{"componentChunkName":"component---src-templates-compete-db-md-js","path":"/compare/hockeystack/ai/md/","result":{"data":{"doc":{"id":"bd89bc7a-beb4-59ad-abf8-9d1ca1361d01","title":"HockeyStack","createdAt":"2026-10-27T21:17:00.000Z","properties":{"Domain":{"value":"https://hockeystack.com"},"Product":{"value":{"name":"Platform"}},"Market":{"value":{"name":"Commercial"}},"Status":{"value":{"name":"watch"}},"Summary":{"value":"AI-powered B2B revenue data intelligence platform that unifies marketing and sales data to provide holistic buyer journeys, multi-touch attribution, and actionable insights."},"Tag":{"value":"AI GTM - B2B Revenue Data Intelligence Platform"},"Funding":{"value":"50"},"Founded":{"value":"2021"},"Team":{"value":"60"},"Details":{"value":"Fully in-person San Francisco team of about 60, growing fast in go-to-market, sales, engineering. $50M round April 2026 after $20M Series A (Bessemer) in late 2025 and $2.7M Seed. 300+ customers, 8-figure ARR. ~80K monthly visits, ~25K social (co-founder Emir Atli 22K+ LinkedIn followers). Sales-led: demo-gated, outbound SDR team, enterprise CTAs. Not product-led: no self-serve or free trial; live preview and template library only. Proprietary closed-source; Atlas and AI agents commercial. Industry: B2B SaaS (revenue operations, attribution, sales intelligence)."},"Features_List":{"value":"- Holistic Buyer Journeys\n- Multi-Touch Attribution\n- Lift and Incrementality Reporting\n- Custom Reports and Dashboards\n- Data Syncing with Source Systems\n- Forward-Looking Insights via AI Agents\n- Identity Resolution and Data Categorization"},"Critical":{"value":"- Event-based data architecture (Atlas) replaces legacy systems-of-record; cookieless tracking captures dark funnel\n- $50M raised April 2026 to launch AI Revenue Agents platform (Odin, Nova) compiling natural language into deterministic workflows\n- Processes 60+ TB of revenue data monthly\n- Deep LinkedIn integration tracks ad impressions and engagements at account level\n- 8-figure ARR, expanding to large enterprise"},"Signals___1st_Party":{"value":"IN: Bi-directional CRM/MAP (Salesforce, HubSpot, Marketo, Pardot, Pipedrive); cookieless fingerprint web visitor tracking; product usage; instant historical CRM backfill\nOUT: Chat/support signals (Intercom, Qualified); customer success signals (Gainsight, Vitally); sales engagement ingestion (Outreach, Salesloft, Apollo, Groove, Nooks, Gong Engage, Smartlead); Zoom Engage/Dialer"},"Signals___2nd_Party":{"value":"IN: LinkedIn Ads impression-level data; Google Ads; Meta; audience and offline conversion sync back to LinkedIn Campaign Manager\nOUT: Open source (GitHub, Scarf); community (Discord, Slack, Discourse, Stack Overflow, Reddit, Khoros, InSided, Influitive); organic social (Twitter/X, YouTube, Medium, DEV, LinkedIn page activity); events (Bevy, Meetup, Gradual, Skilljar); Shopify"},"Signals___3rd_Party":{"value":"IN: Waterfall enrichment (Clearbit, Apollo, ZoomInfo, Clay); intent (G2, Bombora, 6sense, Demandbase); funding and hiring signals\nOUT: Native job change; native news/events; native technographics; TechTarget, Scarf, Toplyne; no owned data asset (licensed pass-through)"},"Signals___Custom":{"value":"IN: API, SDK, webhooks, Zapier, CSV, Snowflake/BigQuery warehouse ingestion into Atlas\nOUT: none"},"P360___Enrichment":{"value":"IN: Contact Enrichment Node in workflows; verified email retrieval; licensed third-party providers; reverse IP account enrichment\nOUT: No proprietary contact database; no out-of-box waterfall; no premium phone tier; no AI quality control on enrichment"},"P360___AI_powered":{"value":"IN: Odin/Nova natural-language queries over stitched profiles and journeys; predictive forecasting and journey analysis trained on resolved data; prompts compile to deterministic workflows and reports\nOUT: AI not used for identity resolution; no AI matching across handles/images/social; no auto-enrichment trigger for net-new contacts"},"P360___Identity":{"value":"IN: Cookieless fingerprinting + reverse IP across devices/sessions; personal email to corporate domain stitching; hashed emails, CRM IDs, auth