VERDANDI

Automated Intelligence
Aggregation.

Multi-source collection and structuring of publicly available data into actionable intelligence profiles.

From Raw Data to Actionable Intelligence

Intelligence work has always been about connecting fragments. A property record here, a satellite image there, a regulatory filing somewhere else. The data exists — scattered across dozens of public sources, each with its own format, its own access method, its own update schedule. Analysts spend more time hunting for data than analyzing it.

Verdandi automates the collection layer. It pulls from public records databases, satellite imagery providers, government filings, and open-source datasets — then structures everything into normalized intelligence profiles that downstream systems can consume immediately. No manual data wrangling. No copy-paste from PDFs.

The system is engineered for portfolio scale. Hundreds of targets can be enriched simultaneously, with historical change detection that flags what shifted since the last collection cycle. When a zoning classification changes, a new permit is filed, or a structure appears in satellite imagery — Verdandi surfaces it before an analyst has to go looking.


Source to Intelligence in Four Stages

Every collection operation follows the same pipeline. Raw data enters, structured intelligence exits.

01
Acquire
Automated collection from public records, satellite providers, and government databases. API-driven where available, structured scraping where not.
02
Normalize
Raw data mapped to a common schema. Addresses standardized, dates unified, identifiers reconciled across sources. Provenance metadata attached to every record.
03
Correlate
Records matched across sources using address normalization, name variant matching, and identifier cross-referencing. Fragmented data consolidated into unified profiles.
04
Deliver
Structured intelligence profiles exported in standard formats — JSON, CSV, GeoJSON — ready for downstream system consumption without middleware.

Technical Capabilities

Six subsystems operating in concert. Each is independently configurable and deployed across the full collection infrastructure.

VD-01

Multi-Source Data Enrichment

Automated collection from public records, satellite imagery, and government databases. Each data source is normalized into a common schema, deduplicated, and tagged with provenance metadata so every data point traces back to its origin. No black-box aggregation — every enrichment is auditable.

VD-02

Cross-Source Record Matching

Fragmented data sources reference the same entities differently — variant spellings, outdated addresses, partial identifiers. Verdandi matches records across sources using address normalization, name variant detection, and identifier cross-referencing to build consolidated profiles from scattered fragments.

VD-03

Structured Output for System Integration

Intelligence profiles formatted for direct consumption by downstream systems — GIS platforms, case management tools, analytical dashboards. Standard export formats (JSON, CSV, GeoJSON) with configurable field mapping. No middleware translation layer required.

VD-04

Portfolio-Scale Batch Processing

Single-target lookups are table stakes. Verdandi processes hundreds of targets in parallel — enriching entire portfolios, jurisdictions, or watchlists in minutes rather than weeks. Queue-based architecture with progress tracking, retry logic, and partial-result delivery for time-sensitive operations.

VD-05

Historical Change Detection

Every collection cycle is diffed against the previous state. Verdandi maintains temporal snapshots and surfaces precisely what changed — new filings, ownership transfers, permit modifications, structural changes visible in imagery. Analysts see deltas, not static dumps. Configurable alert thresholds for material changes.

VD-06

Satellite Imagery Integration

Geographic correlation between structured data and satellite imagery. Overlay property boundaries, infrastructure footprints, and change-detection heatmaps on high-resolution imagery. Multi-temporal comparison for environmental assessment and facility verification.

100s
Targets enriched per batch cycle
Minutes
Not weeks. Portfolio-scale turnaround.
Full
Provenance chain on every data point

VD-ARCH System Architecture

Five processing layers, each independently scalable. Data enters at the top, structured intelligence exits at the bottom.

VD-L1
Collection Layer
OSINT feeds, API integrations, document ingestion pipelines, satellite imagery providers. Automated collection from public records databases, government filings, and open-source datasets with configurable scheduling and rate limiting.
VD-L2
Normalization Layer
Schema mapping, address standardization, deduplication, entity resolution. Raw data from dozens of sources mapped to a common data model with provenance metadata attached to every field. Name variant matching and identifier cross-referencing across jurisdictions.
VD-L3
Analysis Engine
Pattern detection, anomaly scoring, trend analysis, historical change detection. Temporal diff engine compares each collection cycle against previous state, surfacing ownership transfers, permit modifications, and structural changes before analysts go looking.
VD-L4
Storage Layer
Encrypted PostgreSQL with row-level security, vector embeddings for semantic search, full audit log with immutable write-ahead. Every query, every access, every modification recorded. Configurable retention policies aligned to agency requirements.
VD-L5
Delivery Layer
RBAC-filtered dashboards, RESTful and GraphQL API endpoints, automated alerting. Downstream consumers receive only the data their role permits. Standard export formats — JSON, CSV, GeoJSON — with configurable field mapping and no middleware required.

