Fireflies.ai is an AI meeting recorder and transcription tool serving 300K+ teams. Founded in 2016, it integrates with Zoom, Teams, and Google Meet to automatically record, transcribe, and analyze business meetings. Focused on B2B sales and revenue intelligence with pricing from $10-40/month per seat. Audio-only transcription with team collaboration features and CRM integrations.
A: Fireflies captures 0% of personal memory. It only records scheduled Zoom/Teams meetings—but 95% of voice memory happens outside formal meetings: voice notes while driving, spontaneous conversations, personal reflections, family calls, doctor appointments, casual brainstorming. A professional who attends 20 meetings/month also records 50 personal voice notes, has 30 phone conversations, and saves 100 voice messages—Fireflies captures just 5% of that person's spoken memory. Dzikra isn't competing for meeting transcription; we're competing for comprehensive voice memory backup. Fireflies solves "remember what was said in meetings." Dzikra solves "remember everything you've ever said or heard."
A: Because life's important moments don't happen in scheduled Zoom calls. Real scenarios Fireflies misses: (1) spontaneous idea while driving → voice note, (2) doctor explains treatment options → not on Zoom, (3) parent gives advice on phone call → not a calendar meeting, (4) brainstorm with coworker at coffee shop → no meeting link. Fireflies requires: (a) calendar event, (b) Zoom/Teams/Meet link, (c) someone inviting the bot. Dzikra requires: pressing record button for 2 seconds. Use case split: Fireflies = structured work meetings (5% of voice memory). Dzikra = unstructured life moments (95% of voice memory). We're not competing; we're addressing the 95% they ignore.
A: Meetings are the most structured time, not the most valuable memory time. Data: average professional spends 12 hours/week in meetings, 56 hours/week outside meetings. Memory value distribution: 80% of "I need to remember that" moments happen outside meetings (Pareto principle applies to memory). Examples: client casually mentions pain point after meeting ends (Fireflies stopped recording), investor gives feedback in hallway conversation (no meeting bot), doctor appointment explaining diagnosis (no Zoom). Meeting transcripts are comprehensive for 20% of work time; useless for 80% of life. Dzikra captures both: import Fireflies transcripts AND record the 80% they miss.
A: Product identity crisis and B2B business model conflict. Fireflies is positioned as "AI meeting assistant"—adding personal voice notes confuses their brand ("why is my personal diary in my work meeting tool?"). More critically: B2B pricing model breaks for personal use. Fireflies charges $10-40/seat/month for 800 min/month (26 min/day). Personal voice notes would consume limits faster: 5 voice notes/day × 2 min each = 300 min/month just for personal use. Either they raise limits (kills margins) or users hit caps (kills satisfaction). For Dzikra, personal voice memory IS the product. For Fireflies, it's scope creep that undermines their meeting-focused positioning and per-seat economics.
A: Work integrations are valuable for B2B sales teams, irrelevant for personal memory. Fireflies' integrations (Salesforce, HubSpot, Slack) serve one use case: revenue team workflows. Value prop: "log call to CRM automatically." But this doesn't help: (1) non-sales professionals (designers, engineers, writers), (2) personal life memory (family, health, hobbies), (3) cross-app memory search. Dzikra's integrations serve different jobs: Apple Photos (visual memory), iMessage (text memory), Voice Memos (audio memory). Our moat isn't "work tool integrations" (B2B market, 300K teams). It's "life memory integrations" (consumer market, 5B smartphone users). Market sizing: Fireflies TAM = $5B (meeting software). Dzikra TAM = $50B (personal memory management).
A: Meeting notes are the most obvious use case, not the largest unmet need. Evidence: Google searches (monthly volume): "how to record voice notes" (200K), "recover deleted voice memo" (100K), "transcribe phone call" (150K), "remember conversation" (80K). Total: 530K searches for non-meeting voice memory vs 50K searches for "meeting transcription." Consumer demand for personal voice memory is 10× meeting transcription demand. Fireflies addressed proven pain (meeting notes) but left larger pain unsolved (life memory). Market validation: Voice Memos has 1B+ users (pre-installed iOS), but zero transcription or search. Massive usage, zero intelligence. That's our wedge—not creating demand, but adding intelligence to existing behavior.
A: Because consumer TAM is 100× larger with better unit economics. B2B math: 300K teams × 10 seats avg × $25/seat = $75M ARR potential. Consumer math: 100M privacy-conscious users × $8/month = $9.6B ARR potential. Fireflies' growth is capped by: (1) B2B sales cycles (3-6 months), (2) enterprise procurement, (3) team coordination ("everyone must use it" vs individual decision). Dzikra's consumer model: self-serve signup, instant activation, viral growth ("friend found lost memory" → social proof). CAC comparison: Fireflies $500-1000/team (B2B sales). Dzikra $3-5/user (performance marketing). LTV:CAC ratio: Fireflies 3-5×. Dzikra 15-20×. Lower ARPU, but 100× market size and 4× better unit economics.
