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SecurityTop 10 Best Police Facial Recognition Software of 2026
Compare police facial recognition software options like SAFR, NEC NeoFace, and Verkada, with tradeoffs for law enforcement teams.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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SAFR is the best pick for police teams that need API-driven 1:N investigative matching because it pairs those workflows with audit trail coverage that records matcher activity and configuration changes, whereas Paravision Face Recognition fits investigators running repeated gallery-to-watchlist searches since it manages template extraction and gallery updates for consistent batch cycles.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
SAFR
Audit trail coverage that records matcher activity and configuration changes tied to identity search operations.
Best for: Fits when agencies need API-driven matching workflows and strong audit trail coverage for investigative searches.
NEC NeoFace
Editor pickRole-based access plus audit trails tied to matching events and result handling.
Best for: Fits when an agency needs enterprise deployment, traceable matching, and mixed search and verification workflows.
Verkada
Editor pickManaged camera-to-evidence workflow ties watchlist screening outcomes to stored clips for investigation review.
Best for: Fits when agencies want watchlist screening tied to video evidence review with automated workflow outputs.
Comparison Table
SAFR
enterpriseFacial recognition and video intelligence software for public safety and security teams.
Audit trail coverage that records matcher activity and configuration changes tied to identity search operations.
SAFR positions police facial recognition for operational use by combining face model inference, gallery management, and matching workflows under one administrative surface. The system supports cloud-hosted matching workflows and operational controls for searching mugshot-style galleries and returning ranked identification outcomes.
SAFR also includes configuration around evidence handling, including audit trail records that track searches, matcher runs, and administrative changes. Automation and integration are handled through an API layer designed for agency systems that need to trigger matching from investigative or records workflows.
- +API supports triggering 1:N identification workflows from agency systems
- +Administrative audit trail records matcher activity and configuration changes
- +Gallery management supports repeat searches with controlled provisioning
- +Ranked results formatting fits investigative review workflows
- –Best outcomes depend on disciplined probe and gallery template management
- –Requires governance choices to keep searches aligned with policy and roles
Investigators and surveillance operators
Cross-camera identity investigation
Identity-assisted investigative leads
Evidence and records teams
Documented search and match runs
Audit-ready search history
Best for: Fits when agencies need API-driven matching workflows and strong audit trail coverage for investigative searches.
NEC NeoFace
enterpriseBiometric facial recognition technology used by police for identity verification and suspect identification.
Role-based access plus audit trails tied to matching events and result handling.
NEC NeoFace fits agencies that need facial recognition tied to established investigative and records workflows, because it is designed for enterprise deployment and system integration rather than stand-alone desktop matching. The product’s capability split between 1:N and 1:1 flows supports a common police pattern of searching mugshot databases and performing verification for case follow-ups. Governance is handled through audit and access controls so investigators and administrators see different operational views and result histories.
A key tradeoff is that operational accuracy depends on consistent enrollment quality and image handling, so agencies must manage probe image capture variability and gallery update discipline. NeoFace fits usage when investigators need recurring BOLO-style lead generation from controlled mugshot databases and when supervisor review requires traceable match outcomes.
- +Supports both 1:N identification and 1:1 verification in one workflow set
- +Audit and access controls support controlled handling of match outcomes
- +Enterprise deployment options fit on-premise agency architectures
- +Integration-oriented design supports linking to existing case systems
- –Match quality is sensitive to enrollment and probe image capture consistency
- –Operational rollout requires governance discipline for thresholds and approvals
- –API and automation coverage can be deeper only with implementation support
- –Configuration effort increases when cameras, batches, and databases differ
Investigations unit supervisors
Reviewing watchlist match outcomes
Faster accountable lead review
Police records teams
Managing mugshot database updates
More consistent search coverage
Show 2 more scenarios
Case management administrators
Integrating matching into case workflows
Less manual result handling
Administrators can connect NeoFace matching outputs to existing investigative systems.
Field identification teams
Performing identity checks on detainees
Reduced identity ambiguity
Teams can run 1:1 verification when a subject’s face needs confirmation.
