Bring intelligence to your enterprise processes. Whether you have existing generative AI models or want to integrate them into your operations, we offer a comprehensive suite of services to unlock their full potential.

Code Review

Our expert engineers conduct quality checks on code output to ensure it is well-structured, efficient, and error-free. We actively suggest improvements and generate alternative implementations for optimized outcomes. This step is crucial in enhancing the AI model’s performance.

Image/Video Models

Generative AI models can create high-quality images, videos, and avatars. These models use advanced algorithms to generate realistic and customizable content that is revolutionizing the way we use and consume visual media. Enriching and quality checking outputs is critical for precise training.

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Captioning and Metadata

Our skilled and experienced annotators use precise and accurate visual captioning techniques including metadata descriptions to train models for more realistic and comprehensive results.

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NSFW Content

NSFW content moderation and data annotation services to help companies dealing with user-driven AI-generated content. This ensures a safe user experience by identifying and removing inappropriate or offensive content, and by labeling and categorizing data for AI models to recognize patterns and accurately predict outcomes.

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Caption Classification

Caption classification services provide training data with accurate and relevant captions, allowing teams to improve the quality, inclusivity, and interpretability of their model’s generated content, leading to more effective and impactful generative AI applications.
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Caption Ranking

Human-generated image, video, and avatar caption ranking and ordering. This process sorts captions from best to worst, identifies the most accurate and relevant annotations or provides new options to improve the quality of your model’s training data.

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Watermark identification service removes watermarks from images, videos, and avatar data used for AI model training to prevent interference and ensure accuracy. Our advanced algorithms and human expertise are utilized to locate and detect watermarks, and the results are fed back into model training data.

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Blurry/Illegible Image and Character Classification

Innodata offers services for classifying blurry/illegible images, which are often a problem in training generative AI models. Our service uses human annotators and advanced image processing to classify images and text based on quality. This can also be useful for OCR use cases analyzing unstructured data within images, ensuring accurate and reliable training data for AI models.

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Large Language Models

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Training data services for summarization in LLM generative AI models. Our subject matter experts provide accurate and reliable domain-specific summaries. Quality control measures are in place to ensure the data sets meet specific requirements and can scale to large data sets.
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NSFW Content

Identify and eliminate inappropriate content, ensuring a safe and positive user experience. Innodata also aids in labeling large datasets for AI models and identifying explicit content features that violate community guidelines.
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Quality Assurance and Output Grading/Evaluation

Innodata offers quality assurance and output grading services for large language models. Our team tests and checks for errors and inconsistencies to ensure the accuracy and reliability of the generated content. Innodata’s high-quality output grading involves assessing outputs based on various criteria and providing feedback to improve the quality of your models.
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LLMs can generate nonsensical language. Innodata tackles this by reducing hallucinations in models, using techniques like regularization, pruning, and RLHF. Our services optimize performance, encourage realistic language, and train models to avoid incorrect language.

Ethical Data Collection

Our processes adhere to rules of privacy, autonomy, and dignity, ensuring accurate and unbiased data, and protecting data privacy and security. We are the experts in sourcing and generating speech, audio, image, video, text, and document data to meet any industry domain need, helping to develop and deploy responsible AI and generative systems in an ethical manner.

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Workshops & Fine Tuning

Visioning Workshops

A tried and tested methodology that helps companies understand the value and capabilities of implementing generative AI into their own organizations. Our team will assess your organization’s current state and identify the areas where ChatGPT, Bard, Claude or any generative AI model could improve business outcomes. Innodata can also help to bring together key stakeholders from different departments within the organization to build consensus around the goals and objectives of implementing generative AI.

Domain Adaptation

Innodata can assist in adapting your existing generative AI models and processes to perform well in a new domain, or in a specific context or application, by reusing or fine-tuning the model’s parameters. Customize and fine-tune your models, prepare and create new or augmented high-quality training data, and provide continuous improvement and optimization in your generative AI initiatives.

Process Management

Our experts analyze your company’s existing processes, identify areas where generative AI could be used to improve efficiency, reduce costs, and enhance outcomes. Our process-first approach involves a thorough assessment of the potential benefits of incorporating generative AI, like models from OpenAI, Google, Midjourney, and more. We then collaborate with your team to plan the design and implementation solution that integrates with your existing processes.

Model Deployment

Once a generative AI model has been developed, it needs to be deployed to production in order to start generating results. This process can be complex and requires careful planning and execution to ensure that the model performs accurately and reliably in a production environment. Infrastructure setup, deployment strategy, testing and validation, monitoring, and maintenance help ensure that your generative AI models are deployed effectively, successfully, and perform reliably over time.

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Red Teaming

As generative AI is increasingly used in real-world applications, the risk of vulnerabilities, misuse, compromised data, and model security rises. Our teams of specialists conduct red-teaming, jailbreaking, and ethical hacking tests to help mitigate risks and identifying vulnerabilities. Rely on the experts to identify a model’s susceptibilities to attacks and ensure that appropriate measures are in place to safeguard against potential threats.

Authoring & Domain

With 4,000+ in-house SMEs spanning all industries, Innodata offers subject matter expert content authoring, technical writing and rewriting, PII redactions, grammatical and syntactical editing, and summarization in over 40+ languages. By leveraging the expertise and capabilities of Innodata’s SMEs, organizations can ensure their generative AI models are trained on leading domain-specific data, enabling them to accurately generate first-class outputs across multiple languages and industries.

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How We Are Helping Our Customers
Implement Generative AI

(NASDAQ: INOD) Innodata is a global data engineering company delivering the promise of AI to many of the world’s most prestigious companies. We provide AI-enabled software platforms and managed services for AI data collection/annotation, AI digital transformation, and industry-specific business processes. Our low-code Innodata AI technology platform is at the core of our offerings. In every relationship, we honor our 30+ year legacy delivering the highest quality data and outstanding service to our customers.


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