CIGen.io

Objective

A Swiss startup sought to develop a location-based social platform that helps musicians connect, manage rehearsals, and organize performances. The goal was to create an intuitive, feature-rich mobile app that simplifies networking and administrative tasks for artists and band managers.

Challenge & collaboration goals

The platform needed to match musicians based on location, instrument, and preferences, facilitate content sharing, and provide integrated communication and payment solutions. The challenge was to build a seamless, cross-platform application that enhances collaboration while maintaining high performance.

Tech stack

• Mobile development: Flutter, Dart
• Backend & database: .NET, MSSQL, Apache Hive
• Cloud & authentication: Firebase, JWT Auth, Google Auth
• Integrations: YouTube API, Stripe, MapBox
• Notifications & messaging: FCM Notifications, GetStream API

Results

• Cross-platform mobile app developed using Flutter, ensuring native UI performance on iOS and Android.
• Advanced networking features, enabling musicians to search by location, instrument, and skill level.
• Seamless communication tools, including real-time single and group chats.
• Integrated content sharing, allowing musicians to upload and showcase their performances via YouTube.
• In-app payment system, facilitating secure transactions through Stripe.

Key features

• Real-time chat integration – Stream API-powered communication tools for individual and group messaging.
• Location-based search – Connects musicians based on geographic proximity and instrument type.
• Content sharing – Enables users to share sheet music, audio, and video performances.
• Rating and feedback system – Allows musicians to leave reviews and build credibility.
• In-app payments – Supports secure transactions for music collaborations.
• Enhanced user profiles – Interactive profiles with ratings, videos, and smart matching algorithms.

By leveraging modern mobile and cloud technologies, CIGen developed a scalable and user-friendly platform that fosters collaboration and simplifies the management of musical projects.

Objective

A US-based FinTech company required a comprehensive loan management platform to automate loan data analytics, risk assessment, and task management. The goal was to efficiently process thousands of collateral documents, extract relevant data, and build precise risk profiles for investment decision-making.

Challenge & collaboration goals

Handling large volumes of unstructured financial data required a scalable, automated solution capable of managing, analyzing, and visualizing risk. The platform needed to support data extraction, advanced analytics, and reportingwhile ensuring secure access and smooth workflow management.

Tech stack

• Cloud & containerization: Azure, Kubernetes, Docker
• Messaging & event handling: Service Bus, RabbitMQ
• Storage & database: BLOB Storage, T-SQL
• Backend & API: C# .NET
• Frontend & reporting: Angular, Power BI

Results

• Automated data handling, enabling the efficient processing of thousands of collateral documents.
• Advanced risk assessment, visualizing potential risks through data-driven insights.
• Full-cycle task management, supporting the creation, scheduling, and linking of loan-related tasks.
• Secure access management, ensuring controlled data access via Azure Active Directory.
• Comprehensive reporting, providing detailed insights for informed decision-making.

Key features

• Unified asset import and management – Seamless handling of loan data from various sources.
• Full-cycle task management – Enables structured workflows for loan processing.
• Advanced analytics – Transforms raw datasets into actionable risk intelligence.
• In-depth reporting – Generates detailed financial insights and risk assessments.
• Back-end computing algorithms – Implements precise risk modeling and data processing.
• Extended search and queries – Enhances data retrieval for optimized decision-making.

By leveraging Azure, AI-driven analytics, and automation, CIGen developed a robust and scalable loan management solution that enhances efficiency, reduces risks, and supports smarter financial decisions.

Objective

A leading AI solutions provider sought to develop an AI-powered platform to optimize document processing, data integration, and workflow automation. The goal was to streamline enterprise operations, improve efficiency, and enhance decision-making through Azure-based AI solutions.

Challenge & collaboration goals

The company needed to build an AI-driven search and automation engine from scratch, requiring expertise in Microsoft Azure, AI/ML, and scalable backend development. The project focused on enhancing unstructured data processing while ensuring seamless integration with essential business tools.

Tech stack

• Cloud & AI: Azure, Azure OpenAI
• Backend & API: Python, Fast API
• Frontend: React.js

Results

• Improved document processing through advanced AI algorithms, increasing accuracy and efficiency.
• Seamless data integration, enabling a unified data management system.
• Automated workflows, significantly boosting productivity and operational efficiency.
• Mobile accessibility, providing users with on-the-go data interaction.
• Enterprise tool compatibility, ensuring smooth adoption across business environments.