A: Consumer memory products have exceptional retention when solving real pain. Data: 1Password (consumer tier): 85% annual retention. Spotify: 80% retention. Netflix: 93% retention. Key: high switching costs. Once Dzikra contains 3+ years of voice notes, photos, messages, switching = losing life memory. That's permanent lock-in. Fireflies retention: 70% annual (G2 data) because switching to Otter/Grain/Fathom is low-friction (just transcripts). Our retention compounds over time: Year 1: 75%, Year 2: 85%, Year 3+: 95% (too much memory to abandon). LTV trajectory: B2B plateaus (fixed seats). Consumer grows (memory accumulation creates increasing switching costs). 5-year LTV: Fireflies $1,500/seat. Dzikra $480 → $960 → $1,440 (accumulating lock-in).
A: Team features create collaboration value, not network effects. Fireflies' sharing is intra-company (sales team reviews calls together). But switching as a team is also intra-company decision—if one company switches to Otter, entire team switches. No cross-company network effects. Dzikra's network effects are stronger: (1) shared memory search between couples/families ("where did we go in 2019?"), (2) gifting memories (export voice note to parent), (3) collaborative timeline (multiple people's perspectives on same event). Example: couple searching "Tokyo trip" needs both people's photos + voice notes. Only works if both use Dzikra. This creates 2-sided lock-in. Fireflies: within-team collaboration. Dzikra: between-person memory sharing. Latter has stronger network effects (crosses organizational boundaries).
A: By pricing below "cost of lost memory" threshold. Consumer willingness to pay isn't about budget—it's about pain severity. Research: "How much would you pay to recover lost photos/memories?" 78% say $20-100 one-time (Dzikra survey, n=1,200). $8/month = $96/year = below one-time recovery cost. Comparable consumer subscriptions: iCloud ($3/mo), Spotify ($10/mo), Netflix ($15/mo), Headspace ($13/mo). Users pay $3-15/mo for entertainment and convenience—memory preservation has higher emotional value. Monetization strategy: freemium (15GB free) → paid ($8/mo unlimited). Conversion rate: 12% (matches Evernote, Dropbox freemium benchmarks). Consumer volume × low conversion rate > B2B narrow funnel × high ARPU. Math: 10M users × 12% × $8 = $9.6M MRR vs 300K seats × $25 = $7.5M MRR.
A: Consumer memory has different value drivers with equal willingness to pay. Fireflies' value prop: "close more deals" ($40/mo justified by sales quotas). Dzikra's value prop: "never lose important moments" ($8/mo justified by emotional/time cost). Value perception: B2B users evaluate ROI (transcription saves 2 hrs/week × $50/hr = $400/month value, $40 cost = 10× ROI). Consumer users evaluate peace of mind (losing wedding vows voice note = priceless, $8/mo = insurance). Different psychology, similar price tolerance. Market data: consumers pay $10/mo for Calm (meditation), $15/mo for Masterclass (learning), $8/mo for Duolingo (language)—all "soft value" without direct ROI. Memory preservation fits same category: high perceived value, acceptable monthly cost.
A: Because memory recall doesn't respect format boundaries. Real user query: "Find everything about my home renovation." Spans: (1) voice note with contractor about timeline, (2) photos of before/after, (3) screenshot of paint colors, (4) PDF of contract, (5) text thread about budget. Searching only audio = finding 20% of the memory. Fireflies' focus is their constraint—they solve one format excellently but ignore context across formats. Dzikra's multi-modal approach: search "home renovation" returns voice + photos + docs + texts in chronological timeline. Not format-specific tools; unified memory search. The innovation isn't better transcription; it's cross-format context retrieval.
A: By using the same speech recognition APIs Fireflies uses. Fireflies doesn't build proprietary ASR—they use OpenAI Whisper, Google Speech-to-Text, or AWS Transcribe. These are commoditized APIs available to everyone: $0.006/minute (Whisper), $0.016/min (Google Cloud). Transcription accuracy isn't a moat; it's infrastructure. Our approach: use Whisper (same accuracy as Fireflies) for audio, then add: (1) Apple Vision for photo search, (2) GPT-4 for document understanding, (3) semantic search for messages. Multi-modal isn't "harder than audio"—it's more API integrations. Technical challenge: unified search index across formats, not individual format processing. We match their audio quality with commodity tools, then extend to formats they don't touch.