Best for: Fits when an agency needs enterprise deployment, traceable matching, and mixed search and verification workflows.
Verkada
enterpriseCloud-based video security system offering facial recognition and person search for enterprise and law enforcement.
Managed camera-to-evidence workflow ties watchlist screening outcomes to stored clips for investigation review.
Verkada’s facial recognition is packaged around continuous video capture and centralized device management, which reduces the operational gap between a live scene and later review. Evidence comes from the same camera ecosystem that produces the probe content and evidence clips, which helps maintain investigative continuity during lead building. The administrative layer covers role-based access and audit visibility for video access and system actions, which matters for chain-of-custody workflows.
A key tradeoff is that Verkada’s strongest workflow value appears when agencies adopt Verkada cameras and video management in parallel, because investigation review is optimized for that ecosystem. It fits best when patrol units or detective teams need watchlist screening outcomes connected to stored footage for quick investigative follow-up, rather than for deep in-house biometric pipeline tuning.
- +Centralized video evidence links watchlist results to recorded context
- +RBAC and audit visibility for operator access and investigative actions
- +Automation hooks for integrating recognition events into agency workflows
- –Best end-to-end workflow depends on adopting Verkada camera management
- –Limited flexibility for agencies needing custom matching pipelines
Patrol operations
BOLO-driven watchlist screening
Faster investigative lead creation
Detective units
Case building from recognition hits
More consistent evidence narratives
Show 1 more scenario
IT integration teams
Event-driven alert automation
Reduced manual alert handling
Integrations consume recognition-related events to trigger CAD or RMS work queues for investigators.
Best for: Fits when agencies want watchlist screening tied to video evidence review with automated workflow outputs.
IDEMIA Face Recognition
enterpriseBiometric face recognition solutions for government identity, border control, and public security.
Evidence-centered audit trail generation tied to recognition outputs for investigator review and chain-of-custody workflows.
IDEMIA Face Recognition is a police-focused facial recognition system built around end-to-end workflows for 1:N identification and 1:1 verification, with configurable matching and evidence handling. Agencies typically use it for gallery searches against mugshot databases and for verifying suspects with probe images from investigations.
- +Workflow coverage supports 1:N identification and 1:1 verification in investigations
- +Provides evidence-oriented audit trail outputs for review and documentation
- +Supports both cloud-hosted matching and on-premise deployment patterns
- +Configurable gallery and probe handling fits typical mugshot database operations
- –Integration depth varies by CAD and RMS availability, requiring project scoping
- –Requires governance discipline to manage watchlists and false hit response workflow
- –Scoring interpretation and thresholds can be complex across heterogeneous capture sources
- –Automation depth depends on the breadth of provided API and event hooks for agencies
Investigators and surveillance operators
Cross-camera gallery searches
Ranked investigative leads
Investigative units
Probe image suspect verification
Faster identity confirmation
Best for: Fits when police teams need gallery-driven investigative lead generation with audit trail outputs and flexible deployment.
Cognitec FaceVACS
enterpriseFace recognition software suite offering identification, verification, and video screening for government and police applications.
Configurable evidence-linked processing records that tie probe-to-gallery results into an auditable workflow.
Cognitec FaceVACS is built for end-to-end identification work, from face detection and landmark localization to embedding vector extraction and matcher execution. The deployment split between on-premise matching and cloud-hosted matching enables consistent handling of large gallery sets when connectivity or jurisdiction constraints limit centralized processing. Audit trail and evidence workflow support target regulator-facing documentation needs during watchlist hit review and case handoff. RBAC-style administrative control exists to segment duties between ingestion, configuration, and search operators.
- +Supports both on-premise matching and cloud-hosted matching
- +Evidence-ready audit trail and chain-of-custody oriented processing records
- +CAD and RMS integration supports event-driven investigative searches
- +Template pipeline covers detection, alignment, and embedding extraction
- –On-premise deployment requires capacity planning and local maintenance
- –Gallery onboarding and configuration takes disciplined governance
- –Workflow tuning is needed to control investigative lead review throughput
- –Live feed handling depends on upstream capture and stream integrations
Major case management teams
Investigate photo leads against mugshot galleries
Faster lead triage
Investigative operations centers
BOLO alert investigative lead generation
Higher actionable hits
Show 1 more scenario
IT governance and compliance
Split deployments across constrained sites
Lower operational drift
Keeps template extraction and matching workflows consistent across on-prem and cloud patterns.