events; automated CRM normalization, dedupe, reconciliation\nOUT: Account-centric not person-centric; no social handle/image/community matching; no human-review merge or manual merge; fingerprinting privacy risk (GDPR/CCPA); no profile persistence through job changes"},"Auto___Combine":{"value":"IN: Combine first-party behavior, third-party intent (G2, Bombora, keywords, funding, hiring), CRM, and ad engagement in filters, triggers, segments without engineering\nOUT: Limited to ingested sources; no community, open source, or job-change combinations"},"Auto___Score":{"value":"IN: ML account and intent scoring 0-100 trained on historical conversions; multiple custom models; explainable; CRM sync\nOUT: Cold-start problem needing closed-won history; no rules-first impact-points scoring; contact-level scoring not documented"},"Auto___AI_Message":{"value":"IN: Nova generates message snippets and talking points from journey and intent context\nOUT: No sequence/sales engagement delivery path; new capability with minimal proof; quality unsure"},"Auto___AI_Research":{"value":"IN: Odin analyst agent; prompt library (demand gen, ABM); save/schedule prompts via email; recurring Auto Research on account lists by persona; MCP server\nOUT: Weighted to internal analytics over external account research; no community, OSS, or social context; out-of-box prompt depth unsure"},"Signals":{"value":"1st party: bi-directional CRM/MAP (Salesforce, HubSpot, Marketo, Pardot, Pipedrive), cookieless fingerprint web and product usage, instant historical CRM backfill, unified timeline from anonymous touch to closed-won. 2nd party: LinkedIn Ads impression-level data, Google Ads, Meta; syncs offline conversions and high-intent audiences to LinkedIn Campaign Manager; updates dynamic target account lists. 3rd party: waterfall enrichment (Clearbit, 6sense, Demandbase, Apollo, ZoomInfo, Clay); intent from G2 and Bombora; feeds AI account scoring. Custom: API, SDKs, webhooks, Zapier, CSV, Snowflake/BigQuery into Atlas."},"Identity":{"value":"Identity: cookieless fingerprinting + reverse IP for continuity across devices, browsers, sessions; stitches anonymous browsing, personal email, corporate domain into one account journey; deterministic signals (hashed emails, CRM IDs, auth events); automated normalization, dedupe, reconciliation at person and account level. Enrichment: Contact Enrichment Node retrieves verified emails and reachability attributes; licensed third-party providers; real-time reverse IP maps anonymous activity to company domains. AI: Atlas feeds predictive forecasting and journey analysis; Odin and Nova query stitched profiles, journeys, attribution in natural language."},"Automation":{"value":"Workbench: AI-assisted GTM workbench, not a standalone to-do app; creates, assigns, prioritizes tasks in CRM. Workflow: visual if-this-then-that canvas (Source, Transform, Logic, Destination); GTM-native objects. Alert: Slack node with @mentions, custom instructions, dynamic variables. Combine: first-party, intent, CRM, ad data usable together in workflows without engineering. Score: ML 0-100 account and intent scores, multiple models, explainable, CRM sync. AI Message: Nova writes snippets and talking points. AI Research: Odin prompt library, scheduled prompts via email, recurring Auto Research on account lists."},"Support___Systems":{"value":"IN: Pylon ticketing with AI triage; shared Slack and Teams channels; live chat; email; docs site; Notion guides\nOUT: Single-site in-person SF team; SLAs by tier unsure"},"Support___Content":{"value":"IN: docs.hockeystack.com (Getting Started, Marketing Intelligence, Deal DNA, MCP, Security Audit Logs); HockeyStack 101 video series; async written guides\nOUT: Attribution-centric training; thin docs for agents/workflows/deals; no certification or academy"},"Support___Community":{"value":"IN: Template library; live preview dashboard; founder-led LinkedIn presence; private per-customer Slack/Teams channels\nOUT: No public user forum or community; no user-generated templates; no peer learning"}}}},"pageContext":{"id":"bd89bc7a-beb4-59ad-abf8-9d1ca1361d01"}},"staticQueryHashes":[]}