rfi_13363.pdf

County of San Diego - REQUEST FOR INFORMATION (RFI) 13363

RFI No. 2026-SD-ABIS-Mobile Page i 07/16/2026

REQUEST FOR INFORMATION:

Issued September 16, 2026

SAN DIEGO COUNTY

AUTOMATED BIOMETRIC IDENTIFICATION SYSTEM (ABIS) and FIELD IDENTIFICATION DEVICE SOLUTION (MobileID)

RFI No. 2026-SD-ABIS-Mobile Page ii 07/16/2026

Table of Contents

1. INTRODUCTION / OBJECTIVE / PURPOSE

A. Agency Liability and Confidential Information

B. California Public Records Act (CPRA) Compliance

2. BACKGROUND INFORMATION / HISTORY

3. SCHEDULE OF EVENTS AND TIMELINE

4. GENERAL REQUIREMENTS

5. RESPONDENT PROFILE and SIGNATURE BLOCK

Appendix A: ABIS Solution

A. Corporate Background and Law Enforcement References

B. Advanced Modalities and Technology Roadmap

C. Core Architecture, Cloud, and Infrastructure

D. Security, Encryption, and CJIS Policy

E. Interoperability, Open Standards, and NIEM Compliance

F. Algorithmic Performance and Multi-Modal Matching

G. Forensic Latent and Quality Control Interfaces

H. Multi-Vendor Support, Cybersecurity, and Governance

I. Professional Services: Implementation, Conversion, and Maintenance

Appendix B: MobileID Solution

A. Corporate Background and Law Enforcement References

B. Security, Encryption, and CJIS Policy

C. MobileID Fleet Operations and Field Durability

D. Professional Services: Implementation and Maintenance

J. Multi-Vendor Support, Cybersecurity, and Governance

Appendix C: Technical Glossary and Standards

RFI No. 2026-SD-ABIS-Mobile Page 1 of 15 07/15/2026

SAN DIEGO COUNTY

AUTOMATED BIOMETRIC IDENTIFICATION SYSTEM (ABIS) and

FIELD IDENTIFICATION DEVICE SOLUTION

1. INTRODUCTION / OBJECTIVE / PURPOSE

San Diego County (County) is publishing this Request for Information (RFI) on behalf of the San Diego County Regional Cal-ID. The purpose is to seek current market data related to the latest Automated Biometric Identification Systems (ABIS) and Mobile Fingerprint Capture (MobileID) Solutions.

Information gathered from this RFI will assist the Remote Access Network (RAN) Board and regional stakeholders in engineering functional and architectural baselines before launching a formal Request for Proposal (RFP). Vendors should respond to all parts of the RFI that apply to their offering (see Appendices A and B). For example, vendors should respond to Appendices A and B as they apply: i.e. provide information on ABIS only, on MobileID only, or on both ABIS and MobileID.

A. Agency Liability and Confidential Information This RFI is exclusively a request for information and no contractual obligation on behalf of the County whatsoever shall arise from the RFI process. The RFI does not constitute a Request for Proposal (RFP), Request for Offer (RFO), Invitation for Bid (IFB), or other procurement solicitation, nor does it constitute a commitment to issue any solicitation in the future.

B. California Public Records Act (CPRA) Compliance Pursuant to the California Public Records Act (CPRA) (California Government Code § 7920.000 et seq.), materials contained in vendor responses are subject to public inspection and disclosure. If a Respondent asserts that any material in its response is confidential or proprietary information, the Respondent must clearly mark the applicable pages of the submission in boldface type to indicate each claim of confidentiality and include the word "CONFIDENTIAL" at the top of the page.

2. BACKGROUND INFORMATION / HISTORY

The San Diego County CAL-ID currently supports a regional biometric ecosystem that processes criminal bookings, applicant clearances, and high-volume forensic latent print workflows. The central infrastructure interfaces directly with the local Records Management Systems (RMS) and the Jail Information Management System (JIMS), passing identity transactions downstream to the California Identification System (Cal-ID), California Department of Justice (Cal DOJ), and the FBI Next Generation Identification (NGI) database.

