Meero

Type

• Convolutional neural network (for image processing)
• “Meero uses a dual-deep convolutional neural network involving global and local feature extraction on a multi-scale basis, in order to make the algorithm thoroughly learn from the manually enhanced photographs, and to make it robust to changes in lighting (including white balance and color grading), scene semantics, and capture defects (such as noise or motion blur)”

  AI use

• Advance the field
  • Recently started trying to advance applied research in the fields of computer vision and deep learning through contributions to academic literature
  • Mostly relied on applying advances made by others
• Enable resource integration between service providers and beneficiaries
  • Used to drastically reduce time to deliver edited images to brands
  • Used to streamline gig contracting between photographers and brands

AI useRate of return on customer’s investment to make AI work

Immediate:

• Brands (customers) wait less time and pay less money to acquire high volumes of images with greater standardization
• Photographers can increase income by accepting gigs from Meero (effectively outsourcing customer acquisition, editing and billing)
• Photographers can increase capacity to take more photos on site by using Meero service to outsource editing tasks

Long term:

• Brands – greater annual sales from having recent, relevant, high-quality and consistent imagery on their websites or the 3^rd party e-commerce platforms they use to sell
• Photographers increase their personal income

Databases

• Unique 25-million photograph database that is used for machine learning
• Thousands of finished photographs (edited)

Quantum Computing

• N/A

Assets

• Computer vision deep learning AI
• Marketplace user interface that connects customers (brands) and service providers (photographers)
• Cloud-based performance improvement tools specialized for their users
• High-quality, specialized tech team (80 growing to 300)
• Large and growing database of photographs for ML training
• Brand identity of being industry disruptor
• Offices in 7 major cities
• ~800 employees with ~50 different nationalities

Processes

• Marketplace functions such as pricing, contracting and industry-specific photography instructions are all standardized
• Image enhancement process (editing)
• AI-Human quality assurance process
• Types and number of photographs to be taken per photoshoot standardized to be used for machine learning
• Narrative of benefits company produces is consistent across multiple years
• Sales system – process involves using different but standardized incentivization schemes for Business Development Representatives (BDRs), Key Account Managers (KAMs) to close deals, and Customer Success Managers (CSMs) to ensure customers don’t churn (incentives changed 12 times in 18 months)
• Photographer recruitment
• Cybersecurity procedures (had a major breach early that changed the way the company operates)
• Photographer workflow tools
• Brand ambassador meetups and other information gathering initiatives

Priorities

• Attain 5% market share of a $100B global market
• Expand its customer base in new geographies
• Build and improve proprietary photo editing and content enrichment technology
• Increase revenue from major brands
• Enter market for individual consumers
• Accelerate the development of dedicated services for photographers that increases their interaction with and reliance on the company
• Increase tech team from 80 to 300 members
• Focus all external messaging around company’s key talking points and their CEO Thomas Rebaud