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AI를 활용한 맞춤 영양 시장 규모, 점유율 및 동향 분석 보고서 : 유형별, 용도별, 최종 용도별, 지역별, 부문 예측(2026-2033년)

AI In Personalized Nutrition Market Size, Share & Trends Analysis Report By Type (AI Nutrition Apps, Test-based Personalization), By Application (AI-Based Meal Planning & Recommendations), By End Use, By Region, And Segment Forecasts, 2026 - 2033
발행일: | 리서치사: Grand View Research | 페이지 정보: 영문 100 Pages | 배송안내 : 2-10일 (영업일 기준)

    
    
    




※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

AI를 활용한 맞춤 영양 시장 요약

세계의 AI를 활용한 맞춤 영양 시장 규모는 2025년 15억 4,000만 달러로 추정되며, 2033년까지 102억 1,000만 달러에 이를 것으로 예측됩니다.

또한 2026-2033년 연평균 복합 성장률(CAGR) 27.21%를 나타낼 것으로 예측됩니다. 생활습관병 및 만성질환 증가, AI, 데이터 분석 및 오믹스 통합 기술의 발전, 예방적 및 개인화된 건강 솔루션에 대한 소비자 수요 증가가 시장 성장의 주요 요인으로 작용하고 있습니다.

또한, 디지털 헬스 생태계의 확대와 기업 도입의 진전이 시장 환경을 강화하고 있습니다. 생활습관병과 만성질환 증가는 시장 성장을 견인하는 주요 요인입니다. 비만, 당뇨병, 심혈관 질환, 대사증후군 등의 질병은 부적절한 식습관 및 운동 부족과 밀접한 관련이 있습니다. 예를 들어, 국제당뇨병연맹(IDF)에 따르면 현재 약 5억 8,900만 명이 당뇨병을 앓고 있으며, 2050년에는 8억 5,300만 명에 달할 것으로 추산됩니다. 기존의 식생활 지침은 대사, 유전, 건강 상태의 개인차를 충분히 고려하지 못하는 경우가 많습니다. AI를 활용한 영양관리 플랫폼은 생체측정 데이터, 진료기록, 생활습관 정보를 분석하여 정밀한 식습관 개입을 가능하게 합니다. 이러한 기술을 통해 위험을 조기에 발견하고 맞춤 영양 권장 사항을 수립할 수 있습니다.

의료 시스템과 고용주들은 예방 의료 전략을 강화하기 위해 개인화된 영양 관리 도구를 도입하고 있습니다. 영양 기반 중재를 통한 장기적인 의료비 절감에 중점을 두면서 시장 채택이 더욱 가속화되고 있습니다. 예를 들어, 2025년 12월 Avid Health는 Healthnix와 제휴하여 텍사스 주 FQHC(연방 인증 커뮤니티 건강 센터) 및 1차 진료소를 위한 만성 질환 관리 프로그램을 강화했습니다. 환자들이 영양 교육 및 행동 기술을 보다 쉽게 이용할 수 있도록 했습니다. 이번 제휴는 임상 데이터, 원격 환자 모니터링(RPM), 사회경제적 요인(SDOH) 데이터를 통합하는 Avid의 MagSync 플랫폼을 활용합니다. 여기에 헬스닉스의 의료영양치료 도구, 개인별 맞춤 영양사 조언, 장-뇌-통증 연관성에 대한 교육 커리큘럼을 통합하고 있습니다.

또한, 저렴한 가격의 웨어러블 기기 및 가정용 검사 키트가 보급되면서 건강 데이터에 대한 접근성이 확대되고 있습니다. 이를 통해 인공지능 모델은 종단적 데이터 세트를 활용하여 고도로 개인화된 추천을 생성할 수 있게 되었습니다. 예를 들어, 2025년 5월, OURA는 자사 링에 'Meals'와 'Glucose' 기능을 도입했습니다. 이는 AI 기반 식사 사진 분석을 Dexcom의 FDA 승인 OTC 혈당 바이오센서 'Stelo'와 OURA 앱 내에 통합한 것입니다. 'Meals' 기능에서는 비판적이지 않은 형태로 주요 영양소 분석, 단백질 및 식이섬유에 대한 지식, 지속 가능한 습관 형성을 위한 OURA 어드바이저의 가이드를 제공합니다.

