GITNUXSOFTWARE ADVICE
Employment CareerTop 10 Best Cv Scanning Software of 2026
Top 10 Cv Scanning Software picks for 2026, comparing HireRight, iCIMS, and Workday Recruiting with ranking criteria for recruiters.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
HireRight
Background screening case management that organizes candidates using CV-derived intake data
Built for enterprises needing compliance-first candidate screening workflows beyond basic CV parsing.
iCIMS
Editor pickResume Parsing that populates structured candidate fields for ATS workflows
Built for recruiting teams using an iCIMS ATS that need automated parsing.
Workday Recruiting
Editor pickResume parsing into structured candidate profiles within Workday Recruiting workflow
Built for large enterprises needing integrated CV parsing inside workflow recruiting.
Related reading
Comparison Table
This comparison table maps CV scanning workflows across tools such as HireRight, iCIMS, Workday Recruiting, SmartRecruiters, and Greenhouse, focusing on integration depth with ATS and HRIS systems. It compares the underlying data model and schema, plus automation rules and the breadth of the API surface for provisioning, extensibility, and throughput. Admin and governance controls are compared via RBAC, configuration controls, and audit log coverage.
HireRight
enterprise screeningPerforms candidate screening and CV parsing to support applicant data capture and hiring workflows.
Background screening case management that organizes candidates using CV-derived intake data
HireRight supports CV and resume data handling within recruitment screening workflows by mapping document inputs to structured candidate records used during hiring stages. This enables screening teams to initiate background checks and maintain audit-ready histories tied to candidate activities and decisions, reducing reliance on manual spreadsheet transfers. Its document-driven process supports consistency across roles and locations where compliance documentation and traceability are required.
A tradeoff is that CV-driven workflows depend on stable data extraction and recruiter data-entry standards, which can require process tuning for edge-case document formats. This is a strong fit for organizations running high-volume, multi-stage hiring where HR needs predictable handoffs between document intake and screening operations. It also suits teams that need audit-ready documentation across multiple jurisdictions and internal approval steps.
- +CV-to-screening workflow links resumes to background checks and candidate records
- +Structured data fields support consistent screening intake across recruiters
- +Audit trails and case management help keep screening steps traceable
- +Role-based controls reduce risk during high-volume candidate processing
- –CV parsing quality can vary by resume layout and formatting
- –Setup requires careful configuration to match internal screening policies
- –Recruiter self-serve adjustments may be limited without admin involvement
HR operations teams
Resume intake triggers verification workflows
Fewer manual handoffs
Enterprise compliance teams
Audit trails link to candidates
Stronger audit readiness
Show 2 more scenarios
Talent acquisition recruiters
Structured candidate profiles from resumes
Faster candidate processing
Extracted resume fields maintain consistent profiles across hiring stages and reduce data re-entry.
Global hiring program managers
Document intake across multiple locations
More consistent screening outcomes
Centralized candidate handling coordinates checks while keeping recruitment artifacts aligned to local requirements.
Best for: Enterprises needing compliance-first candidate screening workflows beyond basic CV parsing
More related reading
iCIMS
ATS automationUses structured candidate data intake with resume parsing capabilities inside an applicant tracking system.
Resume Parsing that populates structured candidate fields for ATS workflows
iCIMS stands out as an ATS-first vendor where candidate document intake and CV parsing are tightly connected to recruiting workflows and job requisitions. It supports automated resume parsing into structured candidate fields and aligns imported data with downstream stages like screening, interviews, and offers.
CV scanning is most effective when recruiters use iCIMS requisitions and forms because the parsed data can immediately drive matching and activity tracking. Advanced configurations typically depend on iCIMS administrative setup within the larger hiring platform rather than standalone scan-and-export usage.
- +Resume parsing maps text into structured candidate fields
- +Parsed data flows directly into stages, tasks, and candidate profiles
- +Works best inside iCIMS hiring workflows with reduced manual retyping
- +Configurable intake supports multiple role-specific requirements
- –Best results require iCIMS admin configuration and recruiting setup
- –Standalone CV scanning without ATS workflows feels limited
- –Template and field mapping changes can add operational overhead
- –Nonstandard resume formats may reduce parsing quality
Recruiting operations teams
Centralize CV intake per requisition
Faster, cleaner candidate data handoff
Talent acquisition coordinators
Route resumes to structured screening fields
Reduced manual data entry
Show 2 more scenarios
Recruiters managing high volume
Maintain consistent candidate matching inputs
More consistent shortlisting signals
Parsed CV fields support downstream matching and activity tracking across job stages.
