5x Time to ValueReduce Data Prep by 80%

Trash In.
Tables Out.

Get your data ready for AI in 3 weeks.

95% of AI projects stay in the lab. Be the 5%.

Forensic Data Standards

Used in regulated industries. Including isolated air-gapped infrastructure.

Full Ownership

You own the ontology, insights, and the structure. No vendor lock-in on your property.

Put Your Data To Work

Discover insights and find patterns in your systems, PDFs, and Excel sheets.

Problem

Data Lakes are Data Swamps.

80% of time in AI projects is spent on working with data. We cut that time by 80%.

Standard AI Project

Black Box.

  • ×Delayed outcome and ROI
  • ×Misses hidden context
  • ×High burn rate
  • ×No data governance
BC Way

The Semantic Engine.

  • 3-Week Time-to-Value
  • Analytics Before Deployment
  • Business Logic Mapped
  • No datapoint missed
Technology

The Networks Notebook.

We build a Semantic Layer between data and end user. Our Networks Notebook engine ingests multimodally (text, images, logs), identifies hidden relationships, and outputs a structured business logic ready for your AI pipeline.

Relationship Schema
Project ID: 8821-X
Swipe
EMAIL_LOGTRANSACTIONS.CSVOFFSHORE_REGARCHIVE_FILESREL: J. SMITHINTEL_REP_01.PDFSUBJ: A. VKOVTX: $4.2M [SWIFT]SHELL_CORP_LTDFIND_KYC_FLAG
Identified Entity
LLM Query
Contextual Data

Multimodal Mapping

Between disparate systems—connecting the invoice in the PDF to the transaction in the SQL database.

2-in-1 Analysis & Ontology

We identify gaps, patterns, and business insights during the process.

Total Compliance

With GDPR, AI Act, any NDA or court regulation.

Process

Results in 3 Weeks.

Get results faster than the others. Let us take a representative sample of your data and return a structured dataset and analysis.

01
Week 1

Scope & Sample

Define the scope and ingest a data sample. Identify the business logic and patterns.

02
Week 2

Ontology Building

Map the relationships and build the Semantic Layer with a knowledge graph.

03
Delivery

The First Package

You get the clean, structured dataset, the Ontology & Relationship Graph, and a Analysis Report.

04
Next Steps

Full Implementation

With the architecture proven, we scale to the full dataset. Ready for AI ingestion.

Your Raw Data

Unstructured Inputs

"scan_004.pdf"
"fw_contract_negotiation.msg"
"legacy_export_2023.csv"
ERP & CRM
Cloud Drives
System logs

Ontology Engine
The Result
Entity Detected

Acme Corp

Verified Vendor
A
Risk Flagged
Policy Violation
Critical
Opportunity Spotted
License Upsell
High
Contract Value$1,250,000
Payment TermsNet 90 (Non-Standard)
Sources
scan_004.pdf (Pg 12)RE: T&C e-mail 12.12.09
Why us

Forensic Standard.

Our analyses serve as evidence in court. If our data structure is precise enough for the justice system, it is safe enough for your business.

Court Admissible

We operate with the rigor of a forensic investigation.

Social and Media Proof

Our work starred on many stages, in industry reports, and publications.

What You Get

  • 1. Clean Structured DatasetSQL/JSON
  • 2. Ontology & Relationship GraphArchitecture
  • 3. Analysis ReportInsights
  • 4. Technical DocumentationPDF
Meet Our Founders
Michał Domański

Michał Domański

CEO

Paweł Gołąb

Paweł Gołąb

CTO

Proven Results

Case Studies.

Logistics

Fraud Detection

SCOPE: Court Admissible

Analyzed driver behavior signals and logistics exchange data to find anomalies.

Outcome

Detected non-compete breach. Used as evidence in court.

Legal & OSINT

Economic Investigation

SCOPE: Forensic Evidence

Structured chaotic dumps of documents, photos, and bank tables for an active investigation.

Outcome

Identified perpetrator via hidden pattern recognition.

Media & TV

Script Continuity Mapping

SCOPE: 1000 Episodes

Mapped character relationships and plot continuity across 1,000 episodes of a long-running series.

Outcome

Reduced production costs & faster writing process.

Ontology Map
1. Ingestion Sources
scan_004.pdf
legacy_db.sql
incident_report.docx
OSINT_report.pdf
behaviour_patterns.csv
financials.xmlPROCESSING
2. Semantic Mapping
Person BPerson ACompany XFRAUD RISK
3. Structured Output
Entity Detected
Fraud Pattern A
Confidence: 98.2%
Identity Resolution
Person A = Person B
Confidence: 96%
Action
Export to SQL
> Download .CSV
Internal Oracle

Corporate Knowledge

Challenge

Unstructured Data Silos

Outcome

Instant answers cited from specific pages.

Strategic Analysis

Intelligence & Investigation

Challenge

Information Overload

Outcome

Traceable chain of custody for intel.

AML & Fraud

Financial Crime

Challenge

Disconnected Logs

Outcome

Visualizing flow of funds to expose laundering.

Policy Adjudication

Insurance & Claims

Challenge

Complex T&Cs

Outcome

Ranked list of valid exclusions with citations.

Infrastructure

Infrastructure Agnostic.

We work where your data lives. Whether you leverage our sovereign GPU network, your existing commercial cloud, or strictly air-gapped metal—our architecture adapts to your terrain.

Commercial Cloud (BYOC)

Already invested in AWS, Azure, or GCP? You retain your billing credits and security groups; we simply bring the intelligence.

Azure / AWS / Google

Sovereign Data Centers

Need H100s or juridical sovereignty? Leverage our partners who provide dedicated compute and Tier-4 security standards.

Priority GPU Access

On-Premise & Air-Gapped

For TS/SCI or highly classified environments. Use pre-configured hardware appliances at the undisclosed location. The system runs completely offline with zero internet connectivity required.

Local Hardware Only
BC Academy

Workforce Enablement.

Data is one part of the equation. People are the other. Transform your teams into active AI power users.

Workshops for both technical teams and executive leadership that ensure long-term adoption of AI.

Curriculum Highlights

Strategic & Technical Tracks

Prompt Engineering StrategyBeginner
AI Governance FrameworksExecutive
LLM Architecture & ToolingTechnical