{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_interview-co","slug":"interview-co","name":"Interview.co","type":"product","url":"https://interview.co","page_url":"https://unfragile.ai/interview-co","categories":["app-builders"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_interview-co__cap_0","uri":"capability://text.generation.language.job.description.aware.ai.question.generation","name":"job description-aware ai question generation","description":"Analyzes job descriptions and role requirements to automatically generate contextually relevant screening questions using LLM-based prompt engineering. The system extracts key competencies, technical skills, and role-specific attributes from job postings, then uses templated prompts to generate customized question sets that align with hiring criteria rather than using generic question banks. This reduces manual question curation time while ensuring questions target the specific role's requirements.","intents":["Generate screening questions automatically from a job description without manual question writing","Customize questions to specific role requirements and competency models","Reduce time spent on question design for high-volume screening rounds"],"best_for":["Recruiting teams processing 50+ candidates per role","Growth-stage startups without dedicated talent acquisition specialists","Organizations with high-volume hiring across multiple similar roles"],"limitations":["Question quality depends on job description clarity — vague or poorly-written JDs produce generic questions","No built-in validation that generated questions actually predict job performance","Cannot generate questions for highly specialized or niche roles where training data is sparse"],"requires":["Job description in text format (minimum 200 characters recommended)","Active Interview.co account with API access or web interface"],"input_types":["text (job description)"],"output_types":["structured data (array of questions with difficulty levels, competency tags)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_1","uri":"capability://automation.workflow.asynchronous.video.interview.collection.and.storage","name":"asynchronous video interview collection and storage","description":"Provides candidates with a shareable interview link that allows them to record video responses to AI-generated questions on their own schedule, without requiring synchronous scheduling. The system handles video encoding, storage, and retrieval with timestamp metadata, allowing recruiters to review responses asynchronously. This eliminates scheduling friction and timezone constraints while maintaining a complete audit trail of when candidates completed interviews.","intents":["Collect video interview responses from candidates without scheduling calls","Allow candidates to interview on their own time across multiple timezones","Store and organize video responses for team review and comparison"],"best_for":["Distributed teams hiring across multiple geographies","High-volume screening where synchronous interviews are impractical","Organizations wanting to reduce candidate drop-off from scheduling friction"],"limitations":["Video quality varies based on candidate's device and internet connection — no quality standardization","Candidates may feel less personal connection to async video vs live interviews, potentially affecting candidate experience","Storage costs scale with candidate volume; no built-in video retention policies or automatic deletion"],"requires":["Candidate email address for interview link distribution","Candidate device with camera and microphone","Stable internet connection (minimum 2 Mbps upload recommended)"],"input_types":["video (candidate-recorded responses)"],"output_types":["video files with metadata (timestamp, candidate ID, question ID, duration)"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_10","uri":"capability://automation.workflow.team.collaboration.and.interview.review.interface","name":"team collaboration and interview review interface","description":"Provides a shared dashboard where multiple recruiters or hiring managers can view candidate responses, add notes and feedback, and collaborate on shortlisting decisions. The system supports role-based access control (recruiter vs hiring manager vs admin) and enables asynchronous feedback collection from multiple stakeholders. Comments and ratings can be aggregated to support consensus-based hiring decisions.","intents":["Enable multiple team members to review and provide feedback on candidates","Collect input from hiring managers without requiring them to watch full videos","Support consensus-based shortlisting decisions with input from multiple stakeholders"],"best_for":["Organizations with distributed hiring teams across multiple locations","Teams wanting to reduce bias through multi-stakeholder review","Companies with formal hiring committees or consensus-based decision processes"],"limitations":["Collaboration features may be limited to paid tiers, reducing accessibility for small teams","No built-in conflict resolution for disagreements between reviewers","Asynchronous feedback may slow down hiring timelines compared to synchronous discussions"],"requires":["Interview.co account with team collaboration features enabled","Multiple team members with account access"],"input_types":["structured data (candidate scores, interview data)"],"output_types":["structured data (aggregated feedback, consensus scores), documents (review summaries)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_2","uri":"capability://data.processing.analysis.verbal.response.analysis.and.transcription","name":"verbal