HR administrators in iCIMS
Configure intake data mappings
Better alignment across workflows
Admin setup controls how parsed resume data maps into job requisitions and forms.
Best for: Recruiting teams using an iCIMS ATS that need automated parsing
Workday Recruiting
enterprise ATSProvides resume parsing and candidate data capture within a recruiting suite.
Resume parsing into structured candidate profiles within Workday Recruiting workflow
Workday Recruiting stands out because it is part of a unified Workday HCM suite that manages recruiting workflows and downstream HR processes. It supports resume parsing and candidate data extraction to populate structured profiles and speed up screening inside Workday.
Built-in talent matching uses configurable rules and job requisition context to route candidates to recruiters. CV scanning functions are tightly embedded in end-to-end recruiting management rather than offered as a standalone parsing tool.
- +Strong resume parsing that feeds structured candidate profiles in Workday
- +Configurable screening workflows reduce manual candidate movement
- +Job requisition context supports better candidate routing than generic parsing
- +Tight integration with recruiting and broader HR processes improves continuity
- –CV scanning depth depends on overall Workday configuration and recruiting setup
- –Advanced matching and workflow changes can require administrator involvement
- –Less suited for teams wanting a standalone CV parser only
- –Candidate matching customization can feel complex in larger Workday deployments
HR recruiters in Workday
Parse resumes into Workday candidate profiles
Reduced manual data entry
Talent acquisition operations
Standardize candidate intake across requisitions
More consistent candidate routing
Show 1 more scenario
Workday HR admins
Tune enrichment rules and mappings
Cleaner, structured candidate records
Admins configure parsing mappings so extracted resume data populates the right Workday attributes.
Best for: Large enterprises needing integrated CV parsing inside workflow recruiting
More related reading
SmartRecruiters
recruiting platformCaptures and structures applicant information from resumes in recruiting workflows via resume parsing.
Automated CV parsing that maps resumes into structured candidate profiles
SmartRecruiters stands out by pairing CV parsing with an end-to-end hiring workflow built for recruiters, not just résumé extraction. The system converts uploaded resumes into structured candidate fields and supports configurable screening steps across job requisitions.
CV matching feeds downstream processes like interview scheduling and candidate status tracking within the same application. The result is a unified pipeline where parsed CV data stays usable throughout selection and collaboration.
- +CV parsing extracts candidate details into structured fields for faster review
- +Matches feed directly into the hiring workflow with shared job requisitions
- +Collaboration features keep parsed CV data tied to candidate status history
- +Configurable screening steps reduce manual re-entry of CV information
- –CV scanning quality depends on resume formatting and document cleanliness
- –Advanced workflow configuration can feel complex for small recruiting teams
- –More specialized sourcing and parsing expectations may require workflow tuning
Best for: Recruiting teams needing CV scanning connected to structured hiring workflows
Greenhouse
ATS resume parsingUses resume parsing to extract candidate details and streamline applicant intake in hiring pipelines.
Built-in resume parsing that feeds Greenhouse structured fields and automated recruiting workflows
Greenhouse focuses recruiting operations around structured pipelines and role-based candidate records, which changes how resume parsing fits into day-to-day hiring. The resume parsing and CV import capabilities route candidate data into Greenhouse fields, then support downstream workflows like stages, interview scheduling, and collaboration. For teams standardizing sourcing, screening, and evaluation, Greenhouse keeps CV scanning tied to job requisitions and hiring permissions instead of treating it as a standalone scanner.
