AI built around the data, not the model.

We build production AI for organizations whose work depends on regulated content, complex data, and high-stakes reasoning.

- SOLUTIONS IN PRODUCTION

One product. Two engagements. Live in 2026.

Lex AI is our own product, deployed commercially through Paragraf Lex. Two active engagements for the Art Loss Register are going live in 2026.

[ CITATION ] Zakon o radu, čl. 32 [ CITATION ] Sl. glasnik 24/2005 View sources
LIVE · LEGAL · REASONING AGENT · PRODUCTION INTEGRATION

Lex AI - reasoning agent for Serbian legal research

A domain-specialized reasoning agent operating natively inside Paragraf Lex, the de facto legal information platform in Serbia. In production since 2026, deployed under continuous evaluation.

Reasoning agentSource-anchoredSerbian legal languageNative platform integration
Read more about Lex AI
LOT 042 LOT 043 LOT 044 LOT 045 LOT 046 ▸ matched LOT 047
GOING LIVE 2026 · ART-MARKET DUE DILIGENCE

Catalog Star

An engagement for the Art Loss Register - structuring the historical auction record for due-diligence search. In phased rollout; going live in 2026.

the Art Loss RegisterAuction-catalog intelligenceProvenance
Engagement overview
› query: 1972 Ferrari Daytona, sold 2018-2024 Ferrari 365 GTB/4 Daytona Lot 122 · €1.2M · Monaco · 2021 Ferrari 365 GTB/4 Daytona Lot 047 · €1.4M · London · 2019 Ferrari 365 GTB/4 Daytona Spider Lot 209 · €2.6M · Pebble Beach · 2023
GOING LIVE 2026 · CLASSIC VEHICLE PROVENANCE

Classic Car Register

An engagement for the Art Loss Register - linking visual evidence to provenance claims across decades and auction houses. In phased rollout; going live in 2026.

the Art Loss RegisterClassic vehiclesProvenance
Engagement overview
- HOW WE WORK

Engineering, not prompting.

Our process treats AI systems as engineering problems. Retrieval, structure, evaluation and integration come before model choice - because models change every year, but the data and the domain don't.

01

Domain modelling

We co-develop the data ontology with subject-matter experts before any model is selected. Domains carry constraints models alone won't surface.

02

Retrieval & extraction architecture

Hybrid retrieval, structured parsing and entity linking are designed up front. The retrieval layer determines what the model can know.

03

Reasoning layer integration

Models - closed-source, open-weights or fine-tuned - are selected to fit the reasoning load, not the other way around.

04

Evaluation harness

We build the eval before the system. Golden sets, retrieval metrics, hallucination measurement, regression tests.

05

Production integration

Our systems ship inside existing platforms with auth, audit, monitoring and an operational handover.

06

Continuous evaluation

Production traffic feeds back into the eval. Quality is measured on a recurring cadence, not at launch and never again.

- WHY PROZONE AI

Built on enterprise software experience, focused on modern AI.

Prozone AI is the AI-native continuation of the Prozone software ecosystem - decades of enterprise delivery experience now pointed at the systems organizations need to build with modern machine learning.

01

Enterprise heritage

Built on years of delivering complex software systems, document management and business-process platforms across regulated sectors.

02

Domain depth, not generic chat

We focus on AI systems that genuinely understand legal, archival and enterprise data - not generic LLM wrappers.

03

Engineering across the stack

Retrieval, structured extraction, agentic workflows, predictive ML and evaluation - delivered as production software with operational ownership.

04

Regional reach

Operating through Prozone AI and Prozone Middle East, with delivery capability across Serbia, Europe and the Gulf region.

- TRUST & DEPLOYMENT POSTURE

Where the system runs is part of the design.

Engineered for organizations where data sensitivity, audit obligations and operational accountability are primary - not afterthoughts.

Your data, your infra On-prem · Private cloud · Hybrid
Audit-ready Logging · Evaluation · Regression testing
No data exfiltration Conservative on what leaves your network
Production accountability Operational ownership, not one-shot delivery

Have a domain that nobody else seems to understand?

That's usually where we start. Tell us about the documents, the data, the constraints - and what your AI system needs to actually understand.