Best for: Fits when agencies need audit-traceable face recognition with CAD and RMS integrations across on-prem and cloud.
Paravision Face Recognition
API-firstFace recognition software and APIs for government, security, and identity applications.
Workflow-first matching that couples template extraction and gallery updates to repeated watchlist search operations.
Paravision Face Recognition targets law-enforcement workflows that need 1:N identification against a mugshot database and returning investigative leads with match confidence. The system is positioned around biometric template extraction and gallery set management so galleries can be updated as new booking records arrive.
- +1:N identification workflow fits recurring booking to watchlist search cycles
- +Template extraction and gallery set management reduce repeated manual preparation
- –Integration depth depends on surrounding RMS and CAD wiring maturity
- –Governance controls such as audit log and chain-of-custody reporting are not consistently detailed
Investigators and detectives
Mugshot watchlist identification
Prioritized suspect candidates
Operations teams
Repeated searches on updated galleries
Lower manual rework
Best for: Fits when investigators need repeated 1:N matches against a maintained gallery without rebuilding workflows each batch.
Ayonix Face Recognition
API-firstFace recognition technology for surveillance, identity management, and public safety use cases.
Watchlist-style matching workflow packaging that routes recognition results into an investigative review pattern.
Ayonix Face Recognition performs face detection and template extraction for both 1:1 verification and 1:N identification against a managed gallery. It supports watchlist-style matching workflows and produces match outputs that can be routed into investigative or operational systems.
- +Supports both 1:1 verification and 1:N identification workflows
- +Provides an operational matching output format suited to watchlist-style review
- +Template extraction is packaged with recognition workflow configuration
- +Works with gallery-based matching patterns used in mugshot database searches
- –Matching outcome controls can require disciplined governance to avoid noisy leads
- –Integration depth varies by target system and may need custom engineering effort
Investigators and case workers
Watchlist-style identity matching
Actionable match outputs
Intake and booking operations
Managed gallery search workflows
Consistent gallery matching
Best for: Fits when agencies need controlled 1:N matching workflows with gallery management and investigative review outputs.
Herta Facial Recognition
vertical specialistFacial recognition software for security, public safety, and law enforcement deployments.
Investigation-centered match review that ties gallery hits to operator workflow decisions and reporting.
Herta Facial Recognition is a police facial recognition product from Herta Security that focuses on deployment flexibility and workflow alignment with investigative operations. The system supports configurable gallery and probe processing for 1:N identification and 1:1 verification, with matching logic built around face template extraction and vector similarity search.
- +API-oriented integration for CAD and RMS workflows
- +Configurable galleries and probes for 1:N and 1:1 matching
- +Match review tooling supports investigative prioritization
- +Deployment options support agencies that avoid all-cloud matching
- –Integration still requires engineering for reliable data mapping
- –Governance controls rely on disciplined watchlist and role setup
- –Tuning performance for different camera feeds needs repeated validation
- –Some advanced operational metrics are not exposed in a single dashboard view
Investigators and analysts
Gallery search with match review
Higher investigation throughput
Dispatch and RMS operators
API-connected near-real-time identification
Faster match-to-action
Best for: Fits when agencies need controlled facial matching workflows with API integration into existing police systems.
DataWorks Plus FaceID
vertical specialistFacial recognition software designed for law enforcement investigations and biometric searches.
Role-based access with audit trail logging that tracks recognition queries and investigative exports for evidence handling.
DataWorks Plus FaceID performs 1:N facial recognition search against a maintained mugshot gallery and returns ranked matches for investigative review. It couples face detection and template extraction with cloud-hosted matching workflows designed for police agency use cases like photo-based lead generation.
