Re

Real-time freelancer marketplace with per-second billing

Hacker News

Real-time freelancer marketplace with per-second billing

Hi HN! I'm launching Gigs.Quest, a platform where startups can hire freelancers instantly through live video rooms. Problem: Traditional freelancing platforms are slow. You post a job, wait for proposals, interview candidates, negotiate rates, then finally start work. For quick tasks, this is overkill. Solution: Create a room, describe what you need, and qualified talent joins live within 5-12 minutes. Collaborate via HD video and screen sharing. Pay per second ($0.02/sec = $72/hr). All sessions recorded. Why this works: • For startups: Get immediate help without hiring overhead • For freelancers: Monetize expertise without bidding/proposals • Trust: All sessions recorded, transparent earnings, Stripe-backed payments Real use cases from beta: • Debugging production outage (saved 3 hours vs hiring process) • Quick design mockup review (12 min session, $14 cost) • Architecture consultation for new feature (45 min, $54) Tech details: • Pre-authorization holds that scale (start at $5, double at 80% usage) • LiveKit for video infrastructure • Convex for real-time database • Stripe Connect for instant payouts Challenges I'm working on: 1. Quality control (how to prevent low-quality participants?) 2. Discovery (how do freelancers find rooms?) 3. Pricing (is $72/hr the right rate?) I'd love feedback from both sides of the marketplace. What am I missing? Live at: https://gigs.quest

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Product HuntOn track for Day 1 leaderboard · Strong signals: stripe, new, tasks · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: collaborate · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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