Flipside AI scorecard

Last updated: 2026-08-26

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Company Overview

Flipside AI is a BPO company.

Executive summary

Brand Profile: Voice: professional. Voice: technical. Voice: quality-focused. Imagery Style: technical and AI-oriented branding centered on data labeling and machine learning use cases. Client Value Proposition: Summary: Flipside AI publicly positions its value around high-accuracy, secure, ethical, and quality-controlled outsourced data labeling and evaluation for advanced AI systems.. Value Points: Title: Quality control. Value Points: Description: The company emphasizes rigorously quality-controlled curation and high-accuracy labeling.. Value Points: Title: Security and ethics. Value Points: Description: Public copy describes secure and ethical data labeling and evaluation.. Value Points: Title: Human judgment in the loop. Value Points: Description: Offerings stress human-in-the-loop workflows for judgment, curation, and annotation.. Value Points: Title: Specialized AI readiness. Value Points: Description: The company targets datasets for AV, ADAS, robotics, LLMs, and embodied AI applications.. Company Overview: Tagline: Data labeling and AI data engineering for computer vision, perception, and generative AI use cases.. Highlights: Founded in 2010.. Highlights: Based in Quezon City, Philippines.. Highlights: Specializes in AI data labeling, annotation, and human judgment workflows.. Highlights: Publicly described as serving computer vision, ADAS, robotics, and LLM-related use cases.. Description: Flipside AI is the current brand name for Flipside Digital Content Company, Inc., a Philippines-based BPO that shifted from ebook production to outsourced AI data labeling and data engineering services. Public materials describe it as focused on structured data collection, annotation, labeling, human-in-the-loop judgment workflows, and quality-controlled curation pipelines for advanced AI systems.. Competitive Differentiators: Differentiators: Title: Long operating history. Differentiators: Description: Public materials state the company was founded in 2010 and evolved from ebook production into AI data labeling and

Strengths

  • Brand Profile: Voice: professional. Voice: technical. Voice: quality-focused. Imagery Style: technical and AI-oriented branding centered on data labeling and machine learning use cases. (public_web; observed 2026-08-20)
  • Client Portfolio: Industry Concentration: autonomous vehicles. Industry Concentration: advanced driver assistance systems. Industry Concentration: robotics. Industry Concentration: satellites. Industry Concentration: LLM-related use cases. (public_web; observed 2026-08-20)
  • Client Value Proposition: Summary: Flipside AI publicly positions its value around high-accuracy, secure, ethical, and quality-controlled outsourced data labeling and evaluation for advanced AI systems.. Value Points: Title: Quality control. Value Points: Description: The company emphasizes rigorously quality-controlled curation and high-accuracy labeling.. Value Points: Title: Security and ethics. Value Points: Description: Public copy describes secure and ethical data labeling and evaluation.. Value Points: Title: Human judgment in the loop. Value Points: Description: Offerings stress human-in-the-loop workflows for judgment,. (public_web; observed 2026-08-20)

Gaps

  • The reviewed public sources do not establish buyer-specific service levels, staffing commitments, or acceptance criteria for a defined scope. (public_web; observed 2026-08-26)
  • The reviewed public sources do not establish a buyer-specific continuity design, recovery objective, security schedule, or named delivery team. (public_web; observed 2026-08-20)
  • The reviewed public sources do not provide directly comparable commercial terms and independently verified outcomes for a like-for-like engagement. (public_web; observed 2026-08-20)

Firmographics

GB100 score

Overall score: 47

  • egs: 36
  • growth: 50
  • reputation: 45.5
  • ai_readiness: 50
  • market_footprint: 50
  • digital_readiness: 52.6

Scores are calculated from published evidence and the current GB100 methodology; payment does not affect rank.

Services and operating scope

Client Portfolio: Industry Concentration: autonomous vehicles. Industry Concentration: advanced driver assistance systems. Industry Concentration: robotics. Industry Concentration: satellites. Industry Concentration: LLM-related use cases. Competitive Landscape: Competitors: Name: Scale AI. Competitors: Evidence: Both provide AI data labeling and annotation services.. Competitors: Relationship: direct. Competitors: Name: Appen. Competitors: Evidence: Both compete in outsourced data annotation and AI training data services.. Competitors: Relationship: direct. Competitors: Name: Sama. Competitors: Evidence: Both offer human-in-the-loop data labeling and annotation services.. Competitors: Relationship: direct. Competitors: Name: Flipside Group. Competitors: Evidence: Shares the Flipside name but the public source describes AI development services rather than the same BPO entity.. Competitors: Relationship: adjacent. Positioning: Outsourced AI data labeling and evaluation provider with roots in digital content and publishing.. Market Signals: Public sources describe the company as a Philippines-based BPO specialized in outsourced AI data labeling.. Market Signals: A public non-binding acquisition LOI suggests strategic interest in the business.. Differentiators: Founding history in publishing and digitization before shifting to AI data labeling.. Differentiators: Public positioning emphasizes high-accuracy, secure, and ethical labeling.. Differentiators: Capability set includes. Employee & Client Sentiment: Sentiment Trend: unknown. Employee Satisfaction: unknown. Services & Offerings: Categories: Name: Vision data labeling. Categories: Services: 2D bounding boxes. Categories: Services: 3D bounding boxes. Categories: Services: semantic segmentation. Categories: Services: instance segmentation. Categories: Services: panoptic segmentation. Categories: Services: LiDAR annotation. Categories: Services: RADAR annotation. Categories: Services: sensor fusion annotation. Categories: Services: video annotation. Categories: Services: eye-tracking. Categories: Name: Language / generative AI. Categories: Services: Customer service chatbot support data. Categories: Services: Content generation support. Categories: Services: Sentiment analysis support. Categories: Services: Generative AI judgment workflows. Categories: Name: Data engineering. Categories: Services: Structured data collection. Categories: Services: Human-in-the-loop judgment workflows. Categories: Services:

Geography

Delivery Center Details: Centers: City: Quezon City. Centers: Model: office-based headquarters. Centers: Country: Philippines. Hiring & Workforce Signals: Open Positions: Title: STEM Prompt Engineer. Open Positions: Location: Remote. Open Positions: Seniority: unknown. Open Positions: Department: unknown. Open Positions: Title: AI Prompt Engineer. Open Positions: Location: Remote. Open Positions: Seniority: unknown. Open Positions: Department: unknown. Workforce Signals: Notes: Public LinkedIn post indicated remote full-time or part-time hiring for STEM Prompt Engineers and AI Prompt Engineers.. Workforce Signals: Remote Hiring: confirmed. Key Firmographics: Founded Year: 2010. Sectors Display: Computer vision. Sectors Display: Autonomous vehicles. Sectors Display: ADAS. Sectors Display: Robotics. Sectors Display: LLMs / generative AI. Sectors Display: Satellite data. Headquarters Display: Quezon City, Metro Manila, Philippines. Ownership Type Display: Publicly described as a BPO company; also described in 2026 materials as a wholly-owned subsidiary of Nexscient, Inc.. Tech Stack & Tools: Tools: Category: AI. Tools: Confidence: confirmed. Tools: Product Name: Large language models. Tools: Category: AI. Tools: Confidence: confirmed. Tools: Product Name: ChatGPT. Tools: Category: AI. Tools: Confidence: confirmed. Tools: Product Name: Google Gemini. Ai Capabilities: computer vision labeling. Ai Capabilities: perception data annotation. Ai Capabilities: video annotation. Ai Capabilities: LiDAR/RADAR point cloud annotation. Ai Capabilities: sensor fusion annotation. Ai Capabilities: semantic segmentation. Ai Capabilities: instance segmentation. Ai Capabilities: panoptic segmentation. Ai Capabilities: eye-tracking. Ai Capabilities: content generation. Ai Capabilities: sentiment analysis. Ai Capabilities: customer service chatbots. Financial Health: Risk Factors: Non-binding acquisition LOI introduces transaction uncertainty.. Risk Factors: No public financial statements or revenue figures were verified from the sources gathered.. Overall Health: unknown. Financial Events: Date: 2025-08-06. Financial Events:

Methodology

Flipside AI's BPOIndex scorecard is assembled from public, attributable evidence rather than vendor-submitted marketing claims or a paid-placement package. The research pass reviewed 18 distinct source URLs and retained 15 substantive facts or company sections with direct citations. Each retained observation is tied to the page where it was found and to the date on which that page was observed. Information that could not be traced to a reviewed public source was left out. This distinction matters because a provider's website may describe broad capabilities without publishing buyer-specific service levels, staffing commitments, commercial terms, delivery capacity, or independently comparable outcomes. Collection and publication are separate. Collection discovers public pages, records evidence, and builds structured sections for company background, services, delivery footprint, operating signals, and credentials. Publication includes only substantive observations carrying an HTTP citation. The strengths below identify areas where the provider has published inspectable information; they are not guarantees of quality, price, security, or fit. Evidence gaps are questions the reviewed sources did not answer at a buyer-specific level, not negative claims about the provider. Peer links are navigation aids from other canonical BPOIndex profiles, not a claim that every company is identical in size, geography, specialization, or commercial model. Buyers should compare the underlying service taxonomy, locations, evidence, and current score dimensions. Confirm scope-specific service levels, named delivery sites, staffing assumptions, security controls, continuity plans, pricing units, minimum commitments, and referenceable outcomes directly with the provider. The observed dates show when evidence was collected. Later enrichment can add newly published sources, but unsupported inference, duplicate shells, and generic filler do not qualify a page for indexing.

Read the full GB100 methodology

Coverage gaps

  • Insufficient public evidence for employee coverage.
  • Insufficient public evidence for headquarters coverage.
  • Insufficient public evidence for service taxonomy coverage.
  • Insufficient public evidence for industry taxonomy coverage.

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Contact

Website: https://www.flipsidecontent.com

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