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The current environment utilizes a central ABIS for matching infrastructure (Thales CABIS 6), MobileID devices and middleware (Thales), local Livescans (Idemia), and mugshot components (DataWorks Plus).

The scope for this project includes modernization for the following components:

Core Biometric Systems: The backend architecture, NIST archival storage, and matching engines.

Custodial Operations: System for biometric verification at intake and release verification at detention facilities.

Field Operations: MobileID technologies for patrol officers and field investigations and specialized solutions for the Medical Examiner’s Office.

Interoperability Infrastructure: Middleware and interfaces enabling data exchange between the County’s Integrated Justice System (e.g., JIMS), California DOJ (CAL- DOJ), and Homeland Security(Hart/Ident) and the FBI (NGI).

3. SCHEDULE OF EVENTS AND TIMELINE

Milestone Event Timeline / Contact Information Target

RFI Release Date September 16, 2026

Deadline for Vendor Questions/Clarifications

Close of Business: September 30, 2026 - 5:00 P.M. PST

SDSO Response to Questions/Clarifications

Close of Business: October 9, 2026 - 5:00 P.M. PST

Deadline for Electronic Submission of

RFI

October 16, 2026 - 5:00 P.M. PST

Point of Contact Jack Leedham, Procurement Contracting Specialist (jackt.leedham@sdcounty.ca.gov)

Submission Via electronic upload to Buynet before the Date and Time listed in Schedule. (https://sdbuynet.sandiegocounty.gov)

4. GENERAL REQUIREMENTS

The replacement solution(s) described in your offering(s) must natively accommodate the baseline capabilities and core technical features outlined below:

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Standards Compliance: Complete alignment with FBI Criminal Justice Information System (CJIS) Security Policies, Electronic Biometric Transmission Specifications (EBTS), and ANSI/NIST-ITL 1-2011/2015 image and data elements.

System Availability: Uninterrupted continuous availability (24x7x365) across booking locations, backed by an active-passive or active-active secondary disaster recovery environment.

Authentication and Access: Granular access controls, Multi-Factor Authentication (MFA), and secure administrative profiles mapped to distinct public safety roles.

Indelible Auditing: Cryptographically secure, unalterable transaction and user logging to defend the forensic chain of custody for all biometric inquiries and modifications.

Automated Monitoring: Self-healing and continuous background health checks that actively alert agency and cleared vendor IT administrators regarding processing queue latencies and system errors.

All responses must also take the following into account:

Capability Component Legacy System Profile Target ABIS & MobileID Requirement

Core Architecture Local On-Premise (Monolithic) Secure CJIS-Compliant Cloud/Cloud- Hybrid Infrastructure

Biometric Modalities Tenprint, Palmprint, Latent, and 2-Finger Matching

Tenprint, Palmprint, Latent, 2-Finger, Mugshot, and Iris with matching and facial recognition

MobileID IOS/Android bluetooth phone/tablet connected for searching.

FBI-PIV and CJIS compliant, centrally managed queues, enterprise MDM agnostic, at a minimum finger and face supported.

Workflow Management Fixed workflows Drag-and-drop orchestration engine for custom routing rules

Search Parameters Scalable without redesign Scalable without redesign

Disaster Recovery Site Manual cut-over Open to vendor solutions

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5. RESPONDENT PROFILE and SIGNATURE BLOCK

Respondent Profile Component Vendor Document Entry Details

Company Legal Name:

Corporate Street Address:

City / State / Zip Code:

RFI Point of Contact Name:

Official Title:

Direct Contact Phone:

Direct Contact Email:

Company Web Address:

Signature of Authorized Representative: ___________________________________________

Printed Name of Authorized Representative: ________________________________________

Execution Date: _____________________

RFI No. 2026-SD-ABIS-Mobile Page 5 of 15

Appendix A: ABIS Solution Respond to all the following questions.

