The Fintraffic Mobile app provides real-time information on Finnish roads and rail traffic. Information on traffic disruptions and warnings are sent as push notifications directly to your phone – wherever you are. You can also use the application to report any traffic problems and disruptions you encounter.
How does the app work?
Fintraffic App uses real-time data obtained directly from Fintraffic’s traffic centres, so you always get up-to-date information on the traffic situation. By allowing push notifications from the app, you can receive traffic announcements based on your location even while you are travelling.

The convenient map view shows you what is happening on the roads in your local area. You can choose which items you want to see on the map. The application includes all Finnish road weather cameras, road works, congestion points, driving conditions and weather information, road weather warnings, electric car charging stations and gas (CNG) car refuelling stations and a host of other useful information.

The rail traffic section offers a fully real-time view of all long-distance and regional traffic timetables and live train updates. For example, you can save your business trip as a favourite route and you will be informed immediately if there are any disruptions or changes to the route.

You can easily submit your feedback to the Traffic Customer Service’s Feedback Channel service using the application. Have you seen a pothole in the road or a damaged traffic sign? Is one of the announcement screens on a train station platform out of order? The Traffic Customer Service processes feedback and forwards the information to others, including contractors that carry out maintenance work.

You can report traffic deviations and hazards, such as animals wandering along the road, stopped vehicles, poor driving conditions and other unusual traffic conditions. User reports will appear on the map for 30 minutes. Reporting is easy.

YODA is PostNord’s unified, governed data and AI platform designed to consolidate fragmented Nordic data landscapes into a single scalable foundation for BI, ML, and AI use cases. The initiative was launched to address structural inefficiencies across 13 separate data warehouse environments, inconsistent KPI definitions, duplicated infrastructure costs, and slow time-to-market for cross-domain analytics.

The scope of YODA includes:

Establishing a centralized, cloud-native lakehouse architecture on Azure and Databricks

Harmonizing data definitions across countries and domains

Enabling secure self-service analytics for business domains

Providing a governed foundation for ML and AI initiatives

Implementing standardized ingestion, transformation, and semantic modeling patterns

Introducing enterprise-grade data governance and access control

YODA operates under a federated data mesh-inspired model, where domains own their data products while leveraging shared platform capabilities, security guardrails, and standardized golden paths. The platform supports batch and streaming ingestion, curated medallion architecture (bronze, silver, gold), and enables both traditional BI workloads and advanced AI/ML pipelines.

In 2025, YODA matured from a consolidation initiative into a strategic AI enabler. Key developments included:

Expansion of cross-domain data products for logistics optimization

Enablement of ML use cases such as parcel delay prediction and route optimization

Standardized governance mechanisms aligned with AI risk classification and EU regulatory considerations

FinOps-driven cost transparency and optimization across compute workloads

Increased self-service onboarding of domain teams through structured enablement models

The positive impact includes:

Reduction of infrastructure and licensing redundancy

Significant improvement in cross-country KPI alignment

Accelerated time-to-market for analytics initiatives

Foundation for scalable AI adoption across

ABS (Asset Backed Securitization) IT Service is a cross‑functional data, analytics and AI Product designed to move from fragmented, local reporting to a governed, scalable capability that enables faster decisions and measurable business outcomes. The Product focuses on creating a trusted data foundation, industrialized analytics, and repeatable ways of delivering AI‑enabled improvements across TRATON Financial Service, while meeting strict requirements on security, privacy, and regulatory compliance.

Scope and solution

– Business scope: Prioritized end‑to‑end flow within the funding process where data gaps and manual work limited performance (e.g., planning, operational follow‑up, quality, risk/compliance). The scope includes both decision support and operational use (embedding insights into daily routines and systems).
– Data scope: Selected critical data sources (internal systems and approved external data) were mapped into a common, well‑documented model. Automated pipelines improved data quality, lineage, and refresh frequency. Data products were created with clear ownership, SLAs, and access controls.
– Analytics & AI scope: On top of the data products, the team delivered a set of high‑value use cases such as analytical insight, anomaly detection, portfolio optimization and advanced KPI follow‑up. Models and analytical logic are versioned, tested, monitored, and continuously improved using an industrialized analytics/ML lifecycle.
– Operating model: A product‑oriented way of working was introduced (cross‑functional squads, backlog prioritization with business owners, and standard templates for value tracking). Governance covers data ownership, information classification, and AI considerations, with an emphasis on reuse and scalability.

