UX & Product Design Case Studies

AI-native customer support without the AI-startup budget

Modena’s support team handles inbound emails in three languages and serves two distinct audiences — borrowers and investors — under licensed-financial-institution audit requirements.

Annual direct financial gain (5 agents): 27 420 €

Time saved by AI features: 27.5h / week

Challenge

Every customer reply at a licensed credit institution must be auditable and regulation-compliant. The support team was juggling three languages, two portals (modena.ee for lending and modena.capital for investors), and the constant pressure of fast, consistent quality across a small team.

Solution

11 AI workflows, one platform. AI is integrated into 11 distinct support workflows rather than bolted on as a side chatbot; every AI output goes through human review before reaching a customer.

Cost-aware three-model strategy. Triage runs on Haiku, reply drafting on Sonnet, complex reasoning on Opus — admins can see and override the choice per scenario.

RAG on the Zendesk archive. Every new ticket surfaces the three most similar resolved tickets as context, so the AI learns from how humans actually handled the same question.

Portal-aware knowledge base. Every KB article is tagged with a portal — investor tickets never see lending FAQs and vice versa.

Self-extending KB. Every Sunday, Claude reviews resolved tickets and drafts the three most-recurring FAQs; admins click ‘publish’ after review.

Graceful degradation. If the Claude API is down, the platform keeps running — AI is an enhancement, never a critical path.

AI
Backend
PHP
Self-Service
UX

Result

Response time dropped from 5–10 minutes to 1–2 minutes per reply.

Escalations now reach the right person the same day, not from the back of the queue.

Reply quality is more consistent across agents — same KB, same prior resolutions.

New hires use the platform on day one — no ‘prompt engineering’ training needed.

Direct software savings of ~7 140€/year versus Zendesk Suite + Advanced AI.

Key takeaway

An AI-native support operation doesn’t need an AI-startup budget — it needs careful workflow integration, a cost-conscious model strategy, and humans in the loop on every decision.

Dynamic, governance-first data access on Estonia’s most-queried register

The Estonian Population Register is operated by the Ministry of the Interior and SMIT, holding personal data for citizens, EU residents, and permit holders, and serving more than 260 institutions.

Annual queries: 200+ million

Connected institutions: 260+

Challenge

The existing X-Road services were limited by static structures, heavy query loads, and insufficient control over how data was accessed and processed — a problem given the register’s role in critical national infrastructure.

Solution

REST-based X-Road services. Redesigned with built-in intelligent control mechanisms; queries are dynamically configurable per legal or contextual purpose.

Rule-based governance. Data managers can define which fields are accessible, under what conditions, and for which legal basis — enabling autonomous service governance.

Access-rights GUI + audit logs. A new graphical interface for managing user rights and monitoring usage in detail.

Bundled, tagged queries. Multiple queries can be bundled under a single action and tagged with legal context such as ‘justified interest’ or ‘public interest’.

AI
Backend
Java
Public
Self-Service
UX
X-road

Result

A secure, flexible, AI-ready data access platform for critical national infrastructure.

Transparent, automated, intelligent control over how population data is shared.

Stronger public-sector data governance across 260+ connected institutions.

Foundation in place for future AI-powered government services.

Key takeaway

At national-register scale, the win isn’t a faster query — it’s a governance layer that makes every query legally explicit and auditable.

MISX – Pattern detection and surveillance tooling for modern law enforcement

The Police and Border Guard Board is Estonia’s unified law-enforcement and internal-security agency with around 5,000 employees, operating under the Ministry of the Interior.

AI
Backend
Java
UX
X-road

Challenge

The PPA’s new MISX procedural system needed a modern way to manage object and individual surveillance. The legacy approach didn’t scale, leaned heavily on manual work, and gave investigators little support for tracking relationships between entities like vehicles and persons.

Solution

Microservices surveillance module. A new-generation MISX surveillance module built on a modular architecture for scalability and adaptability.

