The Platform

Every component is in production on enterprise-scale datasets. It's not a prototype: it's a proven system.

Components

Four proprietary components

OSINT Engine

Universal data collection engine, configurable on any domain: regulations, competitors, markets, territory, suppliers, tenders.

4 integrated search engines with fallback
Crawling on target sites with IPv6 rotation
Change detection: identifies when a source updates
Multi-format parsing: HTML, PDF, DOCX, XLSX, JSON, XML
Configurable on any vertical domain

RAG Engine

End-to-end Retrieval-Augmented Generation pipeline with hybrid search and multi-collection support.

Semantic chunking with configurable overlap
Vector embeddings (open-weight models or APIs)
Hybrid search: semantic ranking + full-text (Meilisearch)
Multi-collection for separate domains
Support for multiple source types

Knowledge Graph

Multi-type relational graph, battle-tested in production on enterprise-scale datasets.

Typed nodes and edges
N-hop search (2, 3, 4-hop relationships)
Path finding between entities
Interactive drill-down from graph to source documents
Scales to tens of thousands of nodes

Explorer & Dashboard

Interactive views and customizable dashboards with integrated AI chat.

WebGL graph rendering for large-scale graphs
Thematic views: heatmap, timeline, Sankey, treemap
Domain-specific dashboards
Integrated AI chat with tool use on Knowledge Graph + RAG
Radar and comparative analysis

Differentiators

Three innovations that set us apart

Proprietary MCP Server

We build a custom MCP Server that exposes your data, your tools and your processes to any AI — while keeping full control over what goes in and what comes out. The AI becomes an intelligent interface sitting on top of your systems.

Why it matters: MCP is the emerging standard for AI to communicate with enterprise tools. Having your own MCP Server means you decide how the AI accesses data, tools and processes: you're not tied to a third-party platform that changes the rules whenever it wants.

Intelligent Anonymization

Anonymization and pseudo-anonymization layer integrated into the MCP. Your sensitive data is replaced with consistent aliases before leaving the perimeter, and automatically restored in the result. GDPR-compliant by design.

Why it matters: You can use external AI (Claude, GPT) even on your most sensitive data without ever truly exposing it. Critical if you operate in regulated sectors or in Public Administration: data stays in, AI answers come out.

Intelligent AI Routing

The system automatically decides whether to use the internal AI (on-premise, zero cost) or market AI (Claude, GPT) based on task type, data sensitivity and complexity. Maximum power, minimum risk, optimized costs.

Why it matters: You don't have to choose between on-premise and cloud: the system picks the best option case by case. You get top performance on complex tasks and protect data where it really matters.

Open Source

Open stack, zero lock-in

PostgreSQL, Meilisearch, Ollama, open-weight models. Zero vendor lock-in. If tomorrow you want to manage everything in-house, you can — no strings attached.

€0

vendor lock-in

-70%

vs API costs after year one

∞

scalability: decreasing cost per query

Let's start here

Every transformation starts with a conversation.
Tell us your challenge: together we'll find the right solution.

Let's Talk Download the Long Read