- +1:N identification workflow returns ranked gallery matches for quick investigative triage
- +Gallery template management supports batch ingestion for ongoing mugshot database updates
- +RBAC and audit trail logging support controlled access for multi-role staff
- +Integration hooks for CAD and RMS style workflows reduce manual copy-paste steps
- –Operational effectiveness depends on consistent gallery quality and probe-to-gallery alignment
- –Evidence-grade handling can require disciplined chain-of-custody process mapping by the agency
- –Throughput under peak investigations can require careful job scheduling for batch processing
- –Live video stream 1:1 verification workflows are not the core path compared with gallery search
Investigators and case managers
Ranked mugshot lead generation
Ranked lead list
Records and evidence teams
Role-gated evidence exports
Evidence-ready documentation
Best for: Fits when investigators need recurring photo searches across a mugshot gallery with controlled access.
VisionLabs
enterpriseComputer vision and face recognition software for government and public security operations.
Embedding and matching pipeline designed for consistent probe-to-gallery workflows with measurable identification error behavior.
VisionLabs is a police facial recognition vendor that focuses on matching and search workflows built around visual embeddings. Core capabilities include face detection, landmark localization, embedding vector generation, and 1:N identification against a gallery set.
- +API-oriented integration for 1:N searches and 1:1 verification calls
- +End-to-end pipeline from face detection through embedding generation
- +Gallery and probe workflow support for controlled identification batches
- +Configurable match and scoring behavior for measurable error tradeoffs
- –Requires careful governance to manage gallery template lifecycle
- –Deep CAD and RMS connectors often require custom integration work
- –Operational throughput tuning can be dependent on deployment choices
- –On-prem and edge deployment paths may add engineering overhead
Investigators and surveillance operators
Identity search across probe sets
Earlier identity associations
Public-safety integration teams
RMS and CAD workflow automation
Automated match handling
Best for: Fits when investigators need controlled 1:N watchlist matching with programmable probe ingestion and verification steps.
Conclusion
After evaluating 10 police facial recognition software, SAFR stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Police Facial Recognition Software
Police agencies evaluating police facial recognition software need a system that connects probe captures to matcher outputs with evidence-grade traceability. This guide covers Cognitec FaceVACS, NEC NeoFace, Verkada, SAFR, DataWorks Plus FaceID, IDEMIA Face Recognition, Herta Facial Recognition, VisionLabs, Ayonix Face Recognition, and Paravision Face Recognition.
Across these tools, the decision usually turns on integration depth, audit trail scope, and the way each platform packages configuration and automation for recurring investigations. Cognitec FaceVACS leads for evidence-linked processing records that tie probe-to-gallery results into an auditable workflow, while Verkada emphasizes a managed camera-to-evidence workflow that connects watchlist screening outcomes to stored clips.
Police Facial Recognition Software for 1:N watchlist matching and 1:1 verification with audit-traceable evidence workflows
Police facial recognition software matches a probe face against a gallery for 1:N identification and supports 1:1 verification when agencies need focused confirmation. The workflow also has to produce investigator-ready outputs with audit trail coverage that records matcher activity and result handling.
Cognitec FaceVACS is built around configurable evidence-linked processing records that tie probe-to-gallery results into an auditable workflow. NEC NeoFace pairs role-based access with audit trails tied to matching events and result handling, which supports controlled handling of match outcomes across mixed search and verification workflows.
Integration, audit trail, and automation surfaces that hold up in investigations
Police facial recognition software succeeds operationally when probe captures, gallery onboarding, and matcher outputs land in one evidence-grade workflow. Agencies need traceability that connects recognition results to handling actions so investigators can defend decisions during review and documentation.
The feature checklist below focuses on what changes day-to-day system control. It prioritizes how each platform links matching events to audit logs, how the API supports recurring 1:N and 1:1 workflows, and how configuration governance limits noisy leads and inconsistent enrollments.
Evidence-linked processing records and chain-of-custody support
Cognitec FaceVACS ties probe-to-gallery results into configurable evidence-linked processing records that support auditable workflows. IDEMIA Face Recognition generates evidence-centered audit trail outputs tied to recognition results for investigator review.