Automatic pattern detection. Surfaces relationships between entities — for example, linking a person to a vehicle in the context of a traffic incident.

Dynamic form generation. The interface adapts to data type and context, reducing training needs.

Rule-based automation. Status changes and user permissions adjust automatically based on rules — age, event deadlines, case state.

X-Road data validation. Live cross-checks against national registries keep data accurate and current.

Result

Faster decision-making and significantly more process automation in surveillance workflows.

AI-assisted features cut manual work in identifying relevant data relationships.

Modular structure adapts to future procedural and administrative workflows.

A more responsive public-safety tool that saves investigators’ time.

Key takeaway

Investigative workflows benefit more from quietly automated pattern detection than from flashy AI features — speed and reliability matter most.

KPOIS – Microservices and automated data flows for Estonia’s land constraint registry

KeMIT is the IT center for the Estonian Ministry of Climate, maintaining geospatial, weather, and environmental systems including KPOIS, the national land constraint information system.

AI
Backend
Java
Public
UX

Challenge

KPOIS was built on a monolithic architecture that limited flexibility, scalability, and maintenance. Manual data entry created bottlenecks, spatial analysis tools were missing, the UI was static, and integrating external data sources was painful.

Solution

Microservices migration. Transitioned KPOIS to a modular, performance-oriented architecture built for automation.

Standalone geospatial service. Introduced visual buffer-zone creation and interactive map views to support spatial decision-making.

Automated data ingestion. Replaced manual inputs with FME workflows, enabling seamless integration with external registries.

Personalized dashboard. Context-aware tasks and data presented per user, with smart session and notification management.

Schema partitioning. Restructured data models for intelligent data processing and faster queries

Result

A future-proof, automated, user-centric environment for managing land use constraints.

Faster, more accurate decisions for both end users and administrators.

Manual data flows largely replaced by automated registry integration.

Platform now ready to host AI-driven spatial analytics and predictive features.

Key takeaway

Public-sector registries don’t have to stay monolithic — microservices plus automated data flows turn a static registry into a decision-support tool.

A monolith-to-microservices rebuild for Estonia’s nature data system

EELIS is Estonia’s central information system for biodiversity and nature protection data, used by conservation specialists, monitoring teams, and field workers.

AI
Backend
Java
Public
UX

Challenge

EELIS was built as a monolithic, workstation-based application — the legacy architecture limited scalability, was painful to use in the field, and didn’t integrate with modern digital workflows.

Solution

Microservices migration. Complete platform rebuild on a microservices architecture for modularity and scale.

PostgreSQL geo-databases. Backed by interactive map applications and automated CI/CD deployment pipelines.

Mobile field tools. Restructured for seamless data exchange with external registries and support for mobile use in the field.

AI-ready data foundation. Reworked data models enable pattern recognition, decision support, and geospatial analytics.

Open data publishing. Opens the door to training ML models for environmental research and forecasting.

Result

An intelligent, scalable, data-rich platform for nature management across Estonia.

Specialists have meaningfully better tools for fieldwork and daily operations.

Manual data flows largely replaced by automated processes.

EELIS is now a strategic decision-support system, not just a static registry.

Key takeaway

Environmental and scientific registries gain disproportionately from microservices — the real win is unlocking AI and automation that the old architecture made impossible.

From clunky third-party scoring to in-house, real-time credit decisions

Modena is an Estonian fintech offering BNPL, instalment plans, consumer loans, and business credit, trusted by 100,000+ customers and regulated by the Estonian Financial Supervision Authority.

Audience: B2C & B2B in one flow

New credit scoring system: Built in 3 months

Challenge

Modena set out to expand BNPL and loan offerings, but the external credit-scoring provider they had been using was slow, unreliable, and forced customers through third-party interfaces that damaged trust. As a licensed credit provider, mission-critical payment operations could not tolerate that level of friction.

Solution

AI-powered credit scoring engine. Built in-house in three months; ingests customer bank data, categorizes it, and returns a real-time creditworthiness score for both private and business customers.

