{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_fork","slug":"fork","name":"Fork","type":"product","url":"https://www.fork.ai","page_url":"https://unfragile.ai/fork","categories":["research-search"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_fork__cap_0","uri":"capability://data.processing.analysis.real.time.tech.stack.detection.and.monitoring","name":"real-time tech stack detection and monitoring","description":"Continuously scans and identifies technology adoption patterns across target companies by analyzing web signals, DNS records, and application fingerprints. Uses pattern-matching algorithms to detect installed software, frameworks, and infrastructure components, then tracks changes over time to alert users to tech stack shifts. The system maintains a live database of tech signatures and correlates them with company metadata to surface adoption trends.","intents":["I need to know what technologies a prospect is currently using before I pitch to them","I want to monitor when competitors adopt new tools or infrastructure","I need to identify companies that recently adopted a specific technology stack"],"best_for":["B2B SaaS sales teams targeting tech-forward companies","Product marketers conducting competitive intelligence","Sales development reps qualifying inbound leads based on tech fit"],"limitations":["Detection accuracy varies significantly by company size and region — smaller companies and non-US markets have lower coverage","Cannot detect proprietary or internally-developed technologies, only public-facing or commonly-indexed tools","Real-time monitoring latency depends on web crawl frequency, typically 24-72 hours behind actual adoption","Requires companies to have publicly discoverable web presence; air-gapped or private infrastructure is invisible"],"requires":["Company domain or website URL","Active Fork account (freemium or paid tier)","Internet connectivity for real-time signal fetching"],"input_types":["company domain","company name","structured company list (CSV/JSON)"],"output_types":["structured tech stack data (JSON)","change alerts (webhook/email)","timeline of adoption events"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_1","uri":"capability://planning.reasoning.ai.driven.b2b.lead.scoring.and.prioritization","name":"ai-driven b2b lead scoring and prioritization","description":"Applies machine learning models to rank and prioritize sales prospects based on multiple signals including tech stack fit, company funding stage, growth indicators, and historical conversion patterns. The system learns from user engagement (which leads convert, which are ignored) to refine scoring weights over time. Scoring logic combines rule-based filters (e.g., 'Series A+ funding') with learned patterns to surface high-probability opportunities.","intents":["I want to focus my outreach on the most likely-to-convert prospects","I need to automatically rank a list of 1000 companies by sales readiness","I want the system to learn from my team's past wins and apply that pattern to new leads"],"best_for":["Sales teams with 3+ months of historical conversion data to train models","Mid-market B2B companies with repeatable sales processes","Sales leaders managing large prospect pipelines who need triage automation"],"limitations":["Model accuracy depends heavily on data quality and historical conversion logging — incomplete CRM data degrades scoring","No transparent documentation of which signals are weighted most heavily, making it difficult to debug poor rankings","Scoring models may exhibit regional bias if training data is skewed toward US/EU companies","Cold-start problem: new users without historical data receive generic scoring until sufficient conversion data accumulates"],"requires":["Active Fork account (paid tier likely required for custom scoring)","CRM integration or manual conversion logging to train models","Minimum 50-100 historical conversion records for meaningful personalization"],"input_types":["company metadata (size, funding, industry)","tech stack data","historical conversion records (CRM export)"],"output_types":["lead score (numeric 0-100)","ranked prospect list (JSON/CSV)","score reasoning/explainability (if available)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_2","uri":"capability://search.retrieval.funding.activity.tracking.and.alert.generation","name":"funding activity tracking and alert generation","description":"Monitors public funding announcements, SEC filings, and investment databases to detect when target companies raise capital. Automatically extracts funding round details (amount, stage, investors, date) and correlates them with tech stack changes to identify companies in growth mode. Generates alerts via email or webhook when tracked companies announce funding, enabling sales teams to reach out during high-intent windows.","intents":["I want to know immediately when a prospect raises funding so I can reach out at the right time","I need to identify all Series A companies in my target market that raised in the last 30 days","I want to automate outreach