- +CV parsing populates structured candidate fields for fast review
- +Tight job requisition context keeps screening tied to the correct role
- +Workflow automation uses parsed data across stages and assignments
- +Strong collaboration tools support consistent evaluation after import
- –Resume scanning quality depends on document formatting and templates
- –Custom mapping for edge cases can require admin setup effort
- –Less suitable as a standalone CV scanner outside Greenhouse workflows
Best for: Recruiting teams needing CV scanning tightly integrated with hiring workflows
Lever
ATS resume parsingExtracts candidate data from resumes to reduce manual entry in an applicant tracking workflow.
Configurable hiring pipelines that automatically carry parsed resume data into stages
Lever stands out for treating resume intake as part of an end-to-end recruiting workflow rather than a standalone CV parser. It can capture candidate data from resumes, route candidates through configurable pipelines, and support structured evaluation with internal notes and stages.
For teams that already run process-driven hiring, Lever’s workflow automation reduces manual handoffs after documents are reviewed. The result is a CV scanning experience tightly connected to collaboration, tracking, and hiring decisions within a single system.
- +Resume parsing feeds directly into recruiting stages and candidate records
- +Configurable hiring pipelines support fast routing after document intake
- +Collaboration tools centralize evaluation notes for each candidate
- +Automation reduces manual copying of fields into ATS forms
- –CV data quality depends on document formatting and consistency
- –Workflow customization requires setup work to match team processes
- –Limited flexibility for teams wanting standalone parsing only
- –Advanced automation can increase configuration complexity
Best for: Teams needing resume-to-pipeline automation inside a structured recruiting workflow
More related reading
Breezy HR
mid-market ATSParses resumes to populate candidate fields inside its hiring and applicant tracking system.
AI-assisted resume parsing feeding directly into Breezy's hiring pipeline stages
Breezy HR stands out for combining CV parsing with a recruiter-focused pipeline view and structured candidate scoring. It converts uploaded resumes into searchable candidate profiles and supports workflow stages for faster triage.
The system emphasizes collaboration through team hiring pipelines rather than standalone parsing only. Integrations and automations help move parsed candidates through job-specific review steps.
- +CV parsing populates candidate fields for faster triage
- +Pipeline stages align parsed candidates to consistent review workflows
- +Team collaboration features reduce handoff friction during screening
- +Searchable candidate data supports quick shortlisting across roles
- –Advanced parsing accuracy depends on resume formatting consistency
- –Fewer standalone parsing controls than specialized OCR-focused tools
- –Customization depth for sourcing rules is limited versus enterprise suites
Best for: Recruiting teams needing CV parsing tied to structured pipeline workflows
Zoho Recruit
CRM ATSExtracts structured information from resumes to automate candidate record creation in Zoho Recruit.
Resume parsing into structured candidate fields within the Zoho Recruit ATS
Zoho Recruit stands out by combining resume parsing with a broader ATS workflow for managing job pipelines end to end. Resume parsing extracts candidate data into structured fields and supports recruiter review, ranking, and status tracking inside the same system.
The tool also ties parsed candidates to job requisitions so sourcing, screening, and collaboration stay consistent across roles. For CV scanning, the primary value comes from usable automation that feeds directly into ATS stages rather than sending parsed data into a standalone dashboard.
- +CV parsing feeds directly into ATS candidate records for smoother screening workflows
- +Workflow stages and templates help standardize how parsed resumes move through review
- +Zoho integrations extend screening actions with other Zoho business apps
- +Search and filtering leverage extracted fields for faster shortlisting
- –Resume parsing quality can vary by resume formatting and unusual templates
- –Complex recruiter workflows can require admin setup to stay consistent
- –Advanced automation can feel harder to fine-tune than simpler CV scanners
Best for: Recruiter teams needing CV parsing tightly connected to an ATS pipeline
More related reading
Manatal
AI recruitingUses AI-driven resume parsing to match and organize candidates in recruiting workflows.
AI resume parsing that populates structured candidate profiles for pipeline workflows
Manatal centers hiring operations around AI-assisted resume parsing and a structured talent pipeline rather than standalone resume viewing. Its CV parsing and candidate enrichment feed search, tagging, and workflow steps inside a unified recruiting workspace.
Automated matching signals help recruiters prioritize profiles and speed up sourcing-to-review handoffs. The system is designed for ongoing recruitment management, so CV scanning works best when paired with pipeline collaboration and job-specific hiring stages.
