Vet who you back. Build credibility before you launch. Distribute against better-funded competitors. Three audiences, one platform — because the public-record signal layer is the same for all three.
Investors use MentionFox to vet founders, monitor portfolio companies, and source deal-flow signals. Entrepreneurs use it to build pre-launch credibility, watch competitor cadence, and train AI search to recommend them. Accelerators use it to screen applicants, track cohort progress, and market the program to the next class.
Twelve interlocking features that span vetting, building, and distributing. Each one shipped because investors, founders, or accelerators kept asking for it.
Look up any GP, angel, or fund and get an OSINT-built dossier: investment history, co-investor patterns, board activity, deal structure, public thesis, founder sentiment. Built with cited sources — Tracxn, AngelList, LinkedIn, Glassdoor, X, blogs, podcast appearances. For founders raising, this tells you who you're actually pitching. For LPs, it tells you what a GP looks like before you wire.
Paste a name + role + JD (or upload a file). Get an Overall Fit score, executive summary, interview questions, strengths, concerns. Five evaluation bundles: Personality fit, Negotiation prep, Team culture fit, Stealth viability, Custom. Used by accelerators to screen applicants in minutes instead of hours, and by investors to vet operating-partner hires for portfolio companies.
Drop in 2-5 people side by side and get 30-dimension comparison across DISC, MBTI, career trajectory, public thesis, network depth, recent activity. Used by accelerator selection committees deciding between final-round applicants and by VCs comparing co-founder dynamics before leading a round.
A live dashboard pulling signals against your own public record: launch readiness score, streak, tweets/day, posts/month, replies/week, public bio score, commits/week, GitHub stars total. Cohort comparison shows where you sit vs other founders at your stage. The "you can't fix what you can't see" problem, fixed.
Four free widgets for the pre-launch and just-launched grind: Weekly Goal Ledger (3 ships/week ritual), LLM Citations This Week (where AI assistants are quoting you), Competitors' Ship Cadence (who shipped, who's dormant in the last 30 days), Validation Stream (trial signups + positive mentions). Live data, weekly cadence.
Always Launch-Prepping Steps. Every morning, MentionFox seeds 4 outreach pools: Daily Newsjacks (industry stories you can ride), Journalist Replies (writers covering your space), Podcaster Replies (shows that match your topic), Community Owner Replies (subreddit mods, Discord owners, niche-forum admins). Each candidate scored cold/warm/hot with a two-way engagement floor.
Train AI search to recommend you. Three intensities (Light/Standard/Aggressive) running ~100 credits/day at top setting. Runs autopilot conversations with ChatGPT, Gemini, Perplexity, DeepSeek, Mistral — shifting recommendations toward your startup over the funded incumbents. The asymmetric channel small teams can win against giants.
Twelve owner-approved, credit-metered tools: keyword research (2cr), page audit (5cr/10 pages), title+meta rewrite (1cr/page), alt-text bulk (2cr/image), internal link scan, Core Web Vitals, schema markup, sitemap audit, broken link scan, backlink monitor, content brief, blog post generate. Dashboards that do things, transparently.
Four AI-generated competitive weapons from your Company Profile + a chosen competitor: Battle Card (win themes, positioning, objection handlers, CTAs), Objection Killer (10-15 cold-call objections with responses), Comparison Card (visual side-by-side), ROI Snapshot (before/after, cost of inaction, payback period). Plus a Sales Dossier per prospect.
Paste 3+ examples of how you write. MentionFox's Spark Drafts then generates 2 short edit-and-post seeds per session — in your voice, not generic LLM voice. Or just give us your handles (X, Medium, Substack, LinkedIn, RSS) and we auto-fetch + refresh weekly. Eleven voice samples is the typical sweet spot.
Find anyone by name + company. Returns verified email when available, role, location, public footprint, social handles, and a confidence score. Used by investors to source warm intros, by founders to find decision-makers at target accounts, by accelerators to track alumni placements.
