Estonia rolls out Bürokratt, an AI-guided virtual assistant network for public services
Estonian Government (RIA - State Information System Authority) · Estonia
Bürokratt is a network of chatbots deployed on Estonian public sector institutions' websites, letting people obtain information from institutions and use public and information services via virtual assistants. It is a state-created, AI-based digital assistant that helps institutions deliver modern, efficient, around-the-clock customer service using large language models.
Overview
Bürokratt is a network of chatbots deployed on Estonian public sector institutions' websites, letting people obtain information from institutions and use public and information services via virtual assistants. It is a state-created, AI-based digital assistant that helps institutions deliver modern, efficient, around-the-clock customer service using large language models.
This entry has 13 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
Estonian public sector institutions needed a way to deliver modern, efficient, and up-to-date customer service, and to let people interact with the state in natural language rather than navigating complex portals and forms.
The solution
Bürokratt is a network of AI-based chatbots that public sector institutions deploy on their own websites, using large language models to understand natural-language input and answer questions. Per kratid.ee's stated 'Vision of Bürokratt', the chatbots deployed to clients will form a unified network that lets people find answers, solve problems, and consume digital services directly from the chat window, without navigating complex portals or filling out forms — a stated future vision, not a delivered present capability. By the end of 2025 the rollout includes deploying an LLM/RAG model, a general knowledge module, and a central 'global classifier' component that lets different Bürokratt instances communicate securely with each other; from 2026 the plan is for each institution or domain to run its own personalized AI agent within a unified, cooperative network of agents.
Reported business value
The Bürokratt software itself is free; institutions pay only State Cloud hosting (about 150 per month, per the source) plus large language model usage costs, in exchange for RIA support from the first demo through production. Institutions moving from older, manually-maintained rule-based chatbots to LLM-based Bürokratt gain better answers with less manual upkeep — RIA's own electronic identity department (id.ee) was the first to adopt the LLM-based solution, and several public sector institutions already use Bürokratt.
Sources
Open any source and check the claim yourself — that is the point of the register.
Other government & public sector entries in the register.
Austrian Academy of Sciences unlocks Ancient Greek with Mistral
The Austrian Academy of Sciences (OeAW), together with its Austrian Archaeological Institute, partnered with Mistral and services partner Reply to build Apollo, described as the first advanced large language model for Ancient Greek. Apollo is trained on a specialized corpus of 600 million words of historical Greek text plus tens of thousands of published inscriptions and papyri, helping researchers reconstruct damaged texts and identify thematic connections across collections. The OeAW reports Apollo turns work that once took years into hours, addressing over one million unread Greek papyri worldwide, with future phases planned for semantic search and handwritten inscription decipherment.
MITRE's Federal AI Sandbox accelerates government AI research with NVIDIA DGX SuperPOD
Nonprofit MITRE built the Federal AI Sandbox, powered by NVIDIA DGX SuperPOD, to give federal sponsors an affordable, centralized space to test and deploy AI and machine learning across domains such as weather forecasting, cybersecurity, and public benefits administration. The DGX SuperPOD delivers a 300-fold performance increase over MITRE's previous AI computing capabilities and supports thousands of researchers; MITRE is using it with NVIDIA Omniverse and NVIDIA Earth-2 to develop 1-kilometer precision weather forecasts with NOAA and the National Weather Service, plus a foundational model for cybersecurity threat analysis across 190 nations.
Israel's Meteorological Service Predicts the Weather Using NVIDIA Earth-2
The Israel Meteorological Service integrated an AI weather model called F3, powered by NVIDIA Earth-2 and NVIDIA PhysicsNeMo (including the CorrDiff neural network), into its forecasting system to achieve hyperlocal 2.5-kilometer resolution precipitation forecasts. F3 achieved 90 percent lower computational costs compared to running a classic non-AI numerical weather prediction model on a CPU cluster, delivering forecasts in minutes rather than hours, and saved 20-30 percent of the Tel Aviv-Yafo Municipality's preparedness budget for things like urban flood safety. CorrDiff was trained to emulate IMS's regional high-resolution ICON model using low-resolution ECMWF IFS input, enabling four high-resolution forecasts per day. Partners including the Israeli Police, the National Fire and Rescue Authority, the Ministry of Transportation and the National Road Company have adopted the forecasts, and IMS used F3 to issue a high-resolution flood map during a January storm that dropped 150 millimeters of rain in six hours.
AIBots: GovTech Singapore's platform for public officers to build RAG-powered AI chatbots
GovTech Singapore built AIBots, a platform that lets Singapore Public Officers create, customise, and deploy Retrieval-Augmented Generation (RAG) generative AI chatbots in under 15 minutes, enhancing responses by integrating internal agency knowledge bases (including content classified up to Restricted/Sensitive Normal) alongside publicly available information. Officers have used it for talking-points and speech generation, Q&A chatbots on internal HR, travel and onboarding processes, and survey verbatim analysis. Between August 2024 and February 2025, AIBots reached 40,000 users across 115 government agencies, with 12,000 bots created and over 1 million messages sent.
Was this helpful?
Your feedback helps us improve our use case database