Key features

• AI-powered document processing – Automates data handling and reduces manual effort.
• Unified data integration – Connects various data sources for a comprehensive view.
• Automated workflow management – Optimizes routine tasks for enhanced productivity.
• Mobile accessibility – Extends platform functionality for real-time data interaction.

By leveraging Azure AI, automation, and intelligent search capabilities, CIGen helped build a scalable, efficient, and AI-driven enterprise solution that transforms data management and workflow automation.

Objective

A leading energy technology provider sought to modernize its electricity grid management platform to enhance data visualization, improve analytics, and optimize energy distribution for Distribution Grid Operators (DSOs) and electricity retailers.

Challenge & collaboration goals

The company needed to aggregate, process, and visualize vast amounts of grid operation data in real time while ensuring the platform remained intuitive and efficient. The goal was to upgrade the existing system, introduce advanced analytics tools, and improve overall performance.

Tech stack

• Frontend: Vue.js, Vuetify, TypeScript
• Data visualization: Leaflet
• Version control & CI/CD: Bitbucket

Results

• Migration from Vue 2 to Vue 3, modernizing the framework and improving platform stability.
• Performance optimization, eliminating bugs and enhancing user experience.
• Advanced grid analytics tools, empowering DSOs with actionable insights.
• Real-time data visualization, improving grid monitoring and energy distribution efficiency.
• On-time project delivery, ensuring smooth implementation and effective collaboration.

Key features

• Grid planning and analytics – Provides advanced tools for informed decision-making.
• User-friendly interface – Upgraded UI for a more intuitive experience.
• Real-time data visualization – Enables monitoring and management of energy distribution.
• Modernized platform features – Bug fixes and system optimizations for improved performance.

By leveraging modern web technologies and real-time analytics, CIGen helped transform the platform into a more scalable, efficient, and future-ready solution for energy grid management.

Objective

A leading eCommerce technology provider sought to migrate its infrastructure, SaaS platform, and applications to Azure’s serverless architecture. The goal was to enhance scalability, streamline API management, and prepare for future microservices adoption while ensuring uninterrupted service.

Challenge & collaboration goals

The company needed to transition to Azure DevOps, containerization, and standardized APIs for better efficiency and innovation. The migration had to be executed seamlessly, preserving data integrity and minimizing disruption.

Tech stack

• Cloud & serverless: Azure
• Containerization & orchestration: Kubernetes
• Database management: MySQL
• Backend: Node.js, .NET 7
• API management: Azure API Management
• Frontend: React, TypeScript

Results

• Successful migration to Azure serverless architecture, ensuring long-term scalability.
• Minimal disruption and full data integrity maintained throughout the transition.
• Standardized APIs for vendor, carrier, logistics, and trade-in management, improving interoperability.
• Enhanced system performance, allowing for seamless future microservices adoption.

Key features

• Address module – Centralized management of location-based data.
• Drill-down module – Enables in-depth insights and detailed data exploration.
• Departments module – Streamlines hierarchical data organization.
• SMS module – Enforces telecommunication policies for compliance and risk mitigation.
• Invoices module – Integrates financial tools for streamlined billing and payments.

By leveraging Azure’s serverless architecture and containerization technologies, CIGen helped modernize and future-proof the platform, ensuring greater efficiency and scalability.

Objective

Improve healthcare accessibility by enabling virtual consultations with certified doctors worldwide.

The challenge

Our client, a healthcare technology provider, aimed to develop a mobile platform that would enable patients to consult with certified doctors remotely, reducing hospital visits and long waiting times.

Previously, patients had to physically visit hospitals, often enduring long queues before receiving medical attention. The goal was to create a seamless digital alternative where consultations could be booked and conducted within minutes. Additionally, the app needed to support doctor-to-doctor consultations, allowing medical professionals to collaborate on complex diagnoses.

One of the biggest technical challenges was ensuring stable video calls across a wide range of devices, including older smartphones running Android 5.1, iOS 9, and higher. To achieve this, we focused on optimizing app performance, ensuring lightweight layouts for video streaming, and carefully integrating SignalR and Agora for smooth real-time communication.

Collaboration goals

CIGen was responsible for:
Designing and developing an intuitive iOS and Android mobile app.
Enabling real-time video consultations with minimal latency.
Supporting multi-doctor collaboration for more accurate diagnoses.
Ensuring compatibility with older mobile devices while maintaining performance.

