ENSL

SPATIAL & LEGAL AI INFRASTRUCTURE.

Automating Slovenian real estate zoning and compliance through hybrid semantic-spatial architecture and municipal OPN integration.

Core Architecture

SELECT * FROM legal_vectors
WHERE relevance > 0.85
Processing: 1.2M VECTORS
Latency: < 0.4s
INDEX_SIZE: 1.2M VECTORS
LATENCY: < 0.4s
2025

JURISPRUDENCE ENGINE

[PYTHON] [RAG] [LLM] [PINECONE]

Vectorizing 25,000+ Slovenian court cases and real estate laws for high-semantic retrieval.

PYTHON / PINECONE / OPENAI LEGAL INTELLIGENCE SYSTEM
REQUEST_LIVE_DEMO
SELECT * FROM legal_vectors
WHERE relevance > 0.85
Processing: 75% COVERAGE
Latency: BATCH
INDEX_SIZE: 75% COVERAGE
LATENCY: BATCH
2025

SPATIAL DATA PROCESSING

[PYTHON] [GIS] [POSTGIS] [GDAL]

Mapping and translating municipal OPN (Občinski prostorski načrt) GIS data into LLM-readable context.

PYTHON / POSTGIS / GDAL GIS PIPELINE
REQUEST_LIVE_DEMO
SELECT * FROM legal_vectors
WHERE relevance > 0.85
Processing: REAL-TIME
Latency: < 200ms
INDEX_SIZE: REAL-TIME
LATENCY: < 200ms
2025

AUTOMATED ZONING SYNTHESIS

[PYTHON] [LANGCHAIN] [PGVECTOR] [AGENTIC]

Agentic workflows that cross-reference parcel data with legal precedent to answer: "What can be built here?"

PYTHON / LANGCHAIN / PGVECTOR AGENTIC WORKFLOW
REQUEST_LIVE_DEMO
// 01_Problem_Statement

WE DON'T JUST SEARCH LAW.WE COMPUTE SPATIAL REALITY.

Slovenian real estate development is bottlenecked by fragmented municipal zoning laws (OPN) and dense legal precedents. Oriney merges geographic information systems (GIS) with advanced vector search to cut zoning analysis from weeks to seconds.

// SYSTEM_ARCHITECTURE: hybrid_retrieval_pipeline
├── SEMANTIC_ENGINE ← 25,000+ court cases + RE laws
│ ├── vector_store: Pinecone (1.2M embeddings)
│ └── retrieval_latency: < 200ms
├── SPATIAL_ENGINE ← Municipal OPN GIS data
│ ├── coverage: 75% market volume
│ └── data_format: PostGIS + GeoJSON
└── SYNTHESIS → Agentic cross-referencing
└── output: "What can be built here?"
// 02_System_Specifications

SYSTEM SPECS

Infrastructure scale at a glance.

METRIC_01

25k+

Legal Documents Embedded

METRIC_02

75%

National Market Coverage (Phase 1)

METRIC_03

<200ms

Vector Retrieval Latency

System Stack

Our infrastructure runs on a modern AI + Web hybrid stack. Every component is chosen for performance, scalability, and LLM integration.

Astro

React

Tailwind

Python

PostgreSQL

Google Gemini

OpenAI

Anthropic

LangChain

Docker

// System_Expansion_Log

DEPLOYMENT ROADMAP

A structured rollout of our hybrid semantic-spatial infrastructure, from foundational vectorization to national production coverage.

SYSTEM_EXPANSION_LOG
v0.1 FOUNDATION ACTIVE

Jurisprudence Engine & Closed Alpha

Vectorization of 25,000+ legal documents. Closed alpha testing with select legal and architectural partners.

EST. Q1 2026
v0.2 SPATIAL_ALPHA IN PROGRESS

Spatial GIS Pilot

Integration of first municipal OPN datasets across Slovenj Gradec & Ljubljana regions.

EST. Q1 2026
v0.3 HYBRID_SYNTHESIS QUEUED

Hybrid Analysis Synthesis

Cross-referencing legal precedent with GIS polygons. Automated zoning synthesis for Beta access.

EST. Q2 2026
v1.0 PRODUCTION QUEUED

Commercial Launch

National market coverage, automated PDF report export, and regional expansion.

EST. Q4 2026
// BETA_PROGRAM
ALPHA_BUILD

SYSTEM CURRENTLY IN CLOSED ALPHA.

We are testing our hybrid retrieval pipelines with select legal and architectural partners. Join the waitlist for early access.

// NO_CREDIT_CARD_REQUIRED // EARLY_ACCESS_PRIORITY

System Access

Request Beta access, API documentation, or partnership details.

REGIONAL_HQ

OPERATIONAL_STATUS
ACTIVE

Location

Slovenj Gradec, Slovenia

// Data Input Console

// LEAD_ARCHITECT

"Oriney is led by Rok Slemenik, a full-stack architect specializing in high-performance web and AI infrastructure."