A. Corporate Background and Law Enforcement References

1) Provide proof of a legally registered corporation with at least three (3) similar contracts that represent active, fully operational large-scale law enforcement deployments serving populations exceeding 1,000,000 residents.

2) Provide contact information for reference law enforcement agencies.

3) Describe your company’s direct experience migrating multi-million record legacy biometric databases into upgraded topologies without data loss or booking operational downtime.

4) What is the differentiator for your company's biometric solution from other comparable solutions currently on the public safety market?

5) Do you plan to subcontract or partner with third parties for core application elements, algorithms, or mobile devices and/or software?

6) If third-party software components are required to exploit the full utility of the solution, explain how your corporate entity manages third-party software releases, bug fixes, updates, and long-term issue resolution.

7) Describe your system’s lifecycle timeline, upgrade, and EOL/EOS policies.

B. Advanced Modalities and Technology Roadmap

1) Describe your solution’s mature capabilities, budgetary modular add-on costs, and performance expectations for:

a) Contactless mobile fingerprinting via smart phone camera lenses, including minimum requirements and any specific brand and model requirements.

b) Iris capture, 1:N searching, and secure storage.

c) Facial recognition processing still photos and video feeds against criminal repositories and watch lists.

d) Latent Enhancement Tools including but not limited to Major Case Prints, Dataset/elimination prints, ACE-V integration.

2) Provide a detailed narrative regarding the incorporation, architecture, and governance of

Artificial Intelligence (AI) and Machine Learning (ML) within your proposed biometric platform.

a) Describe procedures used to preserve integrity of evidence in court and ensure transparency in casework.

b) Describe how AI/ML models are fundamentally integrated into your core matching engine and workflow subsystems. Specify whether these algorithms are developed natively in-house or rely on third-party frameworks.

c) Detail the continuous training pipelines for your AI models. How frequently are new machine learning, neural network layers, etc. deployed to the system, and how does your company ensure that software patches do not introduce regression bugs or latency issues into live production matching queues?

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d) Detail the specific AI-driven tools available within the forensic user interface (UI) to assist latent examiners in processing, enhancing, and resolving complex, low-quality, or distorted friction ridge impressions.

e) How do these AI enhancement tools interface with standard forensic verification methodologies (e.g., ACE-V documentation logs), and do they allow examiners to audit, adjust, or completely override automated algorithmic features?

f) Explain how your platform ensures that AI-enhanced latent images and matching scores remain legally defensible under current standards for scientific evidence (e.g., Daubert or Kelly/Frye standards).

g) Specify how your system prevents data contamination or distortion during image optimization, guaranteeing that the original biometric record remains entirely unaltered for courtroom exhibits.

h) Describe how your AI models prevent implicit demographic bias (e.g., racial, gender, or age-based variations in matching accuracy) across facial recognition and multi-modal matching engine pipelines.

i) Does your solution generate comprehensive, discoverable mathematical audit trails or "explainable AI" logs that can be utilized in a court of law to defend how an algorithm derived a specific candidate list or similarity score?

j) Specify if your models are trained on publicly scraped data or strictly on legally consented, certified public safety data repositories.

k) Describe how your solution leverages AI to automate background system administration, load balancing, and business process orchestration.

l) Detail how AI is used to monitor system transaction queues dynamically, manages self-healing, optimizes search indexing, and proactively alert administrators regarding device health drops or anomalies across the solution.

m) Explain how AI helps automate database maintenance, such as identifying potential duplicate identities, flag filtering poor livescan captures (NFIQ 2.0 alternatives), or running automated compliance purges based on policy or statute-of-limitations rules.

n) Describe your platform's capabilities regarding automated minutiae extraction, quality control and quality metric data collection/reporting.

C. Core Architecture, Cloud, and Infrastructure

1) Does your solution support cloud-hosted, fully on-premise, or a cloud-hybrid architecture? If cloud elements are used, specify CJIS compliance approach.