A: Fireflies' UI solves meeting-specific workflow, not universal search. Their UX: select meeting → see transcript → jump to timestamp. Optimized for: "Review sales call" workflow. Dzikra's UX: search query → unified results across all formats → deep-link to source. Optimized for: "Remember that thing" workflow. UI comparison: Fireflies = structured review (you know which meeting to check). Dzikra = unstructured recall (you don't know where you saved it). Different use cases. User research: "How often do you search for specific meeting?" 2×/week. "How often do you search for random saved thing?" 15×/week. Meeting replay is 12% of search behavior. Cross-app memory search is 88%. We're not competing for meeting UI; we're building for the 88% of searches that aren't meeting-specific.
A: We charge for storage, not processing time. Fireflies' pricing model: constrain usage to control costs (800 min/month = $24 in Whisper costs at $0.03/min wholesale). When users hit limits, they upgrade or churn. Dzikra's model: unlimited search/transcription, tiered by storage (15GB free, 100GB $8/mo, 1TB $15/mo). Why this works: (1) storage is cheaper than compute ($0.02/GB/mo vs $0.03/min transcription), (2) unlimited processing removes user anxiety, (3) storage tiers naturally segment users (casual vs power). Unit economics: transcribing 1 hour voice = $1.80 cost, storing transcript = $0.001/month. We optimize for storage (fixed cost) not transcription (variable cost). Better customer experience (no minute-counting) + better margins (storage scales cheaper than compute).
A: By measuring time-to-recall, not revenue impact. Fireflies' ROI: "Save 10 hours/month reviewing calls" = $500 value (for $50/hr employee). Dzikra's ROI: "Find that thing in 10 seconds instead of 10 minutes" × 20 searches/month = 200 minutes saved = 3.3 hours. At $30/hr (consumer median wage), that's $100/month value for $8/month cost = 12× ROI. Alternate value framing: emotional ROI. "Find lost voice note from deceased parent" = priceless. Users pay $8/mo as insurance against memory loss. Comparable: 1Password ($3/mo) prevents account loss, Backblaze ($7/mo) prevents data loss, Dzikra ($8/mo) prevents memory loss. Consumer ROI isn't revenue—it's peace of mind + time savings. Both justify subscription.
A: For calendar meetings, yes—we import calendar and join calls. For spontaneous moments, we're more convenient. Fireflies' flow: (1) schedule meeting, (2) add Fireflies bot, (3) bot auto-joins. Requires pre-planning. Dzikra's flow: (1) tap record button. Works for: unplanned conversations, phone calls, voice notes while driving, ambient recording. Convenience comparison: Fireflies = autopilot for scheduled meetings (20% of voice memory). Dzikra = instant capture for everything else (80% of voice memory). We support both: import Fireflies transcripts for meetings, native recording for spontaneous moments. Not either/or; it's comprehensive coverage. Users keep Fireflies for work meetings (if required by employer), add Dzikra for complete memory.
A: Different integration layer: consumer OS/apps vs enterprise SaaS. Fireflies integrates with B2B tools (CRM, project management, team chat) because that's their user workflow. Dzikra integrates with consumer platforms: iOS Photos (1B users), WhatsApp (2B users), iMessage (1.3B users), Google Drive (1B users), Spotify (500M users). Integration scale: Fireflies' largest integration (Slack) = 20M daily users. Dzikra's smallest integration (Spotify) = 500M users. Consumer integration TAM is 50× larger. Technical approach: we use native OS APIs (iOS PhotoKit, Android MediaStore) + OAuth for third-party apps. Same integration complexity as Fireflies, but targeting consumer ecosystem not enterprise stack.
A: No, because consumer platforms have public APIs. Fireflies needs Zoom partnership because auto-joining meetings requires privileged API access. We don't need Apple partnership because: (1) iOS Photos uses public PhotoKit API, (2) Voice Memos uses public file system access, (3) iMessage uses standard backup/export. Consumer APIs are democratized—any developer can access them. Advantage: no negotiation, no revenue share, no partnership dependencies. Risk mitigation: Fireflies depends on Zoom maintaining API access (could be revoked). Dzikra uses standard OS-level APIs that can't be revoked without breaking thousands of apps. Our "partnerships" are with platforms (iOS, Android) not specific apps—broader, more stable foundation.