triggers based on funding announcements"],"best_for":["Enterprise software sales teams selling to growth-stage startups","Sales development reps working from curated prospect lists","Sales operations teams building automated outreach workflows"],"limitations":["Funding data is public-only — private rounds, bridge financing, and undisclosed funding are invisible","Alert latency varies by data source; some announcements may be 1-7 days behind public disclosure","Accuracy depends on data aggregation quality; some regional or smaller funding rounds may be missed","Cannot distinguish between healthy growth funding and distressed financing (e.g., down rounds)"],"requires":["Active Fork account with alert configuration enabled","Webhook endpoint or email address for alert delivery","Target company list or search filters (industry, geography, funding stage)"],"input_types":["company name or domain","funding stage filter (Seed, Series A, Series B, etc.)","date range for historical lookback"],"output_types":["funding event alert (email/webhook JSON)","structured funding data (round size, stage, investors, date)","historical funding timeline"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_3","uri":"capability://data.processing.analysis.company.tech.stack.comparison.and.competitive.benchmarking","name":"company tech stack comparison and competitive benchmarking","description":"Enables side-by-side analysis of technology choices across multiple companies, showing which tools are adopted by competitors, market leaders, or similar-sized firms. Generates aggregated statistics (e.g., '73% of Series B SaaS companies use AWS') to contextualize individual company tech decisions. Uses clustering algorithms to group companies by tech stack similarity and identify market trends.","intents":["I want to see what tech stack companies similar to my prospect are using","I need to understand if my target market is adopting a specific technology","I want to benchmark my company's tech choices against competitors"],"best_for":["Product marketers researching market adoption trends","Sales teams building competitive positioning narratives","Engineering leaders evaluating technology choices based on market adoption"],"limitations":["Comparison accuracy depends on sample size — small markets or niche technologies may have insufficient data for meaningful benchmarks","Clustering algorithms may group companies incorrectly if metadata (size, industry) is incomplete or inaccurate","Survivorship bias: only visible, public-facing tech stacks are included; failed companies or those using different approaches are underrepresented"],"requires":["Active Fork account (likely freemium or paid tier)","Target company list or market segment definition","Minimum 10-20 companies in comparison set for statistical validity"],"input_types":["company list (CSV/JSON)","market segment or industry filter","technology category (e.g., 'cloud infrastructure', 'analytics')"],"output_types":["side-by-side tech stack comparison (table/JSON)","adoption statistics (percentage, count)","market trend analysis"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_4","uri":"capability://search.retrieval.prospect.list.generation.from.tech.stack.and.funding.filters","name":"prospect list generation from tech stack and funding filters","description":"Generates qualified prospect lists by combining multiple filter criteria: companies using specific technologies, funding stage, company size, geography, and industry. Applies AI-driven ranking to order results by sales readiness. Supports saved searches and scheduled list refreshes to maintain up-to-date prospect pipelines. Exports results in multiple formats (CSV, JSON, CRM-ready) for downstream sales tools.","intents":["I want to find all companies in the US using Kubernetes and Series B+ funding","I need to generate a weekly list of new prospects matching my ICP","I want to export a prospect list directly into my CRM"],"best_for":["Sales development reps building initial prospect lists","Sales operations teams automating list generation workflows","Small teams using freemium tier to bootstrap lead generation"],"limitations":["Filter combinations may return very small result sets if criteria are too narrow, limiting usefulness","Export formats may require manual mapping to CRM field schemas, adding operational overhead","No built-in deduplication across multiple list exports; manual cleanup may be required","Freemium tier likely has export limits (e.g., max 500 records per export)"],"requires":["Active Fork account (freemium or paid)","Clear definition of target customer profile (ICP) to set filters","CRM or sales tool with CSV/JSON import capability (for downstream use)"],"input_types":["technology filter (single or multiple)","funding stage filter","company size range","geography/region","industry vertical"],"output_types":["prospect list (CSV, JSON, or CRM-native format)","list metadata (record count, last updated, filter criteria)"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_5","uri":"capability://tool.use.integration.crm.and.sales.tool.integration.with.data.sync","name":"crm