2) Detail how your platform achieves High Availability (HA) matching engine redundancy at the component layer, separating local failover architecture from secondary Disaster Recovery (DR) operations.

3) Detail how your platform supplies MobileID access and network management capabilities that ensure 24x7 connectivity to ABIS data for field identity checks and jail intake/release.

4) Detail the exact software stack dependencies required by your platform (e.g., microservices framework, queue managers, database indexing models).

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5) Specify whether workstation nodes require native thick-client software installations, Virtual Desktop Infrastructure (VDI), or standard web browsers with or without drivers to interact with custom hardware (e.g. fingerprint scanners).

6) Describe any additional hardware, software, licensing, or peripherals (e.g., Appendix F-certified printers, specialized booking camera arrays) that may need to be purchased outside of a primary contract to take advantage of the full functionality of your solution.

7) Describe your process and approach to driver and firmware updates for vendor provided hardware to ensure security and industry standards are continually met. Describe how this is applied to software maintenance and change order processes.

8) Describe your tools to integrate with other ABIS systems, such as CAL-DOJ Latent Gateway (DOJ and FBI Searching, UL registration, reverse search results, tenprint inquiry, printing), and searching other systems (tenprint and latent workflows) in the region where MOUs are in place.

D. Security, Encryption, and CJIS Policy

1) Explain how your solution implements Multi-Factor Authentication (MFA) and data encryption mechanisms to meet FIPS 140-3 validation requirements for data at rest and in transit.

2) Detail how your platform logs, secures, and maintains an unalterable chain of custody for forensic data and user operations.

3) Describe your system’s ability to integrate with SEIM and SYSLOG.

4) Describe how your solution supports CJIS policy compliance and future update strategy.

5) Describe your compliance with the latest FBI CJIS Security Policy.

E. Interoperability, Open Standards, and NIEM Compliance

1) Describe how your solution mitigates unstructured data mapping risks from legacy core applications (e.g., free-text charge entries in JIMS) to preserve strict validation when sending and receiving data packets to Cal DOJ and FBI NGI.

2) Detail your platform's capability to orchestrate an automated NIST packet, consolidating fingerprint data, palmprints, mugshots, and Scars/Marks/Tattoos (SMTs) into a single logical transaction before submission.

3) Describe your solution’s level of compliance and native alignment with ANSI/NIST-ITL and NIEM standards, evaluating the ease of secure data exchange with local JIMS, RMS, Cal-ID, Cal DOJ, and the FBI NGI.

4) Describe your application's ability to seamlessly parse and transmit standardized exchange files (ANSI/NIST-ITL 1-2011/2015) to execute bidirectional partner agency inquiries.

5) Explain how the architecture maps, publishes, and ingests standardized XML, JSON, and NIST data packets to interface with local RMS and JIMS without relying on proprietary translation layers.

6) Describe MobileID integration with the regional ABIS, Cal-DOJ, and the FBI NGI Repository for Individuals of Special Concern (RISC) database.

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F. Algorithmic Performance and Multi-Modal Matching

1) Detail your matching ability to expand without system re-engineering to accommodate scaling response times, throughput, and database size for Tenprint-to-Tenprint (TP:TP), Tenprint-to-Latent (TP:UL), 2-Finger-to-Tenprint (2F:TP), Latent-to-Latent (LT:UL),and Latent-to-Tenprint (LT:TP) searches, inclusive of searching palmprints.

2) Detail your matching ability to expand without system re-engineering to accommodate scaling response times, throughput, and database size for facial recognition and iris searches.

3) What are the most recent formal independent benchmark rankings (e.g., NIST MINEX, FRVT) your biometric algorithms have achieved? Detail where these results are officially posted and your release cadence for algorithmic updates to customer deployed versions of current software and new project/customer installations.

4) Describe how your system allows for individualized algorithm tuning to optimize search response time, accuracy, and avoid missing matching candidates.