- +AI resume parsing extracts structured fields for faster candidate review
- +Candidate search uses parsed data for quicker filtering across roles
- +Workflow stages and collaboration reduce switching between hiring tools
- +Automation helps route candidates to recruiters based on signals
- –Setup of job fields and matching logic takes time and attention
- –Deep customization can feel complex for teams with simple processes
- –Review and QA of parsed data remains necessary for accuracy
- –Feature richness can overwhelm recruiters without process standardization
Best for: Recruiting teams managing multiple roles needing automated CV parsing and pipeline workflows
Textkernel
AI talent intelligenceProvides AI-based resume parsing and candidate matching for recruitment processes.
Textkernel resume parsing with configurable data normalization for candidate matching
Textkernel stands out for enterprise-grade resume parsing and text intelligence focused on extracting structured candidate data from unstructured documents. Core capabilities include CV parsing, normalization, search and matching, and analytics that support recruiting workflows. The tool emphasizes relevance-driven candidate ranking, which helps teams compare resumes beyond keyword-only filtering.
- +Strong resume parsing with structured field extraction for downstream use
- +Search and matching designed for relevance beyond simple keyword filters
- +Analytics support continuous improvement of extraction and matching quality
- –Implementation effort can be high for organizations without engineering support
- –Tuning matching logic and schemas typically requires domain expertise
- –User workflows can feel less intuitive than lighter CV screening tools
Best for: Enterprises needing accurate parsing and ranking at scale across diverse CV formats
Conclusion
After evaluating 10 employment career, HireRight 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 Cv Scanning Software
This buyer’s guide covers how to choose CV scanning software by comparing HireRight, iCIMS, Workday Recruiting, SmartRecruiters, Greenhouse, Lever, Breezy HR, Zoho Recruit, Manatal, and Textkernel.
The comparison focuses on integration depth, the data model and schema choices used for parsed fields, automation and API surface considerations, and admin and governance controls that protect high-volume hiring workflows. Each section maps evaluation criteria directly to concrete capabilities such as CV-to-screening case management in HireRight and resume parsing into structured candidate profiles in Workday Recruiting and Greenhouse.
CV scanning that converts resumes into structured candidate records inside recruiting workflows
CV scanning software ingests uploaded resumes and extracts candidate details into structured fields that can feed recruiting stages, candidate profiles, and downstream actions. Tools like iCIMS, Greenhouse, and Lever treat resume parsing as an intake step that populates ATS records so recruiters can act on normalized fields instead of retyping document text.
Teams use CV scanning to reduce manual data entry, standardize candidate intake across requisitions, and keep parsed values tied to workflow history. This approach is especially visible in HireRight, where CV-derived intake feeds background screening case management with audit-ready histories tied to candidate activities and decisions.
Evaluation criteria that determine parsed data quality and control after import
Parsing accuracy depends on how each tool turns unstructured resume text into a predictable internal schema with consistent field mapping. Greenhouse and Lever score highly in practice because parsed CV data routes into structured candidate fields and then flows across pipeline stages and assignments.
Integration depth matters because the parsed output must support real automation paths such as stage movement, interview scheduling, and task routing. HireRight and Workday Recruiting also show how governance controls and workflow traceability affect compliance-first screening and admin-mediated configuration.
CV-to-structured data mapping into stable candidate fields
The tool must convert resume inputs into structured candidate fields that remain usable across stages and recruiter workflows. iCIMS and SmartRecruiters excel here because parsed data populates structured candidate profiles tied to job requisitions and downstream stages.
Workflow automation that carries parsed fields into stages, tasks, and status history
Automation determines whether parsed data actually saves work after import. Greenhouse, Lever, and Breezy HR connect parsing to pipeline stages and team collaboration so parsed values drive triage and evaluation workflows.
Background screening case management tied to CV-derived intake
For compliance-first programs, the parsed intake must anchor screening steps and audit histories to candidate decisions. HireRight stands out because background screening case management organizes candidates using CV-derived intake data with audit trails and case handling tied to screening steps.