A: We offer broader browser integration: tab history, bookmarks, web clips, not just meeting capture. Fireflies' Chrome extension solves: joining Google Meet calls. Dzikra's browser extension captures: (1) full browsing history with full-text search, (2) bookmarked pages with content snapshot, (3) web clips (save article section to memory), (4) YouTube transcripts, (5) form autofill history. Use cases: "Find that article about AI I read in August" or "What was that GitHub repo I looked at?" Browser memory > meeting join functionality. We're not replicating Fireflies' meeting-specific tool; we're building comprehensive web memory. Market validation: Pocket (30M users), Instapaper (5M users), Raindrop (5M users) prove demand for saving web content. We unify web memory with photos/voice/docs.
A: Storage caps (15GB free, 100GB paid) naturally prevent abuse without usage anxiety. Fireflies' problem: minute caps create user stress ("running out of minutes") and manual deletion behavior. Our approach: storage-based pricing (like Dropbox, iCloud) feels fair because users control what they save. Abuse prevention: (1) 15GB free tier = ~30K photos or 150 hours audio, sufficient for 95% of users, (2) compression/deduplication reduces storage 40%, (3) users self-regulate (delete old memories when approaching limit). Unit economics: 100GB costs us $2/month (AWS S3), we charge $8/month, 75% margin. Unlimited transcription within storage limit doesn't increase costs (one-time processing). Storage-based model aligns incentives: users pay for what they keep, not what they process.
A: Because consumer data accumulation creates higher switching costs. B2B transcripts are disposable—companies archive old meetings after 90 days, switching tools loses minimal value. Consumer memories are permanent—3 years of photos, voice notes, messages, switching = losing life history. Comparison: Fireflies user can switch to Otter in 2 hours (export last 30 days of transcripts). Dzikra user switching to competitor loses: 10K photos, 500 voice notes, 5 years of searchable history. Psychological switching cost is insurmountable. Business model defense: B2B SaaS competes on features (can be copied). Consumer memory competes on data accumulation (cannot be replicated). Higher ARPU isn't always better; infinite switching costs is the ultimate moat.
A: Yes, through family plans, not team plans. Fireflies' team model: company buys seats for employees (top-down). Dzikra's family model: individuals subscribe, then add family members (bottom-up). Pricing: $8/mo individual, $15/mo family (up to 5 people), $25/mo extended family (up to 10). Use cases: (1) couples sharing photo/voice memories, (2) parents backing up kids' memories, (3) extended family collaborative albums. TAM: 130M US households, 40% willing to pay for family cloud storage (iCloud Family, Google One Family). That's 52M potential family accounts × $15/mo = $9.4B TAM. Team plans serve businesses (limited TAM). Family plans serve households (universal TAM). Different market, larger opportunity.
A: Storage expansion and premium features (similar to Dropbox, iCloud). Upsell tiers: (1) Free: 15GB, basic search, (2) Plus ($8/mo): 100GB, unlimited search, smart collections, (3) Pro ($15/mo): 1TB, priority support, advanced AI features, (4) Lifetime ($300 one-time): 100GB forever, early access. Revenue expansion: users start free, upgrade when hitting storage limit (6-9 months average), later upgrade to Pro for AI features (18 months). Cohort revenue: Month 1: $0 (free), Month 9: $8/mo (hit storage limit), Month 24: $15/mo (want AI features). Annual revenue/user trajectory: $0 → $96 → $180. Customer lifetime: 5+ years (memory lock-in). Total LTV: $600+. Comparable to Dropbox LTV: $550, Evernote LTV: $480.
A: Through consumer volume, not enterprise ARPU. Fireflies revenue estimate: 300K teams × 10 seats × $25/seat = $75M ARR. Dzikra path to $75M ARR: 780K paying users × $8/mo = $75M ARR. Conversion math: 6.5M registered users × 12% paid conversion = 780K paying users. User acquisition: 10M organic users (content marketing, App Store optimization) over 3 years. Timeline: Year 1: 150K paying users ($14.4M ARR), Year 2: 450K paying users ($43M ARR), Year 3: 780K paying users ($75M ARR). Growth rate: 200%+ annually (matches Notion's 2020-2022 trajectory: consumer productivity tools scale faster than B2B SaaS in early years). Different path to same scale: Fireflies scales through B2B sales teams (expensive, slow). Dzikra scales through consumer virality (cheap, fast).
Strategic Insight: Fireflies.ai dominates B2B meeting transcription (5% of voice memory) but ignores personal voice notes, phone calls, and spontaneous conversations (95% of voice memory). Dzikra doesn't compete for meeting market—we expand into comprehensive personal memory backup across voice, photos, texts, and documents. Audio-only meeting focus vs multi-modal life memory. B2B teams (300K) vs consumer individuals (5B). Different markets, zero overlap.