6) Describe your facial recognition capabilities to support criminal investigation lead generation, regional watchlists, custodial tracking, and crime lab forensic analysis seamlessly via role-based access.

G. Forensic Latent and Quality Control Interfaces

1) Describe the forensic examiner User Interface (UI), specifically detailing native support for side-by-side latent print editing, automated 1:1 image resizing, and integrated ACE-V verification workflow documentation tools.

2) Explain how your quality control engine utilizes NFIQ 2.0 (or equivalent) metrics to evaluate incoming captures. Detail your platform's handling of borderline quality thresholds, including guided operator remediation loops and auditable supervisor-override rules.

3) Detail how your solution manages data conversion of latents to prevent record corruption or loss within regional Unsolved Latent database.

4) Describe advanced quality control processes standardly available in your toolsets.

Include any option(s) for correcting poor quality prints taken during booking (for example one bad ring finger roll).

H. Multi-Vendor Support, Cybersecurity, and Governance

1) Support Levels: Define your standard support levels and the typical tasks and technical background required for each level.

2) Confirm your approach to an agency-led support posture where the County allocates technical support personnel to manage Tier 1 and Tier 2 triage. Does your model support a direct escalation path where local support staff route complex tickets directly to Tier 3 vendor support? Assume Level 1 and Level 2 support provides daily workstation, server, and vendor application management, excluding specialists (like a DBA).

3) Describe how your company handles multi-vendor integration layers (e.g., Idemia, DataWorks Plus, Thales, JMS vendors, etc.), each with different components of the ecosystem.

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4) Explain your 'Evergreen' lifecycle roadmap. Does your standard maintenance program include operating system (OS) compatibility patches and algorithm updates without triggering billable Change Requests? Is it the same for on premise and cloud?

I. Professional Services: Implementation, Conversion, and Maintenance

1) Data Migration Strategy (Conversion Plan):

a) Describe your expertise, high-level structural flow, and data migration strategy for moving millions of historical records (biometric images, unsolved latent prints, and associated metadata) with zero data loss and zero operational booking downtime.

b) Describe your expertise and strategy for converting, migrating, and aligning different databases. For example, converting booking and unsolved latent databases in an ABIS, and bridging data gaps (e.g. separate mugshot data in one official NIST record for the booking event).

c) What is your pricing structure for data migrations and conversions of existing data sets?

2) Project Management Schedule and Timeline:

a) Describe your project management methodology, software tools, or other delivery mechanisms to ensure timely, on-budget completion and clear communication.

b) Include a high-level conceptual project schedule mapping out the recommended deployment timelines. State all critical assumptions required for this schedule to be achieved.

c) Include estimated durations for core application configuration, database cleaning (deduplication, and error correction of historical records), parallel execution testing, User Acceptance Testing (UAT), Train-the-Trainer training, and full agency-wide cut-over.

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Appendix B: MobileID Solution

A. Corporate Background and Law Enforcement References

1) Provide proof of a legally registered corporation with demonstrated law enforcement experience.

2) Provide contact information for US law enforcement client references with recent (less than 5 years) deployment of more than 500 mobile devices deployed in the field. If you do not have a deployment with more than 500 devices, you may provide a reference for the largest installation.

3) What are the differentiators for your company's MobileID solution from other comparable solutions currently on the public safety market?

B. Security, Encryption, and CJIS Policy

1) Detail how your middleware logs, secures, and maintains information for MobileID transaction data for user operations.

2) Describe your compliance with the latest FBI CJIS Security Policy, including FIPS 140-3 encryption protocols, robust multi-factor authentication, and immutable evidentiary logs.

3) Describe MobileID integration and response times for 2-finger searches with the regional

ABIS, Cal-DOJ, and the FBI NGI Repository for Individuals of Special Concern (RISC) database.

