science methods to provide a well-founded and precise cost calculation for maintenance work. Different model variants, running times and mileages are taken into account. One of the biggest challenges is the large amount of data, which is unevenly distributed depending on the vehicle type and requires efficient processing. The aim is to make reliable predictions that enable maintenance contracts to be tailored precisely to the needs of the vehicles and to optimize the maintenance services business.
Tech stack extract:
Backend Technologies: Python
Data Technologies: Databricks, Spark, Pandas
Infrastructure & Developer Experience: Azure Cloud
Data and AI
Balance sheet figures for risk management
Streamlining credit assessment
Balance sheet figures for risk management
The project “Balance sheet figures for risk management” optimizes the credit assessment process for loans in the medium credit volume range. The aim is to support the manual scoring assessment by risk analysts and thus both shorten the processing time and increase efficiency and quality.
As part of the project, a semi-automated solution is being developed to support risk analysts in calculating credit scores. The process starts with the upload of the financial statements, which are automatically checked for relevant balance sheet ratios. An advanced large language model extracts the necessary data and transfers it to a user-friendly input screen, which the analyst can customize as required. After the final check, the key figures are calculated and used for scoring. The result is saved as a PDF to facilitate further processing. This procedure not only reduces the workload but also ensures greater accuracy.
Tech stack extract:
Frontend & Mobile Technologies: Typescript
Backend Technologies: Python
Data Technologies: Pandas, Azure OpenAI
Infrastructure & Developer Experience: Azure Cloud, Docker, Container Apps

Guidelines

Our principles & values.

We are innovative!

We foster creativity and push technological boundaries to develop forward-thinking solutions that drive progress and create value.

We stand for quality!

We are committed to delivering exceptional results, driven by our dedication and relentless pursuit of excellence.

We are authentic!

We communicate openly and honestly, staying true to who we are while leading by example and inspiring those around us.

We are one team!

We trust, support, and empower each other, working collaboratively to achieve shared goals and celebrate success together.

We are bold!

We take ownership, challenge the status quo, and embrace new opportunities with confidence and courage, driving productivity and meaningful results.

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vent.io Mitarbeiter stehen auf der Dachterasse

vent.io Mitarbeiter in einem Meeting Raum

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Tech Stack

We navigate the digital cosmos with our space-grade tech stack.

Frontend & Mobile Technologies

Typescript, React, Remix, Next.js, Dart, Flutter, Swift, Java

Backend Technologies

Java, Kotlin, Spring, Node.js, Python, Flask

Data Technologies

Databricks, Azure OpenAI, Ray, Spark, Pandas, Microsoft Fabric

Infrastructure & Developer Experience

Terraform, Azure Cloud, Docker, Container Apps, AKS, Github, Github Actions, Github Copilot, Grafana, Azure Insights, Log Analytics Workspace, OpenTelemetry, Visual Studio Code, SonarCloud, Snyk, Dependabot, IntelliJ, JIRA, Airfocus, Miro, WSL, Windows 11, MacBook

Security & Compliance

Microsoft Defender, Intune, Entra-ID, Microsoft Security, Microsoft Purview, Dataguard, GDPR, ISO/IEC 27001:2022

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Product Engineering Leadership

Innovative & technology-driven minds behind Product Engineering division: Georgios Gkekas and Nhut Ajat Hong

Georgios Gkekas – Chief Technology Officer (CTO) 

Georgios Gkekas, the technical visionary at vent.io, leads the technical part of Product Engineering, including Data Science, Data Engineering, Site Reliability Engineering, and Software Engineering. He emphasizes resilient and distributed software architectures, forming in this way the digital foundation for Deutsche Leasing’s AI solutions and portals.

Georgios holds a Computer Science degree from a technical university in Greece and a M.Sc. in Information Networking from Carnegie Mellon University. After graduation, he started working as software engineer and architecting, where he built scalable platforms and products for the financial service industry. Before becoming CTO at vent.io, he was a Data Architect at Deutsche Leasing for 3 years.

Nhut Ajat Hong – Managing Director 

Ajat spearheads vent.io’s Product Engineering division and its strategy, guiding the digital transformation journey for Deutsche Leasing. Central to his leadership is the development of the whole Product Engineering department’s capabilities, which covers the whole spectrum of Product and Engineering disciplines. Currently he also serves as the interim team lead of the ProductX part of the department.

Ajat studied Business Information Systems with a specialization in Enterprise Architecture, a focus that has consistently influenced his professional journey. After graduating, he worked in consulting, advising clients on Enterprise Architecture Management in digital transformation projects. Following eight years in consulting, Ajat joined Deutsche Leasing as an Enterprise Architect in 2018 and was appointed Managing Director in 2021.

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Our Culture

Our passion is the digitalization of industries in Germany and building a portfolio of companies focusing on reliable and innovative solutions to relevant problems in the B2B asset industry. We bring together early stage B2B startups with potential customers while also supporting them with funding and a profound expertise in building data-driven solutions.

We bring together early stage B2B startups with potential customers while also supporting them with funding and a profound expertise in building data-driven solutions.