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The SmallPond Platform

SmallPond provides a configurable DNA database architecture that automatically generates investigative matches in real time.

Instead of relying on static database structures, SmallPond separates how profiles are stored from how they are compared, allowing laboratories and agencies to design systems aligned with their operational, legal, and investigative requirements.


Core Concepts

SmallPond is built around a small number of core concepts:

DNA Profile

A digital representation of genetic markers used for comparison.

Profile Pond

A logical container that defines where profiles are stored.

Matching Net

A configurable rule defining which ponds are compared and how.

Match Result

The outcome of comparisons, producing investigative leads.


1. System Configuration

Before DNA profiles are ingested, SmallPond is configured by authorized administrators.

This configuration defines how profiles are organized and how matching occurs, ensuring alignment with operational workflows, legal requirements, and agency policies.

Configuration includes:

  • Defining Ponds (data organization)
  • Defining Nets (matching logic)

These definitions are typically established based on:

  • Investigative workflows
  • Laboratory procedures
  • Applicable legislation

Profile Ponds

Ponds define where DNA profiles are stored.

  • Known Offenders
  • Arrestees
  • Forensic Evidence
  • Missing Persons
  • Unidentified Remains
  • Elimination Databases

Matching Nets

Nets define how profiles are compared.

  • Which ponds are compared
  • Matching stringency and thresholds
  • Cross-pond and intra-pond comparisons

Matching Nets

Matching behavior in SmallPond is defined by configurable rules called Matching Nets.

A Net specifies:

  • Which ponds should be compared
  • The matching stringency applied

Examples include:

Net Ponds Compared Stringency
Investigative Lead Net Evidence ↔ Known Offenders High
Evidence Correlation Net Evidence ↔ Evidence Medium
Missing Persons Net Missing Persons ↔ Unidentified Remains Medium

Nets can connect two or more ponds, enabling agencies to define matching strategies aligned with investigative objectives and legal requirements.


Why This Matters

Traditional DNA database systems tightly couple data storage and matching logic, limiting flexibility and slowing adaptation to new workflows or legal requirements.

SmallPond’s separation of Ponds and Nets allows agencies to:

  • Adapt matching strategies without restructuring data
  • Support multiple investigative workflows simultaneously
  • Align database behavior with jurisdictional requirements
  • Scale from small deployments to national systems

2. DNA Profiles Enter the System

After the system has been configured, DNA profiles can be ingested from multiple operational workflows.

Profiles may originate from:

  • Rapid DNA instruments used in booking stations or field deployments
  • Traditional laboratory workflows using high-volume forensic instruments
  • External partner databases or collaborative networks

Regardless of source, profiles are normalized and securely ingested into the SmallPond platform.

SmallPond is instrument-agnostic, allowing agencies to integrate Rapid DNA and traditional laboratory pipelines within the same investigative environment.


3. Profiles Are Placed into Ponds

As profiles are ingested into SmallPond, they are placed into a designated Pond.

The destination pond is determined by the user or workflow responsible for importing the profiles.

This may occur through manual entry, batch import, or automated ingestion processes configured by the laboratory.

Profile Source Typical Pond
Rapid DNA Booking Station Arrestees
Laboratory Evidence Workflow Forensic Evidence
Missing Persons Program Missing Persons

This ensures profiles are organized according to operational procedures and governance policies.


4. Automatic Matching

Once a profile is stored in a pond, SmallPond automatically applies all Matching Nets that involve that pond.

This means:

  • Matching occurs immediately upon profile ingestion
  • No manual search initiation is required
  • Continuous evaluation of new profiles against existing data

This enables rapid identification of investigative leads.


5. Investigative Results

Each Net may generate match results depending on the configured comparison rules and stringency.

Results may include:

  • High-confidence matches
  • Candidate matches
  • Investigative leads for further analysis

These results are presented to investigators and analysts to support:

  • Criminal investigations
  • Missing persons identification
  • Cross-agency collaboration

The SmallPond Model

Conceptually, the system operates as follows:

System Configuration (Ponds + Nets)
        ↓
Profiles Enter System
        ↓
Profiles Assigned to Ponds
        ↓
Nets Automatically Applied
        ↓
Investigative Matches Generated

Scalability

SmallPond deployments range from small local DNA programs to national forensic databases, all powered by the same high-performance matching engine.

Deployment Type Typical Scale Example Use
Local Programs 5,000 – 50,000 profiles Rapid DNA programs, local law enforcement databases
Regional Programs 100,000 – 1,000,000+ profiles State or small national forensic DNA databases
National Databases Millions of profiles National identification systems and large investigative datasets

Regardless of database size, SmallPond’s proprietary matching algorithms allow investigators to search very large datasets and identify potential matches in milliseconds.


SmallPond separates data organization from matching logic, enabling real-time investigative matching at any scale.