"개인화된 안내와 인사이트은 생활습관 선택이 신체에 미치는 영향을 이해하고 삶의 질을 향상시킬 수 있는 정보에 기반한 건강 결정을 내리는 데 필수적입니다. OURA와의 협력을 통해 우리는 시장 최초로 혈당 바이오 센서와 스마트 링을 통합하여 활동량, 수면, 스트레스, 영양 및 혈당과의 연관성을 더 깊이 이해할 수 있는 유일무이한 개인화된 대사 건강 경험을 제공합니다. 이번 제휴를 통해 우리는 다시 한번 웨어러블 기술 분야의 개념을 혁신하고, 사람들이 스스로 건강을 관리할 수 있도록 돕는 것을 추구할 것입니다. "

덱스컴 부사장 겸 최고운영책임자(COO) 제이크 리치(Jake Leach)

또한, 대변 샘플의 마이크로바이옴 분석은 개인화된 프리바이오틱스 개입을 지원하며, 디지털 플랫폼은 이러한 권장 사항을 매주 업데이트합니다. 따라서 이러한 기술은 실시간 생리적, 행동적 변화에 적응하는 동적 영양 추천을 가능하게 하여 시장의 성장을 가속할 수 있습니다.

자주 묻는 질문

  • AI를 활용한 맞춤 영양 시장 규모는 어떻게 예측되나요?
  • AI를 활용한 맞춤 영양 시장의 성장 요인은 무엇인가요?
  • AI 기반 영양 관리 플랫폼의 기능은 무엇인가요?
  • 개인화된 영양 관리 도구의 도입이 의료 시스템에 미치는 영향은 무엇인가요?
  • 웨어러블 기기와 가정용 검사 키트의 보급이 시장에 미치는 영향은 무엇인가요?
  • AI를 활용한 맞춤 영양 시장의 경쟁 구도는 어떻게 되나요?

목차

제1장 조사 방법과 범위

제2장 주요 요약

제3장 AI를 활용한 맞춤 영양 시장 변수, 동향, 범위

제4장 AI를 활용한 맞춤 영양 시장 : 유형별 추정 및 동향 분석

제5장 AI를 활용한 맞춤 영양 시장 : 용도별 추정 및 동향 분석

제6장 맞춤 영양 시장 AI : 최종 용도별 추정 및 동향 분석

제7장 맞춤 영양 시장 AI : 지역별 추정 및 동향 분석

제8장 경쟁 구도

LSH 26.03.11

AI In Personalized Nutrition Market Summary

The global AI in personalized nutrition market size was estimated at USD 1.54 billion in 2025 and is projected to reach USD 10.21 billion by 2033, growing at a CAGR of 27.21% from 2026 to 2033. Rising prevalence of lifestyle-related and chronic diseases, advances in AI, data analytics, and omics integration, and growing consumer demand for preventive and personalized health solutions are significant factors contributing to market growth.

Moreover, the expansion of digital health ecosystems and enterprise adoption is strengthening the market environment. The increasing prevalence of lifestyle-related and chronic diseases is a key factor driving market growth. Diseases such as obesity, diabetes, cardiovascular disorders, and metabolic syndrome are closely associated with poor dietary habits and sedentary behavior. For instance, according to the International Diabetes Federation (IDF), approximately 589 million people are currently living with diabetes, with an estimated number to reach 853 million by 2050. Conventional dietary guidelines frequently fail to account for individual differences in metabolism, genetics, and health status. AI-powered nutrition platforms facilitate precise dietary interventions by analyzing biometric data, clinical records, and lifestyle information. These technologies enable early risk identification and the development of targeted nutritional recommendations.

Healthcare systems and employers are adopting personalized nutrition tools to enhance preventive care strategies. The emphasis on reducing long-term healthcare costs through nutrition-based interventions is further accelerating market adoption. For instance, in December 2025, Avid Health partnered with Healthnix to strengthen chronic care programs for FQHCs and primary-care practices in Texas by making nutrition education and behavioral skills more accessible to patients. The partnership leverages Aivid's MagSync platform, which aggregates clinical, RPM, and SDOH data, and integrates Healthnix's Medical Nutrition Therapy tools, personalized dietitian advice, and curricula on gut-brain-pain connections.