response analysis and transcription","description":"Automatically transcribes candidate video responses using speech-to-text APIs (likely Whisper or similar) and extracts linguistic features including word choice, response structure, filler words, and speaking pace. The system processes transcripts to identify key phrases, competency indicators, and communication patterns that align with job requirements. Transcription enables searchability and provides a text-based record for compliance and review.","intents":["Convert video responses to searchable text for easier review","Analyze what candidates said to identify relevant competencies and experience","Create audit trails of candidate responses for hiring decision documentation"],"best_for":["Teams wanting to review interviews without watching full videos","Organizations requiring searchable records of candidate responses","Roles where verbal communication clarity is a key evaluation criterion"],"limitations":["Transcription accuracy varies with audio quality, accents, and background noise — typically 85-95% accuracy depending on conditions","Transcription bias: speech-to-text models perform worse on non-native English speakers and certain accents, potentially disadvantaging diverse candidates","No speaker diarization if multiple people appear in video; cannot distinguish between candidate and background voices"],"requires":["Video file with clear audio (minimum 16kHz sample rate)","Interview.co backend with speech-to-text API integration"],"input_types":["video (with audio track)"],"output_types":["text (transcript with timestamps), structured data (linguistic features, confidence scores)"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_3","uri":"capability://planning.reasoning.ai.driven.candidate.response.scoring.and.ranking","name":"ai-driven candidate response scoring and ranking","description":"Evaluates candidate responses against job requirements using LLM-based scoring that analyzes transcript content, response completeness, and alignment with competency models. The system generates numerical scores for each response and produces ranked candidate lists for recruiter review. Scoring likely uses prompt-based evaluation where the LLM is instructed to assess responses against predefined rubrics tied to job competencies, though the exact scoring methodology is opaque to users.","intents":["Automatically rank candidates to surface top performers without manual review","Score responses consistently against the same competency criteria","Reduce time spent reading transcripts by surfacing highest-scoring candidates first"],"best_for":["High-volume screening where manual review of all candidates is impractical","Teams wanting to reduce unconscious bias by using consistent scoring criteria","Organizations with well-defined competency models that can be translated to scoring rubrics"],"limitations":["Scoring methodology is not transparent to users — no visibility into how responses are evaluated or weighted, making it difficult to audit fairness","Bias amplification risk: LLM-based scoring can over-weight communication styles that match training data (typically native English speakers, formal communication) while penalizing neurodivergent or non-native candidates","No built-in calibration mechanism — scores are not validated against actual job performance or recruiter judgment","Cannot assess non-verbal cues (body language, eye contact, confidence) from transcripts alone"],"requires":["Transcribed candidate responses","Job description or competency model to define scoring criteria","Interview.co backend with LLM access"],"input_types":["text (transcripts), structured data (competency models, job requirements)"],"output_types":["structured data (numerical scores per competency, overall ranking, confidence scores)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_4","uri":"capability://image.visual.non.verbal.cue.detection.and.communication.style.analysis","name":"non-verbal cue detection and communication style analysis","description":"Analyzes video responses to extract non-verbal signals including facial expressions, eye contact patterns, hand gestures, and speaking pace/tone. The system uses computer vision and audio analysis to generate metrics on communication style, confidence, and engagement level. These signals are combined with verbal analysis to produce a holistic candidate assessment that includes soft skill indicators like confidence, clarity, and professionalism.","intents":["Assess soft skills like confidence and communication clarity from video responses","Detect engagement level and enthusiasm from non-verbal cues","Evaluate presentation skills and professionalism based on appearance and demeanor"],"best_for":["Roles requiring strong communication or presentation skills (sales, customer-facing, leadership)","Organizations wanting to assess soft skills without live interviews","Teams seeking to reduce bias by using consistent non-verbal evaluation criteria"],"limitations":["High bias risk: non-verbal analysis can discriminate against neurodivergent candidates (e.g., autism spectrum, ADHD) who may have atypical eye contact or hand movement patterns","Cultural bias: non-verbal communication norms vary significantly across cultures — direct eye contact, hand gestures, and speaking pace are interpreted differently globally","Video quality and lighting affect detection accuracy — candidates with poor lighting or camera angles may be unfairly penalized","No scientific evidence that non-verbal