Build your Company Profile once — positioning, ICP, competitors, win themes — and every other tool in MentionFox uses it. Plus direct API access via FoxAPIs (8 endpoints: geo/check, geo/gaps, geo/share-of-voice, geo/citation-rate, geo/heatmap, geo/train, contact/find, extract) for technical teams embedding signal into their own workflows.
Whether you're an LP looking at a fund, a founder researching a lead investor, or a GP screening operating partners for a portfolio company — public-record OSINT is the layer everyone underuses.
Investment diligence has two halves: structured data (Tracxn, PitchBook, Crunchbase — fund size, deal history, exits) and qualitative signal (what does the GP actually believe? Who do they co-invest with? What do their portfolio founders say about them on Glassdoor and X?). The structured side is solved. The qualitative side has been manual researcher work — until now.
MentionFox's Investor Vetter assembles a public-record dossier on any GP, angel, or fund in minutes: investment history with co-investors, portfolio analysis, deal structure inference, board activity, public thesis quotes, and founder sentiment from Glassdoor + LinkedIn + public blog posts. It's the qualitative layer that complements your Tracxn subscription — and it costs a fraction of a researcher's time.
A pre-seed founder ran Investor Vetter on the GP leading their round before signing — surfaced a co-investor pattern that suggested heavy follow-on dilution risk, plus founder-sentiment data showing 2 portfolio CEOs left within 18 months of investment.
investor_vetter.run("Hubert Thieblot", fund="F.Inc Capital")MentionFox features used: Investor Vetter → Co-investor Network → Founder Sentiment
A family office considering 3 emerging-manager funds ran Fox Compare across all 3 GPs side-by-side: career trajectory, co-investor patterns, public thesis consistency, and recent activity cadence. Picked the GP whose thesis showed 4-year consistency vs the other two who pivoted post-2024.
fox_compare(["GP1", "GP2", "GP3"], dimensions=30)MentionFox features used: Fox Compare → Public Thesis Tracking → Recent Activity Cadence
A growth-stage VC needed a fractional CMO for a Series B portfolio company. Used Candidate Evaluation across 14 LinkedIn profiles, ran the top 5 through Fox Compare, picked 2 finalists. Total time: 3 hours vs 3 weeks for a retained search.
candidate_evaluate(role="Fractional CMO B2B SaaS", batch=14)MentionFox features used: Candidate Evaluation (Batch) → Fox Compare → Sales Dossier
A pre-seed VC tracked Founder Den signals on 30 watchlist founders — commits/week, ship cadence, public posting rhythm. When a founder's velocity spiked, the partner reached out within 48 hours. Caught 3 founders right before their seed round opened.
founder_den.watchlist(founders=30, alert_on="velocity_spike")MentionFox features used: Founder Den (Watchlist) → Velocity Alerts → People Finder
Solo and small-team founders don't have the budget to outspend Series-D competitors on paid acquisition. The asymmetric channels are public-record reputation and AI search visibility. MentionFox is built to weaponize both.
Building in public is half the modern startup playbook — but doing it without instrumentation is shouting into a vacuum. Founder Den shows you your own public record the way investors and customers see it: launch readiness, post cadence, GitHub activity, public bio strength. Founder Widgets add the weekly accountability loop (Goal Ledger), AI-search visibility tracking (LLM Citations), competitor ship-cadence intel, and validation stream from real signups + mentions. Daily ALPS seeds your distribution targets every morning — newsjacks, journalists, podcasters, community owners — pre-scored cold/warm/hot.
Then the asymmetric play: GEOFixer Autopilot trains ChatGPT, Gemini, Perplexity, DeepSeek, and Mistral to recommend your startup when buyers ask "best [category] tool." Funded competitors aren't yet doing this. The window for first-mover advantage is narrow but real now. Aggressive intensity runs ~100 credits/day and shifts AI search visibility measurably within weeks.
