Overview

RES (Registr ekonomickych subjektu) is the statistical register of all economic subjects in the Czech Republic, maintained by the Czech Statistical Office (Cesky statisticky urad, CSU) under Act No. 89/1995 Coll., on the State Statistical Service, as amended. Unlike administrative registers such as ARES that aggregate data from business registries, RES provides the statistical classification view of the Czech economy. Every entity assigned an ICO (Identification Number of a Person) is recorded in RES with standardized statistical classifications including CZ-NACE economic activity codes, institutional sector classification, organizational form, and employee count categories.

The register contains approximately 2.8 million economic subjects, encompassing both active and inactive entities across all sectors of the Czech economy. RES serves as the authoritative national source for economic activity classification and forms the foundation of the Czech Republic's statistical reporting obligations to Eurostat. For OSINT analysts, RES provides intelligence that no other Czech register delivers: the precise industry classification of entities, their employee count ranges, and their institutional sector positioning within the European System of Accounts (ESA 2010) framework. This data is essential for sector-level competitive analysis, industry mapping, economic research, and due diligence verification of claimed business activities.

The legal basis for RES is established in Section 20 of Act No. 89/1995 Coll., which mandates the CSU to maintain a register of economic subjects for statistical purposes. Data flows into RES from administrative sources including the Commercial Register (Justice.cz), the Trade Licensing Register (RZP), the Tax Administration, and sector-specific registries. The CSU enriches this data with statistical classifications that are standardized across the European Union.

Data Sources and Coverage

RES aggregates data from multiple authoritative administrative sources and enriches them with standardized statistical classifications. The register covers all legal entities and natural persons engaged in economic activity in the Czech Republic.

Data Type	Description	Source
ICO	Company identification number (8-digit)	Administrative registers
Entity Name	Official registered name	Commercial Register / RZP
Legal Form	Standardized legal form code	CSU codelist
CZ-NACE Activities	Primary and secondary economic activity codes	CSU classification
Employee Category	Employee count range (0, 1-5, 6-9, ..., 5000+)	CSU statistical surveys
Institutional Sector	ESA 2010 sector classification	CSU classification
Address	Registered seat with RUIAN address code	RUIAN address register
Founding Date	Date of entity creation	Administrative registers
Dissolution Date	Date of dissolution (if applicable)	Administrative registers
Organizational Form	Legal organizational structure type	CSU codelist

Key Classification Systems

Classification	Standard	Purpose	Levels
CZ-NACE	Based on EU NACE Rev. 2	Economic activity classification	4 levels (section to class)
CZ-COPNI	National classification	Non-profit institutions classification	3 levels
CZ-NUTS	EU NUTS standard	Regional statistical classification	4 levels
Legal Form	CSU codelist	Legal entity type (s.r.o., a.s., etc.)	3-digit codes
Size Category	CSU bands	Employee count categorization	12 categories
Institutional Sector	ESA 2010	National accounts sector classification	4-digit codes

Czech Legal Context

RES operates within a well-defined legal framework:

Act No. 89/1995 Coll. (on the State Statistical Service) - primary legislation establishing the register
Act No. 563/1991 Coll. (on Accounting) - defines reporting obligations that feed into RES
Regulation (EC) No. 177/2008 - EU regulation on business registers for statistical purposes
Czech Statistical Office Decree - detailed operational rules for register maintenance
GDPR compliance - natural person data in RES subject to Act No. 110/2019 Coll. (on personal data processing)

Technical Architecture

The RES technical infrastructure operates within the CSU's statistical information system. Data flows from administrative registers through a harmonization pipeline that applies statistical classifications before storage.