cues reliably predict job performance; may introduce noise rather than signal"],"requires":["High-quality video with clear facial visibility and consistent lighting","Computer vision and audio analysis APIs (likely OpenCV, MediaPipe, or similar)"],"input_types":["video (with clear audio and facial visibility)"],"output_types":["structured data (confidence scores, eye contact metrics, gesture frequency, tone analysis, communication style profile)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_5","uri":"capability://automation.workflow.candidate.comparison.and.shortlisting.workflow","name":"candidate comparison and shortlisting workflow","description":"Provides a dashboard interface for recruiters to compare candidate scores, view ranked lists, and create shortlists for next-round interviews. The system allows filtering and sorting by competency scores, response quality, and other metrics, enabling recruiters to quickly identify top candidates. Shortlists can be exported or integrated with downstream hiring workflows (calendar invites for next rounds, email notifications, ATS integration).","intents":["Compare multiple candidates side-by-side to identify top performers","Filter candidates by competency scores or other criteria to create shortlists","Export shortlists for next-round scheduling or ATS integration"],"best_for":["Recruiting teams managing 50+ candidates per role","Organizations wanting to standardize shortlisting criteria","Teams using Interview.co as part of a larger hiring workflow"],"limitations":["Limited customization of comparison views — no ability to define custom comparison metrics or weightings","No built-in A/B testing to validate that shortlisting criteria actually predict success","ATS integration may be limited to specific platforms; custom integrations require API access"],"requires":["Scored candidate responses","Interview.co account with dashboard access"],"input_types":["structured data (candidate scores, competency assessments)"],"output_types":["structured data (shortlists, filtered candidate lists), documents (CSV exports, email templates)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_6","uri":"capability://automation.workflow.freemium.tier.with.limited.screening.capacity","name":"freemium tier with limited screening capacity","description":"Offers a free tier that allows users to conduct a limited number of interviews (typically 5-10 per month) with full access to question generation, video collection, and basic scoring. The freemium model uses a usage-based paywall where additional interviews require a paid subscription. This enables low-friction onboarding and product evaluation without requiring upfront payment, while monetizing through usage scaling.","intents":["Test Interview.co's effectiveness on a small hiring round without financial commitment","Evaluate AI-driven screening before committing to a paid plan","Pilot the tool with a single role or small team before broader rollout"],"best_for":["Startups and small teams with limited hiring budgets","Recruiters wanting to evaluate the tool before recommending to their organization","Organizations testing AI-driven screening for the first time"],"limitations":["Free tier interview limits (typically 5-10/month) are too low for meaningful evaluation of high-volume screening","No access to advanced features like custom scoring rubrics, integrations, or priority support","Freemium tier may have longer processing times or lower priority in the system"],"requires":["Email address to create account","No payment method required for free tier"],"input_types":["none (account creation only)"],"output_types":["account access, limited interview credits"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_7","uri":"capability://text.generation.language.customizable.ai.prompt.engineering.for.question.generation","name":"customizable ai prompt engineering for question generation","description":"Allows recruiters to customize the prompts used to generate screening questions, enabling fine-tuning of question style, difficulty, and focus areas. Users can define custom instructions (e.g., 'focus on problem-solving ability' or 'emphasize leadership experience') that influence how the LLM generates questions. This gives recruiters control over question generation without requiring technical expertise in prompt engineering.","intents":["Customize question generation to match specific hiring priorities or company culture","Adjust question difficulty or style for different candidate levels","Ensure generated questions align with internal competency models or hiring rubrics"],"best_for":["Organizations with well-defined hiring criteria or competency models","Recruiters wanting to iterate on question quality based on feedback","Teams with specific communication styles or cultural values to assess"],"limitations":["Prompt customization requires some understanding of how LLMs respond to instructions — non-technical users may struggle to achieve desired results","No built-in validation that custom prompts produce better questions or more predictive assessments","Changes to prompts may have unintended side effects on question quality or consistency"],"requires":["Interview.co account with prompt customization feature enabled","Job description or competency model to inform custom prompts"],"input_types":["text (custom prompt instructions)"],"output_types":["text (customized questions)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_8","uri":"capability://automation.workflow.interview.link.sharing.and.candidate.invitation","name":"interview link sharing