Furthermore, the increasing availability of affordable wearable devices and at-home testing kits has expanded access to health data, supplying artificial intelligence models with longitudinal datasets for generating highly personalized recommendations. For instance, in May 2025, OURA launched Meals and Glucose features in its ring, integrating AI-driven meal photo analysis with Stelo by Dexcom's FDA-cleared OTC glucose biosensor in the Oura App. Meals provides non-judgmental macronutrient breakdowns, protein/fiber insights, and Oura Advisor guidance for sustainable habits.

"Personalized guidance and insights are essential for helping people understand how their lifestyle choices affect their body, while also encouraging them to make informed health decisions that can improve their overall quality of life. By integrating with OURA, we're bringing the first glucose biosensor and smart ring integration to the market, providing a one-of-a-kind and personalized metabolic health experience that allows users to better understand the link between activity, sleep, stress, nutrition, and their glucose. Through this partnership, we're once again redefining the wearable technology category in the pursuit of empowering people to take control of their health."

Jake Leach, executive vice president and chief operating officer at Dexcom.

Moreover, microbiome analysis of stool samples supports individualized prebiotic interventions, while digital platforms update these recommendations weekly. Thus, such technologies enable dynamic nutrition recommendations that adapt to real-time physiological and behavioral changes, thereby further driving market growth.

Global AI In Personalized Nutrition Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI in personalized nutrition market report based on type, application, end use, and region:

  • Type Outlook (Revenue, USD Million, 2021 - 2033)
  • AI Nutrition Apps
  • Test-based personalization (DNA / Microbiome / Blood)
  • Device-linked metabolic platforms
  • Enterprise / Clinical platforms
  • Application Outlook (Revenue, USD Million, 2021 - 2033)
  • AI-Based Meal Planning & Recommendations
  • Nutrient & Micronutrient Analysis
  • Personalized Supplement Recommendations
  • Allergen & Food Sensitivity Identification
  • Health & Metabolic Monitoring
  • Others
  • End Use Outlook (Revenue, USD Million, 2021 - 2033)
  • Individuals / Consumers
  • Fitness & Wellness Organizations
  • Healthcare Providers
  • Employers & Enterprises
  • Others
  • Regional Outlook (Revenue, USD Million, 2021 - 2033)
  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
    • Denmark
    • Sweden
    • Norway
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Thailand
  • Latin America
    • Brazil
    • Argentina
  • MEA
    • South Africa
    • Saudi Arabia
    • UAE
    • Kuwait

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definitions
    • 1.2.1. Type Segment
    • 1.2.2. Application Segment
    • 1.2.3. End Use
  • 1.3. Information analysis
    • 1.3.1. Market formulation & data visualization
  • 1.4. Data validation & publishing
  • 1.5. Information Procurement
    • 1.5.1. Primary Research
  • 1.6. Information or Data Analysis
  • 1.7. Market Formulation & Validation
  • 1.8. Market Model
  • 1.9. Total Market: CAGR Calculation
  • 1.10. Objectives
    • 1.10.1. Objective 1
    • 1.10.2. Objective 2

Chapter 2. Executive Summary

  • 2.1. Market Outlook
  • 2.2. Segment Snapshot
  • 2.3. Competitive Insights Landscape

Chapter 3. AI in Personalized Nutrition Market Variables, Trends & Scope

  • 3.1. Market Lineage Outlook
    • 3.1.1. Parent market outlook
    • 3.1.2. Related/ancillary market outlook.
  • 3.2. Market Dynamics
    • 3.2.1. Market driver analysis
    • 3.2.2. Market restraint analysis
    • 3.2.3. Market opportunity analysis
    • 3.2.4. Market challenges analysis
  • 3.3. AI in Personalized Nutrition Market Analysis Tools
    • 3.3.1. Industry Analysis - Porter's
      • 3.3.1.1. Supplier power
      • 3.3.1.2. Buyer power
      • 3.3.1.3. Substitution threat
      • 3.3.1.4. Threat of new entrant
      • 3.3.1.5. Competitive rivalry
    • 3.3.2. PESTEL Analysis
      • 3.3.2.1. Political landscape
      • 3.3.2.2. Technological landscape
      • 3.3.2.3. Economic landscape
      • 3.3.2.4. Environmental Landscape
      • 3.3.2.5. Legal Landscape
      • 3.3.2.6. Social Landscape

