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Research Comparison

Updated

Markdown

Summary

Vertical AI revenue intelligence platform for B2B software infrastructure companies. Account Intelligence Graph captures prospect-level intent signals to target and engage technical buyers.

Funding

$20M Seed

Founded

2023

Team

35

onfire.ai

Critical Notes

- Vertical AI built exclusively for selling to technical buyers - De-anonymization links Reddit, Discord, GitHub activity to individuals and accounts - Niche: little value if not selling to engineers, developers, or IT security - Privacy and ethics risk from unmasking pseudonymous users - Seed-stage, launched Oct 2025, 35 staff - SOC2 Type II, ISO 27001, GDPR, CCPA compliant

Key Features

- Account Intelligence Graph tracking 50 million engineers - Prospect-level intent signals from Reddit, Discord, and GitHub - Entity resolution and de-anonymization of public activity - Real-time technographics verified through technical activity - Model Context Protocol (MCP) server for AI agents like Claude - CRM and Sales Engagement integrations - AI-powered account research and prioritization

Details

Officially Onfire AI Ltd., HQ Ramat Gan, Israel. Founded 2023 by Tal Peretz, Shahar Shavit, Nitzan Hadar; two years in stealth. $20M Seed (Oct 2025) co-led by Grove Ventures and TLV Partners, with IN Venture and Leumi Tech. Revenue undisclosed; claims over $50M in deals closed for early SaaS clients. ~2,715 LinkedIn followers. Sales-led: direct and enterprise selling to B2B software infrastructure vendors, credit and contact-based pricing with volume discounts. Free trial and up to 50 free leads gated behind qualification call and 30-minute demo. Closed-source; mines open-source data (GitHub, OSS adoption) for signals but publishes no code.

Signalscompared to Common Room

1st Party

  • Bi-directional CRM and sales engagement sync; product trials, website visits, CRM records; AI agent merges private CRM data with graph without cross-tenant exposure
  • CRM vendors not named; no marketing automation, chat/support, customer success, data warehouse, or paid ads; no named sales engagement list

2nd Party

  • Public developer communities (GitHub PRs/forks/issues/stars, Reddit, Discord, Stack Overflow, Slack, Hacker News); event platforms Luma and Meetup
  • No owned-community platforms, review sites (G2), social (LinkedIn, X, YouTube), commerce; community count inconsistent (25k vs 100k)

3rd Party

  • Technographics from developer activity; hiring patterns and job changes; offline event attendance; firmographic and IP cross-reference; 50M engineers, 5M daily events
  • No intent vendors (6sense, Bombora, Demandbase, G2); no news signal; no non-technical buyer coverage

Custom

  • MCP server (Claude/ChatGPT); Chrome extension for LinkedIn Sales Navigator; Data Access REST API; bespoke AI tuning for golden personas
  • No documented CSV, Zapier, or Google Sheets; webhooks only in alerts; custom signal ingestion unclear

1st Party: bi-directional CRM and sales engagement sync; ingests trials, website visits, CRM records; AI agent merges private data with graph without exposing it to other users. 2nd Party: monitors public developer communities (GitHub, Reddit, Discord, Stack Overflow, Slack, Hacker News); tracks PRs, forks, issues, stars for OSS adoption; de-anonymizes posts to contactable individuals. 3rd Party: Account Intelligence Graph of 50M engineers and 5M daily events; technographics from hiring, job changes, developer activity; Luma and Meetup event attendance; firmographic and IP cross-reference. Custom: MCP server for Claude; Chrome extension for LinkedIn Sales Navigator; REST API; bespoke golden persona tuning; CSV, Zapier, webhooks undocumented.

Identitycompared to Common Room

Enrichment

  • Verified technographics; real-time intent evidence appended to CRM; contact and company enrichment API endpoints
  • No waterfall enrichment; no verified phone numbers; no AI quality control; 50M engineer directory; credit-based

AI Powered

  • NLP de-anonymization engine; evidence trail on every identity; scoring from closed-won patterns; feedback loops from outreach, meetings, win/loss
  • Handle/text-based matching, no image matching; cold start for new customers; needs clean CRM data

Identity

  • Resolves GitHub, Reddit, Discord, Hacker News, Stack Overflow handles, signup emails, LinkedIn profiles to named individuals; prospect-level intent
  • No documented merge review or manual merge; no ongoing job-change maintenance; engineers only; privacy exposure

Identity: resolves pseudonymous profiles across GitHub, Reddit, Stack Overflow, Discord, Slack, Hacker News and events to named individuals via usernames, signup emails, LinkedIn; prospect-level, not account-level. Enrichment: technographics inferred from developer signals and OSS adoption; titles, roles, contacts, firmographics, funding, hiring velocity; real-time intent evidence appended to CRM; contact and company API endpoints. AI: NLP de-anonymization engine; evidence trail for every insight; scoring from closed-won commonalities; continuous learning from outreach, meetings, forecast changes, win/loss.

Automationcompared to Common Room

Combine

  • Account Intelligence Graph joins CRM, community footprints, event attendance, technographics for triggers and filters
  • Fewer sources; no G2, social, intent vendors, marketing automation, CS, warehouse, ads

Score

  • ML scoring on closed-won patterns; weights individual technical signals over company surge; ranked daily queue
  • No clear user-defined rule scoring or custom fields; needs closed-won history; weak outside technical personas

AI Message

  • AI drafts grounded in community pain points, usage trends, real-time intent
  • Drafts only; sending, sequencing, reply tracking external; OpenAI subprocessor; template depth unclear

AI Research

  • Overnight account research briefs; conversational MCP copilot; finds hidden champions, competitive threats, technical challenges
  • Requires customer's own Claude/ChatGPT; no CLI; no documented prompt library; developer footprint scope only

Workbench: daily prioritized ICP account queue with auto-identified technical champion. Workflow: agentic signal-triggered multi-step actions (briefs, CRM updates, draft sequences) with human approval. Alert: custom alerts via MCP copilot or webhooks on GitHub issues, technographic changes, web intent; routed to account owner. Combine: Account Intelligence Graph merges CRM, community footprints, events, technographics, firmographics. Score: AI scoring on closed-won patterns, weighting niche technical signals; ranked daily queue. AI Message: AI drafts grounded in intent signals, usage trends, community pain points. AI Research: overnight account research; MCP conversational copilot to find champions, threats, technical challenges.

Supportcompared to Common Room

Systems

  • Email (support@, privacy@); web forms; dedicated human support in trial; MCP and REST API; trust center; AWS (US/DE), Auth0, OpenAI, Mixpanel, LogRocket
  • No chatbot, live chat, status page, or in-app help; SLAs unclear; small team scale risk

Content

  • docs.onfire.ai (API, MCP, identity resolution, enrichment); resource center with guides, case studies, glossary, blog, AI GTM Calculator; YouTube demos; security and compliance docs
  • Developer-skewed docs; no academy or certification; shallow case studies; $50M closed claim unverified

Community

  • none
  • No user community, forum, template gallery, or peer network

...

Status: Watch

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