🏆 PropTech Germany Award 2024

Real Results, Fixed Cost

Every engagement below was delivered within the estimated budget and timeline under our fixed-cost model. No surprises — just outcomes.

🏆 PropTech Germany Award #1
Case Study 01

AI Real Estate Data Intelligence SaaS

SaaS Platform Development

High-capacity multi-tenant SaaS platform connecting multitude of client data sources with synergy of AI components and discrete business workflows. Deployed on k8s with Terraform IAC, built to scale seamlessly.

Budget€367k
Timeline9 months
Tech Stack
KubernetesTerraformPythonReactMLOpsDevOps
Team
Product OwnerSolution ArchitectMLOps / DevOps EngineerUI/UX Designer1 Lead Engineer2 Back-End Engineers1 Front-End EngineerManual QA
70%
improvement in model response time (MVP vs POC)
$50K+/mo
savings in cloud operations fees
1TB+
storage capabilities designed & implemented
#1
Real estate startup in Germany — PropTech Germany Award

What We Delivered

  • Multi-tenant SaaS platform MVP within budget and timeline
  • Highly scalable microservices architecture on Kubernetes
  • Terraform IAC with seamless deploy/migrate capabilities
  • Engineering excellence with data-driven decision making
  • Full-spectrum testing: unit, integration, functional, smoke, regression, usability
  • Continuous IT support and development for platform and services
  • Security by design with penetration testing
Client Goal

High-capacity SaaS platform able to seamlessly connect multitude of client data sources. Synergy of AI components with discrete business workflows logic implementation.

💳 High-Impact R&D AI
Case Study 02

ML Payment Gateway Cascade

Payment Optimization

Synergy of ML model and data pipelines to streamline payment processing and maximize profits across a diverse portfolio of payment gateway providers. Robust automated ML evaluation and CI/CD pipeline.

Budget€370k
Timeline6 months
Tech Stack
PythonML ModelsData PipelinesCI/CDAutomation QA
Team
Project Manager2 Data Engineers1 Data Scientist2 Data Analysts1 Manual QA1 Automation QA
40%
reduction in payment gateway fluctuations
95%
reduction in human error rate
50%
decrease in time-to-market
25%
reduction in support costs

What We Delivered

  • Robust ML models created and maintained
  • Supportive data stream pipelines for multiple integrations
  • Automated model evaluation process
  • Improved corporate transparency by eliminating manual financial data manipulation
  • Full QA suite: exploratory, compatibility, UI/UX, regression, E2E
  • CI/CD process for product increments
Client Goal

Synergy of ML model and data pipelines to streamline payment processing and maximize profits across diversity of payment gateway providers.

🔮 Predictive Maintenance AI
Case Study 03

Outage Prediction & Anomaly Detection

Performance & Risk Identification

AI model with supportive services for a natural resource extraction company to prognose and manage maintenance activities and MIH resolution. Deployed to production with full automated release candidate testing.

BudgetUnder €400k
TimelineUnder 6 months
Tech Stack
MLOpsPythonAzureMicroservicesDevOps
Team
Project ManagerDev Team LeadBackend DeveloperFrontend Developer2 Data Engineers1 Data Scientist1 MLOps Engineer1 Automation QA
70%
budget planning accuracy vs proprietary past period estimations
90%
reduction in time spent on testing while maintaining quality
30%
increase in overall software quality by multiple metrics
99%
success release ratio measuring prod P0 incidents
60%
more effective maintenance team dispatch planning

What We Delivered

  • Robust microservices architecture with automated backup/restore
  • Seamless scaling capability for rapid business growth
  • Configurable data pipelines for straightforward integrations
  • Detailed change log and discovered/rediscovered bug tracking
  • Handed over to support phase with minimal resources
  • Fully automated release candidate E2E testing
Client Goal

Natural resource extraction company looking for a way to prognose and manage maintenance activities and MIH resolution. AI model with supportive services was developed and released to production.

⚙️ AI Component Development
Case Study 04

AI Component for MS Dynamics 365

CRM Intelligence & Automation

Reduce human effort on routine tasks, automate data gathering and develop XML data schema extraction/upload workflows for a leading MS Dynamics 365 software vendor.

BudgetUnder €100k
TimelineUnder 3 months
Tech Stack
Azure CloudPythonReactReact NativeMS Dynamics 365
Team
Project ManagerBackend DeveloperFrontend DeveloperMobile DeveloperML EngineerManual QA
30%
increase in deal processing speed
20%
increase in deal closure rate
84%
employee satisfaction rating (post-demo feedback)
25%
decrease in contractor FTE expenses

What We Delivered

  • Platform component designed from POC through MVP to PROD
  • Wireframes and designs aligned with client vision and UI/UX principles
  • Solution architecture adopted to client environment and infrastructure
  • Passed company security audit and penetration testing
  • Monitoring, control metrics, and notifications for support
  • Significant decrease in human error across deal workflows
Client Goal

Reduce human effort on routine, automate data gathering and come up with XML data schema extraction/upload workflows based on requirements.

Ready for results like these?

Every engagement is fixed-cost. Tell us about your PropTech platform and we'll come back with a team composition and delivery estimate within 24 hours.