B2C + B2B application portal. One streamlined loan application flow with decision logic that adapts to the customer type.

Merchant webshop plugins. Retailers can offer Modena’s BNPL service at checkout, expanding reach across Estonia’s digital retail market.

No third-party redirects. Onboarding stays inside the Modena interface, removing the trust gap the previous provider had created.

AI across everyday workflows. Internal tools help generate reports on demand and guide marketing by surfacing which customers to contact with which offer.

AI
Backend
Kotlin
Self-Service
UX

Result

Near-instant credit decisions, end-to-end inside Modena’s own interface.

Higher scoring accuracy and lower default risk than the previous external provider.

Expanded merchant reach across Estonian e-commerce.

Faster product iteration — Modena can respond to market changes in days, not quarters.

Key takeaway

In regulated lending, owning the credit-scoring layer is what unlocks both speed and trust — and a small team with AI-accelerated development can build it in months.

An AI-enhanced webshop and warehouse stack for a food-waste fighter

Sumena is an Estonian impact retailer fighting food waste by selling near-expiry, damaged-packaging, and discontinued groceries at 30–80% off, operating an online shop and six physical stores.

Traffic after rebrand: 2x growth

Revenue: 2x month-on-month

Challenge

Sumena’s product mix changes daily — different suppliers, different expiry dates, different stock levels — and manual customer support, pricing, and stock planning created delays, inaccurate forecasts, and missed sales as the business grew.

Solution

Responsive webshop. Modern e-commerce front end built to handle the rapid product turnover that comes with near-expiry inventory.

Intelligent sourcing module. Forecasts future stock needs and estimates sourcing costs based on seasonality, trends, and supplier behavior.

Warehouse management system. Connects sourcing, stock, and storefront so the team sees the same picture across channels.

AI-driven chatbot. 24/7 customer support that understands user queries and guides purchases.

ML on browsing and purchase data. Predicts product popularity and supports pricing decisions, reducing both overstock and stockouts.

AI
Backend
PHP
Self-Service
UX

Result

Traffic doubled after the rebrand and new webshop launch.

Revenue grew 2× month-on-month following the relaunch.

Manual customer support workload reduced through 24/7 AI handling of common queries.

Pricing and stock decisions are now data-driven rather than gut-driven.

Key takeaway

A small impact retailer doesn’t need a Silicon Valley budget to get AI-enhanced e-commerce — it needs the right modules in the right places.

Modernizing the online rental experience

Europcar is a global mobility service provider and one of the world’s largest car rental companies, owned by a consortium led by the Volkswagen Group.

.NET
AI
Backend
Self-Service
UX

Challenge

Europcar needed to enhance its web-based short- and long-term car rental services to improve customer experience and streamline booking operations.

Solution

Platform upgrade. Improvements to the existing rental platform with a focus on user experience and backend optimization.

Result

A more responsive, user-friendly rental interface.

Streamlined booking operations for both short- and long-term rental products.

Key takeaway

A well-targeted UX and backend upgrade on an established rental platform can ship customer value without a full rebuild.

Building trust in lending: how Modena achieved instant credit decisions with AI and custom development

The collaboration between Modena and SRINI has been ongoing for over four years, delivering continuous improvements and growth.

Modena is an Estonian-based FinTech company that provides smart payment solutions and flexible financing. They bridge the gap between merchants and consumers by offering seamless “Buy Now, Pay Later” (BNPL) integrations and traditional credit products through a fully digital, user-friendly ecosystem.

1. BNPL & Checkout Solutions (B2C)

Modena’s core strength lies in its embedded finance tools for e-commerce and retail stores, designed to increase conversion rates and average order value.

Pay in 3 (Split Pay): Customers can divide their purchase into three equal monthly installments. This is typically interest-free and fee-free for the consumer, making it a powerful alternative to credit cards.