Integration depth inside an ATS or recruiting suite, not standalone export
The best results typically depend on using tool-native job requisitions and intake forms so the parser can align to the right context. Workday Recruiting and Greenhouse keep resume parsing embedded in end-to-end recruiting management rather than positioning it as a standalone CV parser.
Configurable routing and matching rules tied to requisition context
Candidate routing improves when parsed fields combine with job requisition context and configurable matching logic. Workday Recruiting supports job-requisition context for routing and configurable screening workflows, and Manatal uses AI resume parsing plus signals to route candidates to recruiters.
Admin controls for field mapping, governance, and traceability
Governance matters when recruiters need guardrails around what can be changed after parsing. HireRight and Workday Recruiting emphasize audit-ready histories and admin involvement for advanced workflow changes, which reduces uncontrolled edits during high-volume processing.
Extensibility signals through automation and API-oriented surfaces
The automation and integration surface determines how parsed data can connect to external systems like background checks and recruiting operations dashboards. Textkernel highlights enterprise implementation effort around tuning normalization and matching logic, which is a sign that deeper extensibility often requires schema and integration work.
A decision framework for selecting CV scanning software with the right integration depth and governance
Start by deciding where parsed candidate data must live after scanning. If parsed fields must immediately drive recruiting stages inside a suite, Greenhouse, Lever, and iCIMS provide resume parsing tied to ATS workflows and requisition context.
Then validate how much admin configuration and governance control exists for field mapping and workflow changes. HireRight provides audit-ready screening case management using CV-derived intake data, while Workday Recruiting relies on overall Workday configuration to determine parsing depth and workflow depth.
Map the target workflow so parsing output triggers real stage actions
Define the exact next step after resume upload, such as interview scheduling, stage movement, or screening tasks. Greenhouse and Lever connect parsed CV fields to pipeline stages and assignments, which reduces manual handoffs after intake.
Confirm the data model so parsed fields align to your requisition and scoring needs
Check whether the tool populates structured candidate fields that match recruiter review and reporting patterns. iCIMS and SmartRecruiters focus on resume parsing into structured candidate fields that flow into tasks and candidate profiles tied to job requisitions.
Evaluate governance by testing how field mapping and workflow changes are controlled
Determine whether recruiters can adjust parsed values or whether admins must configure mapping and policies. HireRight includes role-based controls and admin involvement for setup tuning, and Workday Recruiting can require administrator involvement for advanced workflow changes.
Assess integration depth against the recruitment platform already in use
Choose the tool that fits the ATS suite used for requisitions, intake forms, and hiring stages. Workday Recruiting and Greenhouse embed CV parsing tightly into end-to-end recruiting management, while standalone scanning without ATS workflow integration feels limited for iCIMS.
Plan for parsing variability and edge-case documents with a correction workflow
Expect parsing quality to vary by resume formatting, templates, and document cleanliness. HireRight and Greenhouse depend on stable extraction and may need setup tuning for edge-case document formats, so include a QA step for parsed values in the workflow.
Select for the enterprise use case that matches compliance or ranking requirements
If compliance-first screening requires audit-ready histories tied to screening steps, HireRight is built around background screening case management using CV-derived intake data. If ranking accuracy across diverse CV formats and relevance beyond keyword filtering matters, Textkernel emphasizes configurable data normalization and relevance-driven candidate ranking.
Who benefits from CV scanning tools with structured fields, automation, and governance
CV scanning software fits teams that need parsed resume data to become operational inside hiring workflows. The best match depends on whether the organization uses an ATS suite for requisitions and stages, or requires compliance-first screening traceability.
The recommended tools below map directly to the primary best-for profiles across HireRight, iCIMS, Workday Recruiting, SmartRecruiters, Greenhouse, Lever, Breezy HR, Zoho Recruit, Manatal, and Textkernel.
Enterprises running compliance-first screening beyond basic parsing
HireRight fits this segment because it organizes candidates using CV-derived intake data in background screening case management with audit trails tied to screening steps and decisions.
Recruiting teams using an ATS suite and needing parsing tied to requisitions and stages
Greenhouse and Lever fit because parsed CV fields feed structured candidate records and workflow automation across stages, interview scheduling, and collaboration within the same system. iCIMS also fits when teams run iCIMS requisitions and forms so parsed data immediately drives matching and activity tracking.
