{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_dealcode","slug":"dealcode","name":"dealcode","type":"product","url":"https://www.dealcode.ai","page_url":"https://unfragile.ai/dealcode","categories":["app-builders"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_dealcode__cap_0","uri":"capability://data.processing.analysis.ai.powered.lead.scoring.with.intent.signals","name":"ai-powered lead scoring with intent signals","description":"Analyzes incoming B2B leads using machine learning models trained on historical conversion data to assign propensity scores. The system ingests lead attributes (company size, industry, engagement signals, technographic data) and outputs a numerical score (typically 0-100) ranking purchase intent. Dealcode likely uses gradient boosting or neural network models that weight signals like website visits, email opens, and firmographic fit to surface high-probability opportunities faster than manual review.","intents":["I need to automatically rank my incoming leads by conversion likelihood without manually reviewing each one","I want to identify which prospects are most likely to close in the next 30 days based on behavioral signals","I need to reduce time spent on low-intent leads and focus my team on high-probability deals"],"best_for":["B2B SaaS sales teams with 50-500 monthly inbound leads","Early-stage companies validating product-market fit without dedicated sales ops","Sales managers needing objective prioritization criteria to coach reps"],"limitations":["Free tier likely limits scoring to <100 leads/month or <1000 total leads in database","Model accuracy depends on historical conversion data — new verticals or GTM motions may have poor calibration","No explainability layer — reps cannot see which signals drove a specific score, limiting trust and coaching","Scoring latency unknown — real-time vs batch processing could impact workflow integration"],"requires":["CRM integration or CSV upload capability to feed lead data","Minimum 50-100 historical closed-won/lost deals for model training","Lead attributes including company size, industry, and engagement metrics"],"input_types":["structured lead data (company name, industry, employee count, revenue, contact info)","engagement signals (email opens, website visits, form submissions)","historical conversion outcomes (won/lost deals)"],"output_types":["numerical lead scores (0-100 scale)","ranked lead lists","score distribution analytics"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_1","uri":"capability://data.processing.analysis.automated.lead.enrichment.and.data.normalization","name":"automated lead enrichment and data normalization","description":"Automatically fills missing lead attributes by querying third-party data providers (likely Clearbit, Hunter.io, or similar APIs) and normalizes inconsistent data formats across CRM imports. The system maps raw lead inputs to standardized schemas, deduplicates records, and appends missing fields like company revenue, employee count, technology stack, and verified email addresses. This reduces manual data entry and ensures consistent data quality for downstream scoring and segmentation.","intents":["I have incomplete lead records with missing company info and need to enrich them automatically before scoring","I want to deduplicate leads across multiple sources (web forms, LinkedIn, events) without manual review","I need standardized company and contact data so my sales team can segment and filter leads consistently"],"best_for":["Sales teams importing leads from multiple sources (forms, ads, events, partnerships)","Companies with inconsistent CRM data quality and no dedicated data ops function","Teams needing to quickly validate lead legitimacy before outreach"],"limitations":["Free tier likely caps enrichment API calls (e.g., 100-500 enrichments/month) making it impractical for high-volume inbound","Enrichment accuracy varies by data provider — smaller companies or non-US markets may have sparse coverage","No control over which data providers are queried — potential privacy/compliance concerns if GDPR-sensitive data is appended","Latency for enrichment could delay lead routing — batch processing may not support real-time workflows"],"requires":["CRM connection or CSV upload with at least company name or domain","API keys or credentials for underlying enrichment providers (if customer-managed)","Mapping configuration to match CRM field names to enrichment schema"],"input_types":["raw lead records (partial company/contact info)","CSV uploads with inconsistent formatting","CRM API feeds with missing fields"],"output_types":["enriched lead records with standardized schema","deduplication reports","data quality scores per field"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_2","uri":"capability://data.processing.analysis.pipeline.analytics.and.deal.velocity.forecasting","name":"pipeline analytics and deal velocity forecasting","description":"Aggregates sales