Financial Data and Key Metrics Changes - Revenue grew 46% year over year to $18.4 million, exceeding guidance [6][15] - Adjusted free cash flow rose 88% to $4.8 million, marking the seventh consecutive quarter of positive adjusted free cash flow [11][19] - Adjusted EBITDA improved by $3.4 million year over year, reaching $3 million [15][19] - Gross margin increased to 59%, up from 54% a year ago [17] Business Line Data and Key Metrics Changes - Subscription revenue totaled $9.3 million, showing sequential growth [16] - Content licensing revenue surged over 425% year over year to $8.7 million, driven by AI training fulfillments [16][19] - Advertising business is still developing, with new initiatives launched on various platforms [10] Market Data and Key Metrics Changes - Licensing revenue is expected to exceed subscription revenue by 2027, possibly earlier [12] - The company engaged with nine key partners across various media formats, delivering over 1.5 million distinct assets [7] Company Strategy and Development Direction - The company aims to solidify its position as a leading provider of AI training data, with plans to double its content library in 2026 [12][41] - Focus on cost discipline and rationalizing the cost base to support pricing power and durable growth [11][12] - Plans to install a leader for the advertising business in early 2026 to capture advertising opportunities [10] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in continued double-digit growth in both revenue and cash flow driven by subscriptions, licensing, and advertising [13] - The company anticipates that overall subscription revenue will grow faster in 2026 than in 2025, supported by a strong launch pipeline [12][57] - Management acknowledged the need to smooth out revenue fluctuations in licensing through operational and contractual means [31] Other Important Information - The company reported a net loss of $3.7 million for the quarter, attributed to one-time charges and non-cash stock-based compensation [18] - The balance sheet remains strong with over $29 million in liquidity and no debt [13][19] - The expiration of warrants reduces potential dilution and eliminates lingering share overhang [20] Q&A Session Summary Question: Why is the company investing in lower-margin media when licensing returns are higher? - Management clarified that they are promoting an internal candidate to enhance AI relationships and need seasoned sales leaders to drive revenue generation [24][27] Question: How will the company smooth out revenue fluctuations in licensing? - Management indicated that increasing the roster of partners and structuring agreements as Content as a Service (CaaS) will help reduce revenue lumpiness over time [31][32] Question: How has AI licensing evolved over the last year? - Management reported 18 fulfillments across nine partners, with expectations that existing partners will contribute 60% to 80% of AI licensing revenue [35][36] Question: Can you explain the stock-based compensation in the quarter? - Management explained that the high stock-based compensation was due to market-based awards granted during the quarter, which will be expensed over a more aggressive timeline [52][53] Question: What is the outlook for subscription services in new markets? - Management expressed confidence in subscription revenue growth due to new partnerships and distribution agreements, with plans for new pricing and packaging in 2026 [57][58]

camp network at $32m building ai training data licensing rails. universal and warner finalizing deals this quarter. story protocol at $1.8b for ip derivatives. camp captures the actual $2.8b ai music licensing market not remixes. 56x valuation gap for the infrastructure record labels need right now ...

rice ai has nvidia jetson robots, $750k presale (33,000% oversubscribed), 500 deployed units mining data, and dwf labs backing. what did they choose to do with all that infrastructure? create bitcoin mining for ai training data. ...

$SAPIEN @JoinSapien is a decentralized data foundry that transforms collective human knowledge into high-quality AI training data.Backed by $19.2M from leading VCs, it gamifies data labeling at the AI × crypto frontier. Learn more 👇https://t.co/yXJkUuvB7Q ...

Core Problem & Solution - AI model commoditization and decreasing compute costs highlight data as the primary bottleneck [1] - The company addresses the data bottleneck by coordinating data collection, labeling, and curation using crypto incentives [4] - Crypto and blockchain technology facilitate the placement of data and IP on an immutable ledger, enabling tracking, attribution, and licensing via smart contracts [7] Competitive Advantage & Market Opportunity - Meta Scale AI's partial acquisition created a vacuum in the AI data space, presenting an opportunity for competitors [6] - The company's decentralized approach allows collaboration with any IP, offering flexibility [15] - The company has already secured contracts, indicating market demand [13] Data Acquisition & Application - The company uses crypto incentives to coordinate data collection on a global scale, compensating contributors with stablecoins or other crypto tokens [6] - The collected data, including egocentric video footage from diverse settings, is crucial for training AI models, such as humanoid robots [9] - Contributors set licensing usage terms on the blockchain, ensuring IP safety [12] Business Model & Demand - The company acts as an agent to secure contracts, connecting data providers with AI model developers [13] - Many organizations are willing to work with the company, some dropping contracts from Scale AI [14][15]