RBAC and audit trail tied to matching events and result handling
NEC NeoFace pairs role-based access with audit trails tied to matching events and the handling of match outcomes. DataWorks Plus FaceID adds role-based access with audit trail logging that tracks recognition queries and investigative exports for evidence handling.
Watchlist workflow coupling to camera evidence and investigative review
Verkada packages a managed camera-to-evidence workflow that links watchlist screening outcomes to stored clips for investigation review. Ayonix Face Recognition routes watchlist-style matching outcomes into an investigative review pattern with operational outputs suited for that process.
API-driven matching triggers for recurring 1:N identification
SAFR exposes an API that supports triggering 1:N identification workflows from agency systems and records matcher activity and configuration changes. Herta Facial Recognition offers API-oriented integration into CAD and RMS workflows while keeping configurable galleries and probes for 1:N and 1:1 matching.
Batch onboarding and gallery lifecycle management
DataWorks Plus FaceID supports gallery template management for batch ingestion tied to mugshot database updates. Paravision Face Recognition couples template extraction and gallery set management to repeated watchlist search operations.
Pick the deployment shape and workflow packaging that matches how investigations run
The right choice depends less on whether a platform can run 1:N identification or 1:1 verification and more on how it packages evidence handling, configuration governance, and system integration. Agencies should map probe capture sources and gallery sources to the platform’s workflow objects and output artifacts.
This decision framework forces fork points that change real implementation work. It distinguishes evidence-linked processing and on-prem matching options, managed camera-to-evidence packaging, and API-first systems that require stronger governance around templates and thresholds.
Choose evidence traceability depth before matching quality tuning
If the agency needs evidence-linked processing records that tie probe-to-gallery results into auditable workflows, Cognitec FaceVACS provides configurable records oriented to chain-of-custody handling. If the requirement centers on evidence-oriented audit trail outputs generated alongside recognition results, IDEMIA Face Recognition focuses on investigator review and documentation artifacts.
Select the workflow packaging model: managed camera evidence versus platform-internal matching
If watchlist screening must connect directly to stored video clips with operator audit visibility, Verkada’s managed camera-to-evidence workflow is designed around that end-to-end pairing. If the agency needs to keep matching and evidence handling under its own CAD and RMS workflow orchestration, SAFR is positioned around API-triggered matching workflows that record matcher and configuration activity.
Decide how much governance the agency can operationalize for templates and thresholds
If the agency can run disciplined governance for gallery onboarding and configuration, Cognitec FaceVACS supports on-premise matching with capacity planning and local maintenance. If rollout governance must stay tied to role handling of match outcomes with explicit access control, NEC NeoFace supplies RBAC and audit trails tied to matching and result handling.
Confirm whether the platform’s API covers both 1:N and 1:1 workflow calls
If the agency needs one workflow set that covers mixed 1:N identification and 1:1 verification with matching-event audit coverage, NEC NeoFace supports both in the same operational model. If the agency expects API calls that cover 1:N identification triggers and results tied to configuration and matcher activity, SAFR provides that automation surface.
Match batch gallery lifecycle expectations to the platform’s template management workflow
If the agency routinely updates mugshot galleries through batch ingestion and needs gallery template management for that process, DataWorks Plus FaceID supports batch ingestion for ongoing mugshot database updates. If repeated watchlist matching against a maintained gallery is the dominant workflow and template extraction must be coupled to gallery set management, Paravision Face Recognition packages that recurring cycle.
Agencies that should shortlist each workflow and control profile
Different policing workflows stress different controls. Some agencies need chain-of-custody oriented processing records linked to probe-to-gallery outcomes. Others need RBAC and audit logs tied to match handling decisions or a managed camera-to-evidence pipeline that keeps investigative context attached to watchlist results.
The segments below map agency needs to the platforms’ packaging choices and integration posture so procurement teams can avoid mismatched deployments.
Agencies requiring auditable probe-to-gallery evidence traceability across on-prem and cloud matching
Cognitec FaceVACS supports both on-premise matching and cloud-hosted matching with evidence-ready audit trail and chain-of-custody oriented processing records that tie probe-to-gallery results.
