(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.
Generative AI
Data Solutions
Trusted Data Solutions for Powerful
Generative AI Model Development
Trusted Data Solutions for Powerful Generative AI Model Development
Fuel Advanced AI/ML Model Development With
Data Solutions for Generative AI
High-quality data solutions for developing industry-leading generative AI models, including diverse golden datasets, fine-tuning data, human preference optimization, red teaming, model safety, and evaluation.
Fuel Advanced AI/ML
Model Development With
Data Solutions for Generative AI
High-quality data solutions for developing industry-leading generative AI models, including diverse golden datasets, fine-tuning data, human preference optimization, red teaming, model safety, and evaluation.
Data Collection & Creation
Curate or generate a wide range of high-quality datasets across data types and demographic categories in over 85 native languages.
Our global teams rapidly collect or create realistic and diverse training datasets tailored to your unique use case requirements to enrich the training of generative AI models.
Additionally, develop LLM prompts with high-quality prompt engineering, allowing in-house experts to design and create prompt data that guide models in generating precise outputs.
Our global teams rapidly collect or create realistic and diverse training datasets tailored to your unique use case requirements to enrich the training of generative AI models.
Additionally, develop LLM prompts with high-quality prompt engineering, allowing in-house experts to design and create prompt data that guide models in generating precise outputs.
Supervised Fine-Tuning
Develop data to train and refine both existing and pre-trained models for task taxonomies