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.
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.
The PPA supervises firearm licenses across Estonia, a process that historically required officials to navigate multiple systems, run time-consuming registry queries, and process paperwork manually.
AI
Backend
Java
Public
X-road
Challenge
Firearm license supervision relied on fragmented systems and manual checks across multiple interfaces, slowing decisions, increasing the risk of human error, and limiting oversight transparency.
Solution
Centralized supervision module. A single intelligent module inside the national firearm registry that handles end-to-end supervision.
X-Road registry queries. Automated queries across key government registries detect when supervision is required, with no manual lookups.
Rule-based case initiation. When triggered, the system opens the case, gathers data, compiles a structured report, and drafts a decision — without human intervention.
Built-in validation. Avoids duplicate cases and flags logical inconsistencies, further reducing error risk.
Full audit trail. A detailed data tracker monitors every registry interaction, keeping AI behavior auditable.
Result
Routine supervision tasks largely automated.
Faster, more consistent decision-making.
Reduced human error and improved data quality.
Higher transparency and accountability across oversight activities.
Key takeaway
Regulatory oversight is a natural fit for automation — but only when every AI step is auditable and a human can always inspect the trail.
Working with SRINI has been a consistently positive experience for our team at Bondora. When we first engaged them, we needed a development partner who could hit the ground running in a complex, regulated fintech environment — and SRINI delivered exactly that.
Pärtel Tomberg
CEO / Owner - Bondora
SRINI has been an essential technology partner for Modena from day one. Their team truly understands the fintech landscape and consistently delivers reliable, scalable solutions that keep our installment payment platform running smoothly. What we value most is their ownership mindset — they don't just execute tasks, they think alongside us.
Oliver Matt
CEO - Modena Estonia
SRINI helped us build the tech backbone that makes food rescue retail actually work at scale. From inventory systems to our customer-facing platform, they understood that speed and reliability aren't optional when you're dealing with perishable goods and tight margins. A partner who gets both the mission and the mechanics.
Joosep Kaljula
CEO - Sumena
Our partnership with SRINI goes beyond a typical vendor relationship. As a strategic investment and development partner, SRINI has consistently proven that they deliver on their commitments — both technically and commercially. They bring structure, transparency, and genuine expertise to every project we co-develop. It's rare to find a software company that thinks like a business partner, not just a service provider.
Kristian Hein
CEO - LEI System
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