Administrative Sources                Statistical Classification
+------------------+                 +----------------------+
| Commercial Reg.  |---+             | CZ-NACE Assignment   |
| Trade License    |---+---> RES --> | ESA 2010 Sector      |
| Tax Admin        |---+    Core     | Legal Form Coding    |
| Sector Registries|---+             | Size Category        |
+------------------+                 +----------------------+
                                              |
                                              v
                                     +------------------+
                                     | Public Interface  |
                                     | apl.czso.cz/irsw |
                                     +------------------+

The public interface at apl.czso.cz/irsw provides web-based search functionality. RES data is also accessible through the ARES aggregation layer, which combines RES statistical classifications with data from other administrative registers into a unified XML response.

Component	Technology	Purpose
Data Intake	Batch feeds from administrative registers	Raw entity data collection
Classification Engine	CSU internal system	Statistical code assignment
Storage	Relational database	Entity records with classifications
Public Interface	Web application at apl.czso.cz	User-facing search and lookup
ARES Integration	XML data exchange	Structured API access via ARES
Open Data	CSV/XML exports	Bulk data downloads

API Integration

RES does not provide a standalone REST API. Data access is available through the web interface at apl.czso.cz/irsw and through the ARES XML service, which includes RES classification data in its responses. The Prismatic adapter handles both access methods transparently.

defmodule Prismatic.Osint.Res do
  @moduledoc """
  Adapter for the Czech Register of Economic Subjects (RES).
  Provides statistical classification data for Czech economic entities
  including CZ-NACE activity codes, employee categories, and institutional sectors.
  """

  @doc """
  Look up an entity by ICO and retrieve full statistical classification.
  """
  @spec get(String.t()) :: {:ok, map()} | {:error, term()}
  def get(ico) when is_binary(ico) do
    with {:ok, response} <- fetch_entity(ico),
         {:ok, parsed} <- parse_response(response) do
      {:ok, %{
        ico: parsed.ico,
        name: parsed.name,
        legal_form: parsed.legal_form,
        nace_primary: parsed.nace_primary,
        nace_secondary: parsed.nace_secondary,
        employee_category: parsed.employee_category,
        institutional_sector: parsed.institutional_sector,
        address: parsed.address,
        founded: parsed.founded,
        status: parsed.status
      }}
    end
  end

  @doc """
  Search entities by CZ-NACE code with optional geographic filtering.
  Returns all entities classified under the specified activity code.
  """
  @spec by_nace(String.t(), keyword()) :: {:ok, list(map())} | {:error, term()}
  def by_nace(nace_code, opts \\ []) do
    municipality = Keyword.get(opts, :municipality)

    with {:ok, results} <- search_by_classification(nace_code, municipality) do
      {:ok, Enum.map(results, &normalize_entity/1)}
    end
  end

  @doc """
  Get sector-level statistics for a CZ-NACE code.
  """
  @spec sector_stats(String.t(), keyword()) :: {:ok, map()} | {:error, term()}
  def sector_stats(nace_code, opts \\ []) do
    municipality = Keyword.get(opts, :municipality)

    with {:ok, entities} <- by_nace(nace_code, municipality: municipality) do
      active = Enum.filter(entities, &(&1.status == :active))

      {:ok, %{
        nace_code: nace_code,
        total_entities: length(entities),
        active: length(active),
        by_size: group_by_employee_category(active),
        by_legal_form: group_by_legal_form(active),
        region: municipality
      }}
    end
  end

  @doc """
  Get employee count distribution for a specific NACE sector.
  """
  @spec employee_distribution(String.t()) :: {:ok, map()} | {:error, term()}
  def employee_distribution(nace_code) do
    with {:ok, entities} <- by_nace(nace_code) do
      distribution = entities
        |> Enum.filter(&(&1.status == :active))
        |> Enum.group_by(& &1.employee_category)
        |> Enum.map(fn {category, entities} -> {category, length(entities)} end)
        |> Map.new()

      {:ok, %{nace_code: nace_code, distribution: distribution}}
    end
  end
end

Industry Intelligence Pipeline

defmodule PrismaticPerimeter.Intelligence.IndustryAnalysis do
  @moduledoc """
  Analyzes industry sectors using RES statistical data
  combined with financial intelligence from other Czech registers.
  Supports sector concentration analysis, competitor mapping,
  and economic trend tracking.
  """