Large enterprises standardizing recruiting inside Workday HCM workflows
Workday Recruiting fits because resume parsing populates structured candidate profiles within Workday Recruiting workflow and routing uses job requisition context for better candidate movement.
Teams that need AI-assisted parsing plus multi-role pipeline routing
Manatal fits because it uses AI resume parsing and automated matching signals to populate structured profiles, then routes candidates inside a unified recruiting workspace with pipeline stages and collaboration.
Enterprises focused on high-accuracy parsing and relevance-driven ranking across diverse CV formats
Textkernel fits because it emphasizes enterprise-grade resume parsing with configurable data normalization and relevance-driven candidate ranking beyond keyword filters.
Pitfalls that break parsing-to-workflow automation and data control
Common failures usually come from assuming CV scanning will be standalone and require no governance or workflow alignment. Several tools show that parsing quality and automation depth depend on configuration and on using native job requisitions and intake forms.
Other failures come from underestimating how resume formatting affects extraction and from skipping a QA step for parsed values that feed screening decisions.
Treating CV scanning as export-only instead of a workflow-driven intake step
Standalone scanning without ATS workflow alignment limits how parsed fields flow into downstream actions for iCIMS. Greenhouse and Workday Recruiting avoid this by embedding parsing into structured pipelines and end-to-end recruiting management.
Under-planning for admin configuration of mapping and workflow policies
Template and field mapping changes can add operational overhead in iCIMS, and advanced matching or workflow changes can require administrator involvement in Workday Recruiting. HireRight also requires careful configuration to match internal screening policies, so mapping governance should be planned during rollout.
Skipping QA for parsed values when resume formatting varies
Parsing quality can vary by resume layout and document cleanliness in HireRight and Greenhouse. Manatal and Textkernel both require review and tuning effort for accuracy, so parsed candidate fields should be validated before they drive ranking and screening.
Choosing a tool that does not match the required control and audit trail
Recruiters self-serve adjustments can be limited without admin involvement in HireRight, which is risky if unrestricted changes are expected. HireRight prevents weak traceability by linking screening steps to audit-ready histories, while Zoho Recruit and SmartRecruiters can require admin setup for consistency in complex recruiter workflows.
Over-customizing pipelines without standardizing intake fields first
Workflow customization can increase configuration complexity in Lever, and deeper customization can feel complex in Manatal for teams with simple processes. Standardizing candidate fields and intake expectations first helps Breezy HR and SmartRecruiters keep parsed data usable across collaboration and pipeline stages.
How We Selected and Ranked These Tools
We evaluated HireRight, iCIMS, Workday Recruiting, SmartRecruiters, Greenhouse, Lever, Breezy HR, Zoho Recruit, Manatal, and Textkernel using features strength, ease of use, and value, then computed an overall score as a weighted average where features carries the most weight and ease of use and value follow. The scoring prioritizes how well resume parsing turns into structured candidate fields that drive automation and workflow adoption, because CV scanning only saves time when parsed outputs land in real stages and actions.
HireRight separated itself from lower-ranked options by combining CV-driven intake with background screening case management that organizes candidates and preserves audit trails tied to screening steps and decisions, which elevates features and also improves operational traceability for compliance-first hiring.
Frequently Asked Questions About Cv Scanning Software
How does HireRight handle CV documents versus exporting parsed text to an ATS?
What makes iCIMS resume parsing different from using a standalone CV scanning tool?
How does Workday Recruiting fit CV scanning into a full hiring lifecycle inside Workday?
Which platforms keep parsed CV data usable across interview scheduling and candidate status tracking?
What integration and API patterns show up when CV parsing must automate pipeline movement?
How do admin controls and RBAC differ for compliance-heavy hiring workflows like HireRight versus ATS-first vendors?
What data migration issues commonly affect companies switching from manual resume handling to structured CV parsing?
How do organizations handle security requirements when CV parsing creates searchable candidate records?
What happens when CV files have inconsistent formatting and extraction quality drops?
How should teams choose between an ATS-embedded workflow like Lever and a normalization-focused engine like Textkernel?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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