and sales tool integration with data sync","description":"Provides bidirectional data synchronization with popular CRM platforms (Salesforce, HubSpot, Pipedrive, etc.) to push prospect data, tech stack insights, and funding alerts directly into sales workflows. Supports field mapping to align Fork data with CRM schemas. Enables two-way sync so that CRM engagement data (calls, emails, meetings) flows back to Fork for lead scoring refinement.","intents":["I want to automatically add new prospects from Fork into my Salesforce account list","I need tech stack and funding data to appear as custom fields in my CRM","I want my CRM conversion data to feed back into Fork's lead scoring model"],"best_for":["Sales teams already using Salesforce, HubSpot, or Pipedrive","Sales operations teams building integrated lead generation workflows","Teams with technical resources to configure field mappings"],"limitations":["Integration depth varies by CRM platform; some platforms may have limited custom field support","Field mapping requires manual configuration; no auto-detection of matching fields","Sync latency depends on API rate limits; real-time sync may not be available on all tiers","Two-way sync requires careful conflict resolution logic to prevent data overwrites"],"requires":["Active Fork account (likely paid tier for integrations)","CRM account with API access enabled","CRM API credentials (OAuth token or API key)","Technical knowledge to configure field mappings"],"input_types":["CRM platform selection (Salesforce, HubSpot, Pipedrive, etc.)","field mapping configuration (Fork field → CRM field)","sync frequency/schedule"],"output_types":["synced prospect records in CRM","custom fields with tech stack and funding data","sync logs and error reporting"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_6","uri":"capability://text.generation.language.outreach.message.generation.and.personalization","name":"outreach message generation and personalization","description":"Generates personalized sales outreach messages (emails, LinkedIn messages) based on company tech stack, funding activity, and company profile. Uses templates and AI-driven personalization to reference specific technologies, recent funding rounds, or company milestones in outreach copy. Supports A/B testing of message variants to optimize response rates.","intents":["I want to generate a personalized email mentioning the prospect's recent funding and tech stack","I need to create multiple message variants to test which resonates best","I want to scale personalized outreach without writing each message manually"],"best_for":["Sales development reps managing large outreach campaigns","Sales teams wanting to scale personalized messaging without manual effort","Teams with data-driven cultures that test and optimize outreach copy"],"limitations":["Message quality depends on accuracy of underlying company data; poor data produces generic or irrelevant messages","No transparent documentation of how personalization is generated, making it difficult to debug poor results","A/B testing requires sufficient volume (100+ messages per variant) for statistical significance","Generated messages may lack authentic voice or context-specific nuance that manual writing provides"],"requires":["Active Fork account with outreach feature enabled (likely paid tier)","Company data (tech stack, funding, profile) populated in Fork","Email or LinkedIn account for message delivery"],"input_types":["company profile (name, industry, size)","tech stack data","funding event details","message template or style preference"],"output_types":["personalized message text (email or LinkedIn format)","A/B test variants","performance metrics (open rate, response rate)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_7","uri":"capability://planning.reasoning.market.segment.and.icp.definition.with.data.validation","name":"market segment and icp definition with data validation","description":"Provides tools to define and validate Ideal Customer Profile (ICP) criteria by analyzing historical wins and losses. Allows users to specify ICP attributes (company size, funding stage, industry, tech stack) and validates these criteria against historical conversion data to measure fit accuracy. Suggests refinements to ICP definition based on patterns in won vs. lost deals.","intents":["I want to define my ICP based on data from my past wins, not just guesses","I need to validate if my current ICP definition is actually predictive of conversions","I want to refine my ICP based on patterns in my lost deals"],"best_for":["Sales leaders and revenue operations teams defining go-to-market strategy","Teams with 6+ months of historical conversion data to analyze","Organizations wanting data-driven ICP definition rather than intuition-based"],"limitations":["Requires complete and accurate historical conversion data; missing or incorrect data degrades analysis","Small sample sizes (< 50 deals) may produce unreliable patterns due to statistical noise","Cannot account