  @spec sector_analysis(String.t(), String.t() | nil) :: {:ok, map()} | {:error, term()}
  def sector_analysis(nace_code, region \\ nil) do
    with {:ok, entities} <- Res.by_nace(nace_code, municipality: region),
         {:ok, stats} <- Res.sector_stats(nace_code, municipality: region) do
      top_entities = entities
        |> Enum.filter(&(&1.employee_category in ["50-99", "100-249", "250+"]))
        |> Enum.map(fn entity ->
          {:ok, ares} = Ares.get_full_details(entity.ico)
          Map.put(entity, :ares_data, ares)
        end)

      {:ok, %{
        sector: nace_code,
        region: region,
        statistics: stats,
        top_entities: top_entities,
        concentration: calculate_sector_concentration(entities),
        growth_indicators: analyze_founding_trends(entities),
        analyzed_at: DateTime.utc_now()
      }}
    end
  end

  defp calculate_sector_concentration(entities) do
    active = Enum.filter(entities, &(&1.status == :active))
    large = Enum.filter(active, &(&1.employee_category in ["250+", "1000+"]))
    %{total: length(active), large_entities: length(large), ratio: length(large) / max(length(active), 1)}
  end
end

Use Cases

Competitor Mapping and Industry Intelligence

RES enables systematic identification and analysis of all competitors within a defined industry sector and geographic region. By querying CZ-NACE codes, analysts can enumerate every registered entity in a sector, analyze size distribution, and identify dominant players. This is particularly valuable for market entry assessments and competitive landscape studies.

Identify all competitors in a NACE sector and region
Analyze sector size distribution and concentration indices
Track new entrants and exits in specific industries over time
Combine with ARES for financial details on sector leaders

Economic Research and Statistical Analysis

RES is the primary data source for economic research at the sector and regional levels. Its standardized classifications enable cross-country comparisons within the EU (through NACE harmonization) and longitudinal analysis of Czech economic structure.

Sector-level employment analysis using employee count categories
Regional economic structure mapping across CZ-NUTS regions
Entity creation and dissolution trend tracking for economic cycle analysis
Cross-reference with CEDR subsidy data for sector-specific public support analysis

Due Diligence and Compliance Verification

RES provides independent verification of business activity claims. If an entity claims to operate in a specific industry, RES records reveal the officially registered CZ-NACE codes, which may differ from marketing claims.

Verify claimed business activities against registered NACE codes
Compare entity size claims with registered employee category
Cross-reference legal form with Justice.cz commercial register data
Support KYC/AML processes with verified industry classification

Data Quality and Reliability

Quality Dimension	Assessment	Notes
Completeness	High	All ICO-assigned entities included
Timeliness	Moderate	Dependent on administrative source updates
Accuracy	High	Official CSU classification methodology
Consistency	High	EU-harmonized classification standards
Accessibility	Moderate	Web interface; structured data via ARES
Authority	Definitive	CSU is the sole statistical authority

Data quality considerations specific to RES:

NACE codes may not reflect actual current business activities if the entity has not updated its registration
Employee categories are statistical estimates based on surveys and administrative data, not exact headcounts
Inactive entities remain in the register, which can inflate sector counts if not filtered
Update lag between administrative changes and RES reflection typically spans days to weeks

Platform Integration

Within the Prismatic Platform, RES serves as the statistical classification layer, enriching entity records from other Czech registers with standardized industry and organizational data.