Tech stack

To build a scalable and high-performance telehealth platform, we utilized:

• Mobile development: Xamarin, MVVMCross
• Cloud & backend: Firebase, SignalR
• Real-time communication: Agora, SignalR
• API management: Refit
• Caching & performance optimization: Akavache
• CI/CD & testing: AppCenter
• Secure payments: LiqPay integration

Team composition

CIGen rapidly assembled a team of experienced professionals to bridge the talent gap, delivering a production-ready solution within a significantly shorter time frame:

• Mobile app developer
• Backend engineers
• Project manager
• Quality assurance specialist

Solution & results

CIGen developed a user-friendly telehealth application that empowers patients and doctors with seamless virtual consultations. The solution provides real-time video communication, secure payments, and streamlined scheduling, improving accessibility and convenience for users.

Key achievements:

Effortless onboarding – Doctors undergo credential verification, ensuring trust and compliance.
Seamless booking & payments – Patients can easily choose doctors, schedule appointments, and process payments securely.
Stable video calls – Optimized for smooth video streaming across a range of devices, including older models.
Multi-doctor collaboration – Up to five doctors can join a consultation for enhanced diagnosis.

Core features

Profile creation & verification – Doctors’ credentials are reviewed and approved during registration.
Doctor selection & ratings – Patients can choose specialists based on reviews and experience.
Secure payments – Integrated with LiqPay, ensuring safe transactions.
Real-time chat & video calls – Powered by SignalR, Firebase, and Agora for reliable communication.
Collaborative consultations – Multiple doctors can join a session to discuss complex cases.
Post-consultation feedback – Patients can rate their experience, and doctors can update medical records.

By leveraging advanced mobile technologies and real-time communication tools, CIGen helped revolutionize telemedicine, making healthcare consultations more accessible, efficient, and reliable.

Objective

Minimize investment risks through AI-driven loan risk analytics, portfolio diligence, and asset valuation.

The challenge

Our client, a FinTech company specializing in real estate loan portfolio acquisitions, needed a solution to process large volumes of unstructured and scanned collateral documents. These documents contained essential details about properties, including lien and title status, assignments, and other critical risk indicators.

Due to the complexity of raw datasets and the limitations of standard software in interpreting them, the client required an advanced solution to accurately evaluate risk profiles and calculate optimal bid pricing. They partnered with CIGen to develop a machine learning-powered pricing module that would enable fact-driven decision-making.

Collaboration goals

CIGen was tasked with developing an AI/ML-based application that could:

• Automate loan risk assessment
• Provide data-driven portfolio analytics
• Offer accurate bid pricing calculations
• Ensure seamless scalability and performance

Tech stack

To build a scalable and high-performance solution, we leveraged:

• Cloud platforms: Azure, AWS
• Containerization & orchestration: Kubernetes
• Storage & authentication: BLOB Storage, Azure AD
• Backend development: C# .NET, T-SQL
• Frontend development: Vue.js
• Machine learning & data analytics: AI-driven models for risk assessment

Team composition

CIGen rapidly assembled a dedicated team of experts, ensuring minimal ramp-up time:

• Backend engineers
• Frontend engineer
• Project manager
• Quality assurance specialist

Solution & results

CIGen developed a flexible, AI-enhanced financial platform that streamlines loan risk analysis and pricing model calculations. The solution allows asset managers to make data-backed investment decisions while minimizing financial risks.

Key achievements:
Customizable data management – Departments can define data fields and modify parameters without developer assistance.
User-friendly interface – Authenticated users can easily adjust loan parameters and visualize real-time analytics through graphs and charts.
Advanced analytics engine – Users can create and refine pricing model scenarios with ease.
Rapid loan calculations – Cloud-based ML algorithms execute precise loan risk calculations within seconds.

Core features

Data management: Uploading, storing, and versioning real estate loan tape data from Excel files.
Pricing scenarios: Configuring indexes and key variables into pricing scenarios, managing, and storing them.
Machine learning-powered pricing: Executing ML-based pricing calculations using AWS clusters on demand for each request.

By integrating AI and machine learning, CIGen delivered a robust, scalable, and highly efficient solution that empowers FinTech organizations to make smarter, data-driven bid pricing decisions.