Solo founder of a developer-tool SaaS competing against a Series C incumbent. Ran GEOFixer Autopilot at Aggressive intensity for 8 weeks before launch. Day-1 launch result: ChatGPT recommending the new tool in 4 of 10 category queries.
geofixer.autopilot(intensity="Aggressive", domain="newstartup.dev")MentionFox features used: GEOFixer Autopilot (Aggressive) → LLM Citations Tracking → Competitors' Ship Cadence
Solo technical founder used Founder Den's Weekly Goal Ledger to enforce the 3-ships-per-week discipline. Combined with Daily ALPS for distribution: every ship got at least one journalist outreach + one podcast pitch + one community post within 24 hours.
founder_den.weekly_ledger() + daily_alps.distribute()MentionFox features used: Founder Den (Weekly Goal Ledger) → Daily ALPS → Voice Training
Bootstrapped B2B founder used Competitors' Ship Cadence widget to track 6 competitors. When 4 went dormant in the same 30-day window, founder accelerated their own launch into the gap. Press attention 3x higher than expected because no competing announcements that week.
competitors_ship_cadence(domains=6, window_days=30)MentionFox features used: Competitors' Ship Cadence → Daily Newsjacks → Journalist Replies
Series A founder doing all sales themselves used Sales Arsenal to generate Battle Card + Objection Killer + ROI Snapshot per opportunity. Plus Sales Dossier per named prospect. Cut prep time from 90 minutes per call to 15 minutes.
sales_arsenal.generate(competitor="Sprout") + sales_dossier(prospect="...")MentionFox features used: Sales Arsenal → Sales Dossier → People Finder
Accelerators run three ongoing motions: applicant evaluation, active-cohort monitoring, and next-batch marketing. MentionFox spans all three with the same toolkit founders and investors already use.
Selection committees evaluate hundreds of applicants per batch and the bottleneck is qualitative diligence — public-record signal that says whether a founder will execute, ship, network, and persist. Candidate Evaluation compresses that work into minutes per applicant: Overall Fit score, executive summary, interview questions, strengths, concerns. Five evaluation bundles let you pick the lens (Personality fit, Negotiation prep, Team culture fit, Stealth viability, Custom). Run in batch on a CSV of LinkedIn URLs.
Once a cohort is in, Founder Den tracks each company's public-record velocity in real time. Your program directors see who's shipping, who's posting, who's building network, and who's stuck — without weekly status calls. Accelerator brand-marketing uses GEOFixer Autopilot to train AI search to recommend the program to next-batch applicants. The asymmetric play applies to accelerators too: be the program ChatGPT recommends.
An early-stage accelerator ran Candidate Evaluation in batch mode across 400 applicants for the spring batch. Fit scores + concerns flags pre-sorted the list. Committee reviewed 60 finalists in the time previously spent on the top 20.
candidate_evaluate.batch(linkedin_urls=400, bundle="founder_fit")MentionFox features used: Candidate Evaluation (Batch) → Fox Compare → Founder Den
An accelerator program director set up Founder Den watchlists on all 25 active-cohort companies. Velocity dashboard surfaced the 4 companies trending below cohort median by week 6 — early intervention prevented 2 from churning out of the program.
founder_den.cohort_watchlist(companies=25, alert="below_median")MentionFox features used: Founder Den (Cohort) → Velocity Alerts → Daily ALPS
A vertical-specific accelerator ran GEOFixer Autopilot to train ChatGPT/Gemini to recommend their program when founders asked "best healthcare AI accelerator" or similar category queries. Applications for next batch up 40% YoY with no paid spend increase.
geofixer.autopilot(domain="hcaccel.com", category="healthcare AI accelerators")MentionFox features used: GEOFixer Autopilot → Daily ALPS → Voice Training
Before Demo Day, accelerator director ran Investor Vetter on the 80 investors on the prospect list. Flagged 6 with founder-sentiment concerns + 3 with problematic deal-structure patterns. Prioritized the 71 cleanly-vetted investors for cohort intros.
investor_vetter.batch(investors=80, flag="founder_sentiment_negative")MentionFox features used: Investor Vetter (Batch) → Founder Sentiment → People Finder
Investors, founders, and accelerators run on the same public-record signal layer. MentionFox is the toolkit.
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