[ARES]          [Justice.cz]      [RZP]
   |                |               |
   v                v               v
+------------------------------------------+
|     Prismatic Entity Resolution Engine    |
|                                          |
|  Entity Record + RES Statistical Layer:  |
|  - CZ-NACE classification               |
|  - Employee category                     |
|  - Institutional sector (ESA 2010)       |
|  - Legal form code                       |
+------------------------------------------+
            |
            v
   [Perimeter Security Rating]
   [Sector Analysis Pipeline]
   [Due Diligence Reports]

Integration touchpoints:

Component	Integration	Data Flow
ARES Adapter	Primary data path	RES data included in ARES XML responses
Entity Resolution	Classification enrichment	NACE codes attached to entity profiles
Perimeter EASM	Sector risk context	Industry classification for security ratings
Due Diligence	Verification layer	Activity and size verification
Analytics	Sector dashboards	Statistical aggregations and trend analysis

NABLA Compliance

RES integration within the Prismatic Platform adheres to NABLA epistemic framework requirements:

Axiom	Implementation
Signal Plurality	RES data cross-referenced with ARES and RZP for multi-source verification
Contradiction Preservation	Discrepancies between RES NACE codes and declared activities preserved and flagged
Provenance Mandatory	All RES data tagged with CSU source and extraction timestamp
Time Decay	Entity classifications timestamped; staleness alerts for data older than 90 days
Unknown Valid	Missing employee categories explicitly represented as unknown, not assumed
Source Independence	RES treated as independent statistical source distinct from ARES administrative layer

Trinity Gate compliance for RES-derived claims:

Structural: Entity-sector relationships form valid DAG in knowledge graph
Logical: NACE classification hierarchy enforced (section > division > group > class)
Formal: Employee category ranges validated against CSU codelist definitions

Performance Metrics

Metric	Target	Typical
ICO Lookup	< 500ms	~200ms (via ARES cache)
NACE Sector Query	< 2s	~1.2s (depending on sector size)
Sector Statistics	< 3s	~2s (aggregation computation)
Employee Distribution	< 2s	~1.5s
Cache Hit Rate	> 80%	~85% (24h TTL for entity data)
Data Freshness	< 7 days	~3 days (administrative source lag)

Caching strategy: Entity-level data cached with 24-hour TTL. Sector-level aggregations cached with 1-hour TTL due to potential changes from entity updates. Full sector statistics regenerated daily.

Czech Administrative Registers

ARES - Administrative entity register with financial data (primary RES access path)
Justice.cz - Commercial register details and corporate filings
RZP - Trade licensing register for license verification
VR.cz - Unified public registry portal

Financial and Subsidy Intelligence

CEDR - Central subsidy register for sector-level subsidy analysis
SZIF - Agricultural subsidy data for primary sector analysis

Entity Verification

Datove Schranky - Entity existence verification via data boxes
Insolvencni rejstrik - Insolvency status cross-reference

Platform Components

OSINT Core - Core OSINT framework and adapter layer
Prismatic Perimeter - EASM with sector-aware security ratings

Connect & Contribute

Created by Tomáš Korcak (korczis) | Open Source under GHL

GitHub | GitLab | LinkedIn | Contact
Developer Portal | Architecture | Meet the Creator

RES

Capabilities

Try RES

Overview

Data Sources and Coverage

Key Classification Systems

Czech Legal Context

Technical Architecture

API Integration

Industry Intelligence Pipeline

Use Cases

Competitor Mapping and Industry Intelligence

Economic Research and Statistical Analysis

Due Diligence and Compliance Verification

Data Quality and Reliability

Platform Integration

NABLA Compliance

Performance Metrics

Czech Administrative Registers

Financial and Subsidy Intelligence

Entity Verification

Platform Components

Connect & Contribute

Intelligence Network

Related Content

Agent Ecosystem

Applications

Doctrine

RES

Capabilities

Try RES

Overview

Data Sources and Coverage

Key Classification Systems

Czech Legal Context

Technical Architecture

API Integration

Industry Intelligence Pipeline

Use Cases

Competitor Mapping and Industry Intelligence

Economic Research and Statistical Analysis

Due Diligence and Compliance Verification

Data Quality and Reliability

Platform Integration

NABLA Compliance

Performance Metrics

Related Resources

Czech Administrative Registers

Financial and Subsidy Intelligence

Entity Verification

Platform Components

Connect & Contribute

Intelligence Network

Related Content

Agent Ecosystem

Applications

Doctrine