Chapter 4. AI in Personalized Nutrition Market: Type Estimates & Trend Analysis

  • 4.1. Segment Dashboard
  • 4.2. Global AI in Personalized Nutrition Market Type Movement Analysis
  • 4.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by Type, 2021 to 2033 (USD Million)
  • 4.4. AI Nutrition Apps
    • 4.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 4.5. Test-based personalization (DNA / Microbiome / Blood)
    • 4.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 4.6. Device-linked metabolic platforms
    • 4.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 4.7. Enterprise / Clinical Platforms
    • 4.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)

Chapter 5. AI in Personalized Nutrition Market: Application Estimates & Trend Analysis

  • 5.1. Segment Dashboard
  • 5.2. Global AI in Personalized Nutrition Market Application Movement Analysis
  • 5.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by Application, 2021 to 2033 (USD Million)
  • 5.4. AI-Based Meal Planning & Recommendations
    • 5.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 5.5. Nutrient & Micronutrient Analysis
    • 5.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 5.6. Personalized Supplement Recommendations
    • 5.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 5.7. Allergen & Food Sensitivity Identification
    • 5.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 5.8. Health & Metabolic Monitoring
    • 5.8.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 5.9. Others
    • 5.9.1. Market estimates and forecasts, 2021 - 2033 (USD Million)

Chapter 6. AI in Personalized Nutrition Market: End Use Estimates & Trend Analysis

  • 6.1. Segment Dashboard
  • 6.2. Global AI in Personalized Nutrition Market End Use Movement Analysis
  • 6.3. Global AI in Personalized Nutrition Market Size & Trend Analysis, by End Use, 2021 to 2033 (USD Million)
  • 6.4. Individuals / Consumers
    • 6.4.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 6.5. Fitness & Wellness Organizations
    • 6.5.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 6.6. Healthcare Providers
    • 6.6.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 6.7. Employers & Enterprises
    • 6.7.1. Market estimates and forecasts, 2021 - 2033 (USD Million)
  • 6.8. Others
    • 6.8.1. Market estimates and forecasts, 2021 - 2033 (USD Million)

Chapter 7. AI in Personalized Nutrition Market: Regional Estimates & Trend Analysis