pipeline data to calculate metrics like deal velocity (average time from lead to close), win rates by stage/segment, and revenue forecasts. The system likely ingests CRM pipeline snapshots, applies statistical models (moving averages, regression) to historical deal cycles, and projects future revenue based on current pipeline composition and historical conversion rates. Visualizations surface bottlenecks (e.g., deals stuck in negotiation) and forecast accuracy vs quota.","intents":["I need to forecast next quarter's revenue based on current pipeline and historical close rates","I want to identify which pipeline stages are bottlenecks and where deals are getting stuck","I need to track whether my sales team is on pace to hit quota and adjust strategy accordingly"],"best_for":["Sales managers and revenue leaders needing visibility into pipeline health","Early-stage companies without dedicated sales ops or BI infrastructure","Teams wanting quick forecasting without building custom Salesforce dashboards"],"limitations":["Forecasting accuracy degrades with small sample sizes — early-stage companies with <20 deals/quarter will have high variance","No causal analysis — identifies bottlenecks but doesn't explain root causes (e.g., why deals stall in negotiation)","Free tier likely limits historical data retention (e.g., 6-12 months) making trend analysis unreliable","Assumes linear deal progression — doesn't account for deal acceleration/deceleration or seasonal patterns"],"requires":["CRM integration (Salesforce, HubSpot, Pipedrive) with deal stage and close date data","Minimum 20-30 historical closed deals for statistically meaningful forecasts","Consistent deal stage definitions across the sales team"],"input_types":["CRM pipeline snapshots (deal stage, amount, close date, owner)","historical closed deal records","quota targets (optional)"],"output_types":["revenue forecasts (point estimates + confidence intervals)","deal velocity metrics (average days per stage)","win rate analytics by segment/stage","pipeline health dashboards"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_3","uri":"capability://automation.workflow.automated.lead.routing.and.assignment.optimization","name":"automated lead routing and assignment optimization","description":"Distributes incoming leads to sales reps based on configurable rules (territory, industry, company size) and AI-driven optimization (assigning leads to reps with highest historical close rates for similar prospects). The system likely maintains rep performance profiles, calculates lead-to-rep affinity scores, and routes new leads to maximize expected close probability. May include round-robin fallback for balanced workload distribution.","intents":["I want to automatically assign leads to the rep most likely to close them based on past performance","I need to balance lead distribution fairly across my team without manual assignment","I want to ensure leads are routed to reps with relevant industry expertise or territory coverage"],"best_for":["Sales teams with 5-50 reps where manual lead assignment creates bottlenecks","Organizations with clear territories or industry verticals where rep specialization matters","Teams wanting to reduce lead response time by automating assignment"],"limitations":["Requires historical rep performance data — new reps or reps with <10 closed deals will have poor affinity scoring","Free tier likely caps leads routed/month or number of reps supported","No real-time availability checking — may assign leads to reps who are at capacity or on vacation","Optimization assumes rep performance is stable — doesn't adapt to rep skill development or market changes"],"requires":["CRM integration with rep profiles and historical deal outcomes","Configuration of routing rules (territories, industries, company size bands)","Minimum 20-50 historical deals per rep for meaningful affinity scoring"],"input_types":["incoming lead records with company/contact attributes","rep profiles with territories, industries, and historical performance","routing rule definitions"],"output_types":["lead-to-rep assignments","assignment confidence scores","workload distribution reports"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_4","uri":"capability://tool.use.integration.crm.data.synchronization.and.pipeline.integration","name":"crm data synchronization and pipeline integration","description":"Establishes bidirectional sync between Dealcode and connected CRM systems (Salesforce, HubSpot, Pipedrive) to pull lead/deal data and push back scores, assignments, and enriched attributes. Uses standard CRM APIs (REST/GraphQL) with polling or webhook-based triggers to keep data fresh. Handles schema mapping, conflict resolution (e.g., if CRM and Dealcode have conflicting data), and maintains audit logs of changes.","intents":["I want my lead scores and enriched data to automatically appear in my CRM without manual export/import","I need changes made in my CRM (deal