VD-INT Integration Map

External system connections via standard protocols. Each integration is independently configurable.

VERDANDI INTELLIGENCE HUB HSIN HTTPS / REST USASpending.gov REST API Federal Register REST API SAM.gov Entity REST API Agency SFTP Feeds SFTP / SCHEDULED STIX / TAXII THREAT FEEDS
HSIN Homeland Security Info Network — HTTPS/REST
USASpending.gov Federal spending data — REST API
Federal Register Regulatory filings & notices — REST API
SAM.gov Entity Entity management — REST API
Agency SFTP Feeds Scheduled bulk data transfers — SFTP
STIX / TAXII Structured threat intelligence — Threat Feeds

VD-STACK Technology Stack
CategoryTechnology
DatabasePostgreSQL with Row-Level Security
SearchVector embeddings + full-text indexing
APIRESTful + GraphQL endpoints
EncryptionAES-256-GCM at rest, TLS 1.3 in transit
AuthRBAC with row-level enforcement
ProcessingQueue-based batch with retry logic
ExportJSON, CSV, GeoJSON

VD-METRICS System Metrics
Multi-Format
Data Source Ingestion
Public records, satellite imagery, government filings, OSINT feeds — all normalized to common schema
Sub-Second
Query Response Target
Pre-indexed intelligence profiles served from PostgreSQL with vector search for semantic queries
AES-256
Encryption Standard
AES-256-GCM at rest, TLS 1.3 in transit. Row-level security enforced at the database layer
7-Year
Default Audit Retention
Configurable retention aligned to agency requirements. Immutable write-ahead audit log on every access

VD-COMPLY Compliance Mapping

Security controls aligned to NIST 800-171 Rev. 2 families relevant to intelligence aggregation operations.

Control FamilyIDImplementationStatus
Access Control 3.1 Role-based access control with row-level database enforcement. Users see only data their role permits. Aligned
Audit & Accountability 3.3 Every query, access, and modification logged with immutable write-ahead. Full provenance chain on all data points. Aligned
Media Protection 3.8 AES-256-GCM encryption at rest for all stored intelligence data. Encrypted backups with key rotation. Aligned
System & Comms Protection 3.13 TLS 1.3 on all data in transit. Network segmentation between collection, processing, and delivery layers. Aligned
Identification & Auth 3.5 Multi-factor authentication on all operator accounts. Session management with configurable timeout policies. Aligned

VD-MESH Platform Ecosystem

Verdandi intelligence feeds directly into the broader Tereda Labs platform — AI-assisted analysis through IRONWRAITH, geospatial correlation via SPECULUM, threat detection with HELL HOUND. Field data flows in through SILTWIRE, communications are handled by TESSERA, and the entire infrastructure runs on FORGE architecture.

VERDANDI INTELLIGENCE IRONWRAITH AI DECISION SPECULUM SPATIAL HELL HOUND THREAT DEF SILTWIRE FIELD OPS TESSERA COMMS FORGE PLATFORM
VERDANDI IRONWRAITH SPECULUM HELL HOUND SILTWIRE TESSERA FORGE

Federal Application

Pre-Acquisition Due Diligence at Scale

Federal agencies routinely assess properties, facilities, and infrastructure across entire jurisdictions — environmental reviews, base realignment studies, disaster recovery planning. Each assessment requires aggregating records from county assessors, state regulatory agencies, federal databases, and commercial satellite providers. Verdandi automates this collection layer, reducing weeks of analyst time to a single batch operation.

Output integrates directly with GIS platforms and case management systems already in use. No format conversion, no manual data entry, no copy-paste from PDF reports.


Applicable Domains

Verdandi adapts to any domain where publicly available data needs to be collected, structured, and analyzed at scale.

Federal Intelligence Law Enforcement Due Diligence Facility Assessment Environmental Monitoring Infrastructure Planning

Discuss Intelligence Capabilities

Architecture review with the engineers who built it. No sales deck. No demo theater.