  • 7.1. Regional Market Share Analysis, 2025 & 2033
  • 7.2. Regional Market Dashboard
  • 7.3. Market Size & Forecasts Trend Analysis, 2021 to 2033:
  • 7.4. North America
    • 7.4.1. U.S.
      • 7.4.1.1. Key country dynamics
      • 7.4.1.2. Regulatory framework
      • 7.4.1.3. Competitive scenario
      • 7.4.1.4. U.S. market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.4.2. Canada
      • 7.4.2.1. Key country dynamics
      • 7.4.2.2. Regulatory framework
      • 7.4.2.3. Competitive scenario
      • 7.4.2.4. Canada market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.4.3. Mexico
      • 7.4.3.1. Key country dynamics
      • 7.4.3.2. Regulatory framework
      • 7.4.3.3. Competitive scenario
      • 7.4.3.4. Mexico market estimates and forecasts, 2021 - 2033 (USD Million)
  • 7.5. Europe
    • 7.5.1. UK
      • 7.5.1.1. Key country dynamics
      • 7.5.1.2. Regulatory framework
      • 7.5.1.3. Competitive scenario
      • 7.5.1.4. UK market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.2. Germany
      • 7.5.2.1. Key country dynamics
      • 7.5.2.2. Regulatory framework
      • 7.5.2.3. Competitive scenario
      • 7.5.2.4. Germany market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.3. France
      • 7.5.3.1. Key country dynamics
      • 7.5.3.2. Regulatory framework
      • 7.5.3.3. Competitive scenario
      • 7.5.3.4. France market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.4. Italy
      • 7.5.4.1. Key country dynamics
      • 7.5.4.2. Regulatory framework
      • 7.5.4.3. Competitive scenario
      • 7.5.4.4. Italy market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.5. Spain
      • 7.5.5.1. Key country dynamics
      • 7.5.5.2. Regulatory framework
      • 7.5.5.3. Competitive scenario
      • 7.5.5.4. Spain market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.6. Norway
      • 7.5.6.1. Key country dynamics
      • 7.5.6.2. Regulatory framework
      • 7.5.6.3. Competitive scenario
      • 7.5.6.4. Norway market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.7. Sweden
      • 7.5.7.1. Key country dynamics
      • 7.5.7.2. Regulatory framework
      • 7.5.7.3. Competitive scenario
      • 7.5.7.4. Sweden market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.5.8. Denmark
      • 7.5.8.1. Key country dynamics
      • 7.5.8.2. Regulatory framework
      • 7.5.8.3. Competitive scenario
      • 7.5.8.4. Denmark market estimates and forecasts, 2021 - 2033 (USD Million)
  • 7.6. Asia Pacific
    • 7.6.1. Japan
      • 7.6.1.1. Key country dynamics
      • 7.6.1.2. Regulatory framework
      • 7.6.1.3. Competitive scenario
      • 7.6.1.4. Japan market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.6.2. China
      • 7.6.2.1. Key country dynamics
      • 7.6.2.2. Regulatory framework
      • 7.6.2.3. Competitive scenario
      • 7.6.2.4. China market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.6.3. India
      • 7.6.3.1. Key country dynamics
      • 7.6.3.2. Regulatory framework
      • 7.6.3.3. Competitive scenario
      • 7.6.3.4. India market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.6.4. Australia
      • 7.6.4.1. Key country dynamics
      • 7.6.4.2. Regulatory framework
      • 7.6.4.3. Competitive scenario
      • 7.6.4.4. Australia market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.6.5. South Korea
      • 7.6.5.1. Key country dynamics
      • 7.6.5.2. Regulatory framework
      • 7.6.5.3. Competitive scenario
      • 7.6.5.4. South Korea market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.6.6. Thailand
      • 7.6.6.1. Key country dynamics
      • 7.6.6.2. Regulatory framework
      • 7.6.6.3. Competitive scenario
      • 7.6.6.4. Thailand market estimates and forecasts, 2021 - 2033 (USD Million)
  • 7.7. Latin America
    • 7.7.1. Brazil
      • 7.7.1.1. Key country dynamics
      • 7.7.1.2. Regulatory framework
      • 7.7.1.3. Competitive scenario
      • 7.7.1.4. Brazil market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.7.2. Argentina
      • 7.7.2.1. Key country dynamics
      • 7.7.2.2. Regulatory framework
      • 7.7.2.3. Competitive scenario
      • 7.7.2.4. Argentina market estimates and forecasts, 2021 - 2033 (USD Million)
  • 7.8. MEA
    • 7.8.1. South Africa
      • 7.8.1.1. Key country dynamics
      • 7.8.1.2. Regulatory framework
      • 7.8.1.3. Competitive scenario
      • 7.8.1.4. South Africa market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.8.2. Saudi Arabia
      • 7.8.2.1. Key country dynamics
      • 7.8.2.2. Regulatory framework
      • 7.8.2.3. Competitive scenario
      • 7.8.2.4. Saudi Arabia market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.8.3. UAE
      • 7.8.3.1. Key country dynamics
      • 7.8.3.2. Regulatory framework
      • 7.8.3.3. Competitive scenario
      • 7.8.3.4. UAE market estimates and forecasts, 2021 - 2033 (USD Million)
    • 7.8.4. Kuwait
      • 7.8.4.1. Key country dynamics
      • 7.8.4.2. Regulatory framework
      • 7.8.4.3. Competitive scenario
      • 7.8.4.4. Kuwait market estimates and forecasts, 2021 - 2033 (USD Million)