stage updates, rep reassignment) to sync back to Dealcode for re-scoring","I want to avoid duplicate data entry and keep a single source of truth across tools"],"best_for":["Sales teams already using Salesforce, HubSpot, or Pipedrive who want to layer AI on top","Organizations with existing CRM workflows that can't be disrupted","Teams needing real-time data consistency across multiple tools"],"limitations":["CRM API rate limits may throttle sync frequency — free tier likely syncs hourly or daily rather than real-time","Schema mapping is manual configuration — requires technical setup to match CRM fields to Dealcode schema","Conflict resolution is deterministic (e.g., CRM wins) — no intelligent merging of conflicting data","Free tier likely limits number of synced objects (e.g., 1000 leads) or fields"],"requires":["CRM account with API access enabled (Salesforce, HubSpot, or Pipedrive)","API credentials or OAuth token for authentication","Field mapping configuration between CRM and Dealcode schemas"],"input_types":["CRM API responses (lead/deal records, custom fields)","field mapping configuration (JSON or UI-based)"],"output_types":["synced lead records in CRM with scores and enriched data","sync status reports and error logs","audit trail of changes"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_5","uri":"capability://data.processing.analysis.behavioral.engagement.tracking.and.signal.aggregation","name":"behavioral engagement tracking and signal aggregation","description":"Monitors B2B prospect engagement signals (email opens, website visits, content downloads, LinkedIn interactions) by integrating with email platforms (Gmail, Outlook), website analytics, and social monitoring tools. Aggregates these signals into an engagement score that feeds into lead scoring and prioritization. Likely uses event streaming or webhook ingestion to capture signals in near-real-time and correlates them with deal progression.","intents":["I want to know which leads are actively engaging with our content so I can prioritize outreach","I need to track when a prospect visits our website or opens our emails to trigger timely follow-up","I want to identify buying signals (e.g., multiple team members from same company engaging) that indicate deal readiness"],"best_for":["B2B companies with content-driven GTM (webinars, whitepapers, email nurture)","Sales teams wanting to move from activity-based metrics to intent-based prioritization","Organizations with multi-threaded deals where tracking multiple stakeholder engagement matters"],"limitations":["Free tier likely tracks limited signal types (e.g., email opens only, not website visits)","Privacy regulations (GDPR, CCPA) may restrict tracking — requires explicit consent and privacy policy updates","Signal attribution is probabilistic — email opens may be false positives (auto-open, preview pane), website visits may be bots","Latency between signal occurrence and scoring update may be hours, not minutes"],"requires":["Email platform integration (Gmail, Outlook, or email service provider API)","Website analytics integration (Google Analytics, Segment, or custom pixel)","Prospect email addresses and domain information for tracking","Privacy compliance review and consent management"],"input_types":["email open/click events from email platform","website visit events from analytics platform","social engagement signals (optional)","content download events"],"output_types":["engagement scores per lead","engagement timeline (when signals occurred)","multi-threaded engagement reports (by company/account)","engagement alerts for high-intent signals"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_6","uri":"capability://data.processing.analysis.batch.lead.import.and.csv.processing","name":"batch lead import and csv processing","description":"Accepts bulk lead uploads via CSV or Excel files, validates data quality, maps columns to standardized schema, and ingests records into the platform for scoring and enrichment. Includes error handling (flagging invalid emails, missing required fields) and preview functionality to confirm mapping before import. Likely supports deduplication against existing records during import.","intents":["I have a list of 500 leads from a trade show and need to bulk import them into Dealcode for scoring","I want to upload a CSV and have Dealcode automatically map columns and validate data quality","I need to import leads from multiple sources (LinkedIn, event lists, partner lists) without manual entry"],"best_for":["Sales teams with periodic bulk lead sources (events, campaigns, partner lists)","Non-technical users who need simple import without API integration","Organizations migrating from legacy systems or consolidating lead lists"],"limitations":["Free tier likely caps import file size (e.g., 1000 rows) or frequency (e.g., 1 import/month)","Column mapping is manual — requires user to match CSV columns to Dealcode schema","No incremental updates — each import is treated as new records, requiring manual deduplication","Validation is basic — may not catch semantic errors (e.g., invalid domain formats, mismatched company/contact info)"],"requires":["CSV or Excel file with lead data","At least company name or domain for enrichment","Column headers that can be mapped to standard fields (company, contact, email, etc.)"],"input_types":["CSV files (.csv)","Excel files (.xlsx, .xls)","tab-delimited text files"],"output_types":["imported lead records","import validation report (errors, warnings, skipped rows)","deduplication summary"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dealcode__cap_7","uri":"capability://data.processing.analysis.lead.segmentation.and.filtering.by.attributes","name":"lead segmentation and filtering by attributes","description":"Enables users to create dynamic segments of leads based on multi-dimensional filters (company size, industry, geography, lead score range, engagement level, technology stack). Segments can be saved and reused for targeted outreach campaigns, reporting, or routing rules. Likely supports both simple AND/OR logic and more complex rule definitions.","intents":["I want to filter my leads to focus on mid-market SaaS companies in North America with high engagement","I need to create a segment of leads that match my ideal customer profile (ICP) for targeted outreach","I want to save a segment for monthly reporting on how many qualified leads we're generating"],"best_for":["Sales teams with diverse lead sources needing to focus on high-fit prospects","Marketing teams wanting to coordinate with sales on ICP definition and lead quality","Organizations with multiple sales tracks (SMB, mid-market, enterprise) requiring different routing"],"limitations":["Free tier likely limits number of saved segments (e.g., 5-10)","Filtering is static — segments don't automatically update as new leads arrive or scores change","No segment overlap analysis — can't easily identify leads matching multiple ICPs","Segmentation is attribute-based only — can't segment by behavioral patterns or deal velocity"],"requires":["Lead records with enriched attributes (company size, industry, technology stack)","Defined ICP or segmentation criteria"],"input_types":["filter criteria (attribute ranges, categorical values)","segment definitions (rule combinations)"],"output_types":["filtered lead lists","segment size and composition reports","saved segment definitions"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["CRM integration or CSV upload capability to feed lead data","Minimum 50-100 historical closed-won/lost deals for model training","Lead attributes including company size, industry, and engagement metrics","CRM connection or CSV upload with at least company name or domain","API keys or credentials for underlying enrichment providers (if customer-managed)","Mapping configuration to match CRM field names to enrichment schema","CRM integration (Salesforce, HubSpot, Pipedrive) with deal stage and close date data","Minimum 20-30 historical closed deals for statistically meaningful forecasts","Consistent deal stage definitions across the sales team","CRM integration with rep profiles and historical deal outcomes"],"failure_modes":["Free tier likely limits scoring to <100 leads/month or <1000 total leads in database","Model accuracy depends on historical conversion data — new verticals or GTM motions may have poor calibration","No explainability layer — reps cannot see which signals drove a specific score, limiting trust and coaching","Scoring latency unknown — real-time vs batch processing could impact workflow integration","Free tier likely caps enrichment API calls (e.g., 100-500 enrichments/month) making it impractical for high-volume inbound","Enrichment accuracy varies by data provider — smaller companies or non-US markets may have sparse coverage","No control over which data providers are queried — potential privacy/compliance concerns if GDPR-sensitive data is appended","Latency for enrichment could delay lead routing — batch processing may not support real-time workflows","Forecasting accuracy degrades with small sample sizes — early-stage companies with <20 deals/quarter will have high variance","No causal analysis — identifies bottlenecks but doesn't explain root causes (e.g., why deals stall in negotiation)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"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":"2026-05-24T12:16:30.282Z","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=dealcode","compare_url":"https://unfragile.ai/compare?artifact=dealcode"}},"signature":"xNSRCa3ZnN/IC6rfhNSJOC7bQMDq/oMfIOiJt7J2dWl71Kwzem2X3SR6u2vjFtAAtXH3athkaQ9RGpJbA+73DA==","signedAt":"2026-06-20T11:59:50.321Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/dealcode","artifact":"https://unfragile.ai/dealcode","verify":"https://unfragile.ai/api/v1/verify?slug=dealcode","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"}}