Agencies that must control who can handle match outcomes and need audit trails tied to matching events
NEC NeoFace provides role-based access plus audit trails tied to matching events and result handling across combined 1:N and 1:1 workflows.
Agencies building watchlist screening workflows around recorded video evidence review
Verkada’s managed camera-to-evidence workflow ties watchlist screening outcomes to stored clips and exposes RBAC and audit visibility for operator access and investigative actions.
Agencies that require API-triggered matching from existing agency systems with strong matcher and configuration audit coverage
SAFR offers API support for triggering 1:N identification workflows and records administrative audit trail entries for matcher activity and configuration changes.
Agencies focused on investigative match review where gallery hits must map to operator decisions and reporting
Herta Facial Recognition centers on investigation-centered match review that ties gallery hits to operator workflow decisions and reporting, with API-oriented integration into CAD and RMS workflows.
Common procurement and deployment pitfalls that degrade investigative outcomes
Mistakes usually appear in two places. Agencies either skip the governance work that keeps probe and gallery data aligned, or they pick a workflow packaging model that forces extra engineering for evidence and audit artifacts.
The issues below reflect failure modes tied to configuration discipline, template lifecycle, integration depth, and how audit trails map to recognition results.
Treating audit trails as a generic logging feature instead of evidence-linked processing records tied to matcher outputs
Cognitec FaceVACS is built around configurable evidence-linked processing records that connect probe-to-gallery results into auditable workflows. IDEMIA Face Recognition focuses on evidence-centered audit trail outputs tied to recognition outputs for investigator review.
Choosing a system without planning for gallery template lifecycle and governance discipline
NEC NeoFace match quality is sensitive to enrollment and probe image capture consistency, which can surface as operational lead noise if governance is weak. DataWorks Plus FaceID and VisionLabs both require careful governance for gallery template lifecycle so probe-to-gallery alignment stays consistent across recurring searches.
Building around a workflow packaging model that does not match the agency’s evidence pipeline
Verkada’s best end-to-end workflow depends on adopting Verkada camera management, which can limit agencies needing custom matching pipelines. Herta Facial Recognition and VisionLabs both require engineering effort to map CAD and RMS data reliably if data wiring and integration contracts are not defined early.
Overlooking that template extraction and gallery updates can dominate implementation time for recurring watchlist cycles
Paravision Face Recognition couples template extraction and gallery set management to repeated watchlist search operations, which can reduce repeated manual preparation when the agency’s workflow fits that cycle. Ayonix Face Recognition and DataWorks Plus FaceID can still require careful governance to keep recognition outputs aligned with investigative review patterns.
How We Selected and Ranked These Tools
We evaluated police facial recognition software on features 40%, operational ease and integration fit that agencies control 30%, and value 30%. Features scoring emphasized evidence-linked processing records, RBAC plus audit trails tied to matching events, and API and automation surfaces that support recurring 1:N identification and 1:1 verification workflows.
Ease and value scoring emphasized operational rollout impacts like on-prem capacity planning, local maintenance, and governance discipline for enrollment and gallery template management. Cognitec FaceVACS separated itself by tying probe-to-gallery results into configurable evidence-linked processing records and by supporting both on-premise matching and cloud-hosted matching with chain-of-custody oriented audit-ready workflow artifacts.
Frequently Asked Questions About Police Facial Recognition Software
How do Cognitec Data Fusion workflows connect face matching to CAD and RMS systems?
What integration and automation patterns does Verkada support for watchlist screening into case review?
Which products support both 1:N identification and 1:1 verification in a single deployment surface?
Where does Babel Street fit relative to Cognitec Data Fusion and Verkada for API-driven matching workflows?
What audit artifacts and access controls are available for investigators who need traceable result handling?
How do data model and schema choices affect gallery management when mugshot databases update continuously?
What breaks if probe images and gallery templates use different configuration settings for template extraction?
When do on-premise deployments become a requirement instead of cloud-hosted matching?
How does admin control coverage differ between SAFR, DataWorks Plus FaceID, and Ayonix when multiple investigators run searches?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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