C. MobileID Fleet Operations and Field Durability

1) Provide detailed specifications for your MobileID hardware and software. Specify if your solution requires a dedicated software application deployed on Agency-managed (multiple agencies in the county with different MDMs) smartphones (iOS/Android) or includes an all-in-one standalone device.

2) Provide independent laboratory verification for MIL-STD-810H shock compliance, Ingress Protection (IP67 or higher), and chemical resistance against standard public safety disinfectants (e.g., CaviCide, bleach, and isopropyl alcohol).

3) Describe MobileID operational ergonomics tailored to field deputies working under high-stress conditions.

4) Detail how your middleware supplies and monitors MobileID access and network management to ensure 24x7 connectivity to ABIS for field identity checks and jail intake/release.

5) Explain how your devices handle connectivity dropouts across public safety networks (FirstNet Band 14, Verizon Frontline), including their ability to support localized 1:1 verification cache look-ups in completely offline settings.

6) Detail your platform's capacity to support a prioritized queue, allowing a field user (e.g., medical examiner) to push an ambiguous or sub-threshold scan to a remote fingerprint examiner for real-time visual adjudication.

7) Describe sustainability and lifecycle timelines, upgrade, and EOL/EOS policies.

8) Discuss software support frameworks and long-term Evergreen refresh lifecycles.

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9) Describe your tools to integrate with other ABIS systems, such as CAL-DOJ Mobile Gateway, FBI RISC searching, and searching other systems in the region where MOUs are in place.

D. Professional Services: Implementation and Maintenance

1) Project Management Schedule and Timeline:

a. Describe your project management methodology, software tools, or other delivery mechanisms to ensure timely, on-budget completion and clear communication.

b. Include a high-level conceptual project schedule mapping out the recommended deployment timelines.

c. Include estimated durations for core application configuration, database cleaning, parallel execution testing, User Acceptance Testing (UAT), Train-the-Trainer training, and full agency-wide cut-over.

J. Multi-Vendor Support, Cybersecurity, and Governance

5) Support Levels: Define your standard support levels and the typical tasks and technical background required for each level.

6) Confirm your approach to an agency-led support posture where the County allocates technical support personnel to manage Tier 1 and Tier 2 triage. Does your model support a direct escalation path where local support staff route complex tickets directly to Tier 3 vendor support? Assume Level 1 and Level 2 support provides daily workstation, server, and vendor application management, excluding specialists (like a DBA).

7) Describe how your company handles multi-vendor integration layers (e.g., Idemia, DataWorks Plus, Thales, etc.), each with different components of the ecosystem.

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Appendix C: Technical Glossary and Standards

Term Definition

ABIS Automated Biometric Identification System

ACE-V Analysis, Comparison, Evaluation, and Verification

AI/ML Artificial Intelligence/Machine Learning

ANSI American National Standards Institute

BCP Biometrics Consulting Partners LLC

CABIS Cogent ABIS

Cal DOJ California Department of Justice

Cal-ID California Identification System

CJIS Criminal Justice Information Services

Cogent Current AFIS, livescan, and mugshot biometrics solution provider

CPRA California Public Records Act

DNA Deoxyribonucleic Acid

DNS DNA Network Service – California DNA database.

DOB Date of Birth

DR Disaster Recovery

EBTS Electronic Biometric Transmission Specification

EOL End of Life

EOS End of Support

FBI Federal Bureau of Investigation

FIPS Federal Information Processing Standards

HA High Availability

ITL Information Technology Laboratory

JIMS Jail Information Management System

JSON JavaScript Object Notation

MDC Mobile Data Computer

MFA Multi-Factor Authentication

NFIQ NIST Fingerprint Image Quality

NIEM National Information Exchange Model

NIST National Institute of Standard

NGI Next Generation Identification

RAN Board Remote Access Network Board

RFI Request for Information

RFP Request for Proposal

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Term Definition

RISC Repository for Individuals of Special Concern

RMS Records Management System

UI User Interface

ULF Unsolved Latent File

VDI Virtual Desktop Infrastructure

(End of RFI Document)