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ML Data Preparation: The process of converting raw data into dataset of features and labels for training, testing and implementations of algorithm.

Foiwe manages all critical steps to provide high quality dataset for machine learning models to perform efficiently. We work on both dataset and data model to complement each other and to ensure the model performs to expectations.

Benefits of Data Preparation

Technology is evolving everyday and technocrats must  stay up to date with changing trends in Big Data and AI. Foiwe’s Data Preparation solutions helps in gaining edge at a fraction of the cost
End-to-end Preparation

Foiwe provides assistance in all steps involved in preparing unsorted data to train your neural engine for any project. Our experts work on your big data to convert it into a structured and quality driven data sheets.

Curated by Experts

Unstructured data are categorized keeping human sentiments and actions in mind -resulting in a natural learning. This in return generates accurate and close to real life scenarios resulting better AI application.

Safe and Secure Access

Every action in each step is logged and monitored religiously to provide the best possible data safety. Our compliance to various data protection guidelines such as GDPR ensure that your data is protected and have only authorized access.

Our Key Metrics

We are passionate about our work. Our analysts stay ahead of the curve to provide engaging and stable experience.

0 M
Items Moderated each day
40 K
Profiles Reviewed peach day
90 %
Average Accuracy
0 M
Live Streams each day
5 Y
of Experience
90 %

Tailor-made and scalable solution for all content moderation needs

Dedicated Account Manager available 24x7 as a Single Point of Contact

With your dedicated account manager, as single point of contact and accessible round the clock over phone or messenger, you get a personalized support and swift communication literally in real time. We aim at seamless problem-solving, enhancing overall satisfaction on our service delivery and partnership effectiveness through continuous communication across multiple channels.

Tailor-Made Solution Based on Your Specific Project Needs

Content moderation for an app demands a tailor-made solution aligned with your project's unique requirements. Our customized offerings ensure that the moderation process effectively aligns with your content types, user demographics and compliance mandates. We are your extended team working together towards user safety, platform integrity and user experience.

Real-Time Implementation of Updates and Guideline Changes

We understand that real-time implementation of moderation guideline changes in an app is crucial for maintaining user safety and adherence to evolving content standards. Swift updates prevent harmful or inappropriate content from slipping through the cracks, ensuring a responsive and adaptable moderation system that protects both users and the app's reputation.

Applications and Capabilities

Data Preparation also helps in machine learning, and in particular, it is helpful for large machine learning tasks, which in turn helps in providing better quality solutions to problems faced by users.


  • Processing Big Data
  • AI Systems
  • Ecommerce platforms


  • Cleaner and structured data stream
  • Capable to handle large data volumes
  • Multilingual team
  • Experienced Staffs for greater output

Speak with our subject matter experts

Data Preparation for Machine Learning

Importance of ML Data preparation 

Data Preparation is a supervised task in Machine Learning, as it requires inputs like feature maps, labels, input constraints, etc. The main work in Data Preparation is to construct and design a data type, which can be used in various algorithms like Data mining, Data classification, and Data cleansing. These data types are the critical building blocks of diverse Machine Learning Algorithms like principal component analysis, neural networks, supervised learning, artificial intelligence, decision trees, etc. Data can also be used in different stages of an algorithm, like training, pre-training, post-trained, and benchmarks.

Foiwe manages all critical steps to provide high quality dataset for machine learning models to perform efficiently. We work on both dataset and data model to complement each other and to ensure the model performs to expectations.

Related Services

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Case Studies and Reports

Image moderation is the process of assessing, filtering and managing images , to ensure they adhere to specific guidelines, policies or standards. Image Moderation helps to remove the content that is offensive, illegal or against the platform’s terms of service.

1.Nudity Detection: One of the most common types of image moderation is the detection of nudity or explicit content. Moderator check images for explicit body parts and flag or remove them accordingly to the online platform guideline.
2.Violence and Gore Detection: This type of image moderation, moderator identifies violent or gory images, preventing them from being shared on platforms that aim to maintain a non-violent environment.
3.Hate Speech and Offensive Content: Image moderation can identify hate speech, offensive symbols and content that promotes discrimination, ensuring it doesn’t gain traction online.
4.Copyright and Trademark Violations: In image moderation, moderator check for copyright and trademark violations, protecting intellectual property rights.
5.Drugs and Substance Abuse: Images containing drug-related content can be flagged and removed to maintain a safe and responsible online space.
6.Spam and Scams: Image moderation can help detect and filter out images associated with spam and scams. Also using image moderation moderator protect users from online fraudulent activities.
7.Brand Safety: It ensures that brands’ advertisements don’t appear next to inappropriate or controversial content, safeguarding their reputation.

1.User Safety: Image moderation protects users, especially children and vulnerable individuals, from exposure to harmful and explicit content.
2.Compliance with Regulations: Many countries have regulations in place that require online platforms to moderate and filter content. In image moderation also help to follow rule of that country.
3.Brand Reputation: For businesses and advertisers, image moderation is crucial to protect their brand reputation by ensuring their ads don’t appear alongside offensive or inappropriate content.
4.Community Guidelines: It helps maintain and enforce community guidelines on social media platforms and websites, fostering a respectful online environment.
5.Content Quality: Image Moderation ensures that platforms maintain a high standard of content quality, making them more attractive to users and advertisers.

While image moderation is essential, it is not without challenges. Some of these challenges include:
False Positives and Negatives: Overly strict algorithms can result in false positives, flagging innocent content, while overly lenient ones may miss offensive material.
Evolving Content: As content creators find new ways to evade moderation, systems must continually adapt to emerging trends and techniques.
Scalability: For platforms with massive user bases, moderating images at scale can be a significant technical challenge.

Here are some key aspects of moderation in media:
1.Content Screening: Moderators review and assess user-generated content, such as text, images, videos and comments, to determine whether it violates platform-specific rules or standards. This may include identifying and removing content that is offensive, illegal, spammy or otherwise inappropriate.
2.User Behavior Monitoring: Moderation extends beyond just content and may involve monitoring user behavior for violations. This can include identifying and taking action against users who engage in harassment, hate speech or other disruptive behaviors.
3.Enforcement of Policies: Moderators enforce community guidelines, terms of service, and content policies set by the media platform. They may issue warnings, temporary suspensions, or permanent bans to users who repeatedly violate these policies.
4.Filtering and Blocking: Automated tools and algorithms, in conjunction with human moderators, may be used to filter out or block certain keywords, phrases or types of content that are commonly associated with violations.
5.Reporting Mechanisms: Media platforms often provide users with the ability to report content or users that they find objectionable. Moderators review these reports and take appropriate actions.
6.Legal Compliance: In some cases, media moderation is necessary to ensure that content adheres to legal requirements, such as copyright laws, defamation laws or regulations related to hate speech and discrimination.
7.Protecting Minors: On platforms frequented by minors, moderation may be particularly focused on preventing the dissemination of harmful or age-inappropriate content.
8.User Engagement: Moderation can also play a role in fostering positive user engagement and community building by encouraging respectful and constructive interactions.
9.Crisis Management: In the event of a crisis or emergency, moderators may be responsible for disseminating accurate information, preventing the spread of misinformation and managing communication channels effectively.
10.Content Curation: Some media platforms employ content curators or editors who select and feature content to ensure it aligns with the platform’s objectives or editorial standards.


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