Positive impact

The ABS IT Service has improved the organization’s data readiness and ability to scale analytics and AI. Early results include:

– Faster, more reliable decision‑making through a single source of truth for key metrics
– Removed manual reporting and reconciliation by and improved data quality (fewer defects, clearer ownership)
– Shorter lead time from idea to production for reporting analytics/AI use cases, from months to days
– Measurable business outcomes in prioritized processes: Data & Analytics first changed the business process from re-active to proactive with a proven monetization.
– Increased adoption: Product teams, supported by training and enablement that strengthens long‑term capability

Overall, ABS IT Service demonstrates how a modern data foundation, robust governance, and a pragmatic delivery model can turn data into sustained business impact—and create a scalable platform for future financial AI‑driven innovation

In January 2025, DeLaval — one of the world’s leading dairy farming technology companies — embarked on a bold, enterprise-wide data and AI transformation. Internally named D4D (Data for DeLaval) and affectionately dubbed “Data Therapy,” this initiative set out to fundamentally rewire how DeLaval thinks about, accesses, and creates value from data and artificial intelligence.

The scope of the transformation is broad and deep, touching strategy, operating model, culture, people, processes, and technology simultaneously.

STRATEGIC SCOPE

The initiative began not with technology procurement but with diagnosis. The incoming Senior Data & AI Platforms and Products Lead ran structured data strategy sessions across DeLaval’s Digital Solutions (DS) organization — engaging domain cells , platform teams, and senior leadership including the CIO, LT, and General Management. These sessions surfaced a clear picture: data teams had become organizational bottlenecks, data access was slow and manual, and data duplication was eroding trust in data-driven decision-making. The resulting D4D strategy was co-created with stakeholders, grounded in their lived experience, and endorsed at the highest level of the organization.

OPERATING MODEL

A new hub-and-spoke (decentralized) operating model was designed and implemented. The central Data & AI Platform team (the “hub”) now owns shared infrastructure, governance standards, tooling, and data platform services. Business domain cells (the “spokes”) own their domain-specific data products and analytics, operating autonomously within governed, standardized frameworks. This model simultaneously centralizes governance and decentralizes execution — enabling scale without surrendering accountability.

ORGANIZATIONAL SCOPE

Two specialized teams were formally established within a new Data & AI Product Area:
— Data Platform Team: tasked with modernizing DeLaval’s legacy platform toward a cloud-agnostic, zero-copy architecture supporting AWS, Azure, SAP, and on-premise environments, while delivering self-service capabilities and reusable components to domain teams.
— Cognitive Platform Team: tasked with scaling AI and agentic solutions as-a-service across all product areas, delivering repeatable, governed AI capability rather than one-off experiments.

PEOPLE & CULTURE SCOPE

The “Data Therapy” framework addresses the human side of transformation across three dimensions — People, Process, and Product (Tech). People interventions include upskilling and reskilling programs, experience mapping across data personas, a community of data advocates, data owner incentive programs, and DevEx improvements. Process interventions include golden path frameworks for data personas, data mentorship programs for cells, role boundary clarity, analytics handoff processes, and roadmapping. Technology interventions include self-serve platform development, low/no-code insights capabilities for non-technical teams, standardized engineering practices, platform vitals monitoring, governance implementation, and centralized external data sharing infrastructure.

AI & PRODUCT SCOPE

Within the first 12 months, DeLaval moved from zero production AI to a live AI services model, with first-version solutions releasing in predictive maintenance, service support enablement, and generative AI capabilities — all delivered through the Cognitive Platform team’s as-a-service model.

By 2028, the vision is for every DeLaval team to independently access trusted, compliant, high-quality data through an intuitive self-service ecosystem — seamlessly integrated into DeLaval’s processes, culture, and daily decision-making from day one of any new employee’s tenure.

This is not a platform upgrade. It is a transformation of how a global industrial company relates to its own data — and ultimately, to its customers and the farmers it serves.