Pay Later (30 Days): Often marketed as “Click & Try,” this allows customers to order goods, receive them, and only pay after 30 days. It is ideal for fashion and home decor where customers want to verify the quality before committing.

Modena Hire-Purchase (Järelmaks): For high-ticket items (electronics, furniture, etc.), Modena offers long-term financing for up to 48 months with instant credit decisions at the point of sale.

2. Personal Lending Products

Beyond the checkout, Modena provides direct-to-consumer financial services via their online platform.

Credit Line (Krediidiliin): A flexible “digital wallet” with a limit of up to €5,000. Users only pay interest on the amount they actually withdraw, providing a safety net for unexpected expenses.

Small Loans & Refinancing: Fixed-term loans for personal projects or the consolidation of existing high-interest debts into a single, more affordable monthly payment.

3. Business Solutions (B2B)

Modena supports the growth of small and medium-sized enterprises (SMEs) with fast, data-driven credit products.

Business Loans: Quick financing up to €50,000 for inventory, equipment, or working capital.

Merchant Portal: A dedicated dashboard for retailers to track BNPL performance, manage refunds, and analyze customer behavior in real-time.

4. Investment Opportunity: Modena Capital

Unique to Modena is their integrated investment platform, allowing retail and institutional investors to earn returns by funding the loan portfolio.

Target Returns: Investors can earn up to 11% p.a.

Safety Features: Most investments are protected by a 60-day buyback guarantee, reducing the risk for the investor.

Why Modena Stands Out?

Speed: Their proprietary credit scoring algorithm provides decisions in seconds.

Regulatory Status: Licensed as a creditor by the Estonian Financial Supervision Authority, ensuring high standards of transparency and consumer protection.

Seamless Integration: Their API allows merchants to add multiple payment options to their webshop with minimal technical effort.

In short: Modena is the Baltic answer to Klarna, offering a comprehensive suite of tools that make buying, selling, and lending more flexible and accessible for the digital age.

A frictionless lending experience with near-instant credit decisions.
Higher accuracy in credit scoring, reducing risk compared to external solutions.
A trusted and user-friendly interface, which strengthened customer confidence.
Agility in product development, allowing Modena to respond to market needs faster.

AI
Backend
Kotlin
Self-Service
UX

Case Category: UX

AI-native customer support without the AI-startup budget

Modena’s support team handles inbound emails in three languages and serves two distinct audiences — borrowers and investors — under licensed-financial-institution audit requirements.

Dynamic, governance-first data access on Estonia’s most-queried register

The Estonian Population Register is operated by the Ministry of the Interior and SMIT, holding personal data for citizens, EU residents, and permit holders, and serving more than 260 institutions.

MISX – Pattern detection and surveillance tooling for modern law enforcement

The Police and Border Guard Board is Estonia’s unified law-enforcement and internal-security agency with around 5,000 employees, operating under the Ministry of the Interior.

KPOIS – Microservices and automated data flows for Estonia’s land constraint registry

KeMIT is the IT center for the Estonian Ministry of Climate, maintaining geospatial, weather, and environmental systems including KPOIS, the national land constraint information system.

A monolith-to-microservices rebuild for Estonia’s nature data system

EELIS is Estonia’s central information system for biodiversity and nature protection data, used by conservation specialists, monitoring teams, and field workers.

From clunky third-party scoring to in-house, real-time credit decisions

Modena is an Estonian fintech offering BNPL, instalment plans, consumer loans, and business credit, trusted by 100,000+ customers and regulated by the Estonian Financial Supervision Authority.

An AI-enhanced webshop and warehouse stack for a food-waste fighter

Sumena is an Estonian impact retailer fighting food waste by selling near-expiry, damaged-packaging, and discontinued groceries at 30–80% off, operating an online shop and six physical stores.

Modernizing the online rental experience

Europcar is a global mobility service provider and one of the world’s largest car rental companies, owned by a consortium led by the Volkswagen Group.

Building trust in lending: how Modena achieved instant credit decisions with AI and custom development