Chapter 8. Competitive Landscape

  • 8.1. Company/Competition Categorization
  • 8.2. Strategy Mapping
  • 8.3. Company Market Position Analysis, 2025
  • 8.4. Company Profiles/Listing
    • 8.4.1. Appinventiv
      • 8.4.1.1. Company overview
      • 8.4.1.2. Financial performance
      • 8.4.1.3. Product benchmarking
      • 8.4.1.4. Strategic initiatives
    • 8.4.2. BetterMeal Al
      • 8.4.2.1. Company overview
      • 8.4.2.2. Financial performance
      • 8.4.2.3. Product benchmarking
      • 8.4.2.4. Strategic initiatives
    • 8.4.3. BiteAI
      • 8.4.3.1. Company overview
      • 8.4.3.2. Financial performance
      • 8.4.3.3. Product benchmarking
      • 8.4.3.4. Strategic initiatives
    • 8.4.4. Culina Health
      • 8.4.4.1. Company overview
      • 8.4.4.2. Financial performance
      • 8.4.4.3. Product benchmarking
      • 8.4.4.4. Strategic initiatives
    • 8.4.5. DayTwo
      • 8.4.5.1. Company overview
      • 8.4.5.2. Financial performance
      • 8.4.5.3. Product benchmarking
      • 8.4.5.4. Strategic initiatives
    • 8.4.6. EatLove
      • 8.4.6.1. Company overview
      • 8.4.6.2. Financial performance
      • 8.4.6.3. Product benchmarking
      • 8.4.6.4. Strategic initiatives
    • 8.4.7. EIT Food
      • 8.4.7.1. Company overview
      • 8.4.7.2. Financial performance
      • 8.4.7.3. Product benchmarking
      • 8.4.7.4. Strategic initiatives
    • 8.4.8. Habit
      • 8.4.8.1. Company overview
      • 8.4.8.2. Financial performance
      • 8.4.8.3. Product benchmarking
      • 8.4.8.4. Strategic initiatives
    • 8.4.9. InsideTracker
      • 8.4.9.1. Company overview
      • 8.4.9.2. Financial performance
      • 8.4.9.3. Product benchmarking
      • 8.4.9.4. Strategic initiatives
    • 8.4.10. January AI
      • 8.4.10.1. Company overview
      • 8.4.10.2. Financial performance
      • 8.4.10.3. Product benchmarking
      • 8.4.10.4. Strategic initiatives
    • 8.4.11. LemonBox
      • 8.4.11.1. Company overview
      • 8.4.11.2. Financial performance
      • 8.4.11.3. Product benchmarking
      • 8.4.11.4. Strategic initiatives
    • 8.4.12. Nourished
      • 8.4.12.1. Company overview
      • 8.4.12.2. Financial performance
      • 8.4.12.3. Product benchmarking
      • 8.4.12.4. Strategic initiatives
    • 8.4.13. Nutrigenomix Inc.
      • 8.4.13.1. Company overview
      • 8.4.13.2. Financial performance
      • 8.4.13.3. Product benchmarking
      • 8.4.13.4. Strategic initiatives
    • 8.4.14. Nutrify LLC
      • 8.4.14.1. Company overview
      • 8.4.14.2. Financial performance
      • 8.4.14.3. Product benchmarking
      • 8.4.14.4. Strategic initiatives
    • 8.4.15. Nutrino Health Ltd.
      • 8.4.15.1. Company overview
      • 8.4.15.2. Financial performance
      • 8.4.15.3. Product benchmarking
      • 8.4.15.4. Strategic initiatives
    • 8.4.16. Persona Nutrition
      • 8.4.16.1. Company overview
      • 8.4.16.2. Financial performance
      • 8.4.16.3. Product benchmarking
      • 8.4.16.4. Strategic initiatives
    • 8.4.17. Spur Fit
      • 8.4.17.1. Company overview
      • 8.4.17.2. Financial performance
      • 8.4.17.3. Product benchmarking
      • 8.4.17.4. Strategic initiatives
    • 8.4.18. Viome Inc.
      • 8.4.18.1. Company overview
      • 8.4.18.2. Financial performance
      • 8.4.18.3. Product benchmarking
      • 8.4.18.4. Strategic initiatives
    • 8.4.19. Suggestic Inc.
      • 8.4.19.1. Company overview
      • 8.4.19.2. Financial performance
      • 8.4.19.3. Product benchmarking
      • 8.4.19.4. Strategic initiatives
    • 8.4.20. Zoe Ltd.
      • 8.4.20.1. Company overview
      • 8.4.20.2. Financial performance
      • 8.4.20.3. Product benchmarking
      • 8.4.20.4. Strategic initiatives
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