and candidate invitation","description":"Generates shareable interview links that can be distributed to candidates via email, SMS, or direct sharing. The system tracks link expiration, candidate completion status, and reminder notifications. Recruiters can customize invitation emails with company branding, instructions, and deadline information. The link provides a single entry point for candidates to view questions and record responses without requiring account creation.","intents":["Send interview invitations to candidates without requiring them to create accounts","Track which candidates have started and completed interviews","Customize invitation messaging to reflect company brand and hiring process"],"best_for":["Organizations wanting to reduce candidate friction in the screening process","High-volume hiring where manual email management is impractical","Teams using Interview.co as part of a larger recruiting workflow"],"limitations":["Link expiration policies may not be configurable — candidates may lose access if they don't complete interviews within a fixed timeframe","No built-in reminder system for candidates who start but don't complete interviews","Email deliverability depends on candidate email provider — invitations may land in spam"],"requires":["Candidate email address","Interview.co account with interview link generation enabled"],"input_types":["text (candidate email addresses)"],"output_types":["text (shareable interview links), documents (invitation emails)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_interview-co__cap_9","uri":"capability://automation.workflow.hiring.decision.audit.trail.and.compliance.documentation","name":"hiring decision audit trail and compliance documentation","description":"Maintains a complete record of all interview data, scores, and hiring decisions with timestamps and user attribution. The system enables recruiters to document the rationale for accepting or rejecting candidates, creating an audit trail that can be reviewed for fairness and compliance. This supports legal defensibility of hiring decisions and enables post-hoc analysis of hiring patterns.","intents":["Document hiring decisions and rationale for compliance and legal defensibility","Review hiring patterns to identify potential bias or discrimination","Provide candidates with documentation of their interview performance if requested"],"best_for":["Organizations in regulated industries (finance, healthcare) with strict hiring documentation requirements","Teams wanting to audit hiring decisions for fairness and bias","Organizations concerned about legal defensibility of hiring decisions"],"limitations":["Audit trail only documents what the system recorded — does not capture informal discussions or decisions made outside the platform","Scoring methodology remains opaque, making it difficult to explain why a candidate was rejected based on AI scores","No built-in tools to analyze hiring patterns for bias — requires manual review or external analysis"],"requires":["Interview.co account with audit logging enabled","Compliance or legal team to review audit trails"],"input_types":["structured data (interview scores, hiring decisions)"],"output_types":["documents (audit reports, decision logs), structured data (hiring metrics, pattern analysis)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["Job description in text format (minimum 200 characters recommended)","Active Interview.co account with API access or web interface","Candidate email address for interview link distribution","Candidate device with camera and microphone","Stable internet connection (minimum 2 Mbps upload recommended)","Interview.co account with team collaboration features enabled","Multiple team members with account access","Video file with clear audio (minimum 16kHz sample rate)","Interview.co backend with speech-to-text API integration","Transcribed candidate responses"],"failure_modes":["Question quality depends on job description clarity — vague or poorly-written JDs produce generic questions","No built-in validation that generated questions actually predict job performance","Cannot generate questions for highly specialized or niche roles where training data is sparse","Video quality varies based on candidate's device and internet connection — no quality standardization","Candidates may feel less personal connection to async video vs live interviews, potentially affecting candidate experience","Storage costs scale with candidate volume; no built-in video retention policies or automatic deletion","Collaboration features may be limited to paid tiers, reducing accessibility for small teams","No built-in conflict resolution for disagreements between reviewers","Asynchronous feedback may slow down hiring timelines compared to synchronous discussions","Transcription accuracy varies with audio quality, accents, and background noise — typically 85-95% accuracy depending on conditions","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.78,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.445Z","last_scraped_at":"2026-04-05T13:23:42.551Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=interview-co","compare_url":"https://unfragile.ai/compare?artifact=interview-co"}},"signature":"hasS7Bmb7uhOBWMANwpZP7OCrv88T+TZ9RWpmYwThhDTpOJDAzU8mo+f8D9IXGR2js4hVJi9on1P4PJjn3awAA==","signedAt":"2026-06-22T00:30:46.931Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/interview-co","artifact":"https://unfragile.ai/interview-co","verify":"https://unfragile.ai/api/v1/verify?slug=interview-co","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}