for qualitative factors (relationship strength, champion engagement) that influence conversions","ICP validation is retrospective; may not predict future market conditions or competitive changes"],"requires":["Active Fork account (likely paid tier)","CRM export with historical deals (won/lost status, company attributes)","Minimum 50-100 historical deals for meaningful analysis"],"input_types":["historical deal data (CRM export with won/lost status)","company attributes (size, funding, industry, tech stack)","deal metadata (deal size, sales cycle length, etc.)"],"output_types":["ICP definition (structured criteria)","fit accuracy metrics (% of wins matching ICP)","refinement suggestions (attributes to add/remove)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_fork__cap_8","uri":"capability://data.processing.analysis.sales.intelligence.dashboard.with.custom.metrics.and.reporting","name":"sales intelligence dashboard with custom metrics and reporting","description":"Provides a customizable dashboard displaying key sales intelligence metrics: prospect pipeline health, tech stack adoption trends, funding activity in target market, lead score distribution, and outreach performance. Supports custom metric definitions and scheduled report generation (daily, weekly, monthly). Integrates data from multiple sources (Fork's tech stack database, CRM, outreach tools) into unified views.","intents":["I want a single dashboard showing my prospect pipeline health and market trends","I need to generate weekly reports on new funding activity in my target market","I want to track how many prospects are using a specific technology over time"],"best_for":["Sales managers and revenue leaders monitoring pipeline health","Sales operations teams building reporting infrastructure","Teams wanting visibility into market trends alongside pipeline metrics"],"limitations":["Dashboard performance may degrade with large datasets (10,000+ records); query optimization required","Custom metric definitions require technical knowledge or support from Fork team","Report scheduling may have latency; real-time updates not guaranteed","Data freshness depends on underlying data sources; tech stack data may be 24-72 hours behind"],"requires":["Active Fork account (likely paid tier for custom dashboards)","CRM integration for pipeline data (optional but recommended)","Outreach tool integration for performance metrics (optional)"],"input_types":["metric definition (field, aggregation, filters)","date range","segment/filter criteria"],"output_types":["dashboard visualization (charts, tables, KPIs)","scheduled reports (PDF, email, CSV)","metric data export (JSON, CSV)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Company domain or website URL","Active Fork account (freemium or paid tier)","Internet connectivity for real-time signal fetching","Active Fork account (paid tier likely required for custom scoring)","CRM integration or manual conversion logging to train models","Minimum 50-100 historical conversion records for meaningful personalization","Active Fork account with alert configuration enabled","Webhook endpoint or email address for alert delivery","Target company list or search filters (industry, geography, funding stage)","Active Fork account (likely freemium or paid tier)"],"failure_modes":["Detection accuracy varies significantly by company size and region — smaller companies and non-US markets have lower coverage","Cannot detect proprietary or internally-developed technologies, only public-facing or commonly-indexed tools","Real-time monitoring latency depends on web crawl frequency, typically 24-72 hours behind actual adoption","Requires companies to have publicly discoverable web presence; air-gapped or private infrastructure is invisible","Model accuracy depends heavily on data quality and historical conversion logging — incomplete CRM data degrades scoring","No transparent documentation of which signals are weighted most heavily, making it difficult to debug poor rankings","Scoring models may exhibit regional bias if training data is skewed toward US/EU companies","Cold-start problem: new users without historical data receive generic scoring until sufficient conversion data accumulates","Funding data is public-only — private rounds, bridge financing, and undisclosed funding are invisible","Alert latency varies by data source; some announcements may be 1-7 days behind public disclosure","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.25,"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":"2026-05-24T12:16:30.892Z","last_scraped_at":"2026-04-05T13:23:42.561Z","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=fork","compare_url":"https://unfragile.ai/compare?artifact=fork"}},"signature":"2HqH8pWDCDCboexVtDCuU+ElrX66htkWA41kvamBc9MHH4n/CADqlJzfGV/63eIUuEMRHEn7KvxT2CQgU9N8BA==","signedAt":"2026-06-21T10:25:57.162Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/fork","artifact":"https://unfragile.ai/fork","verify":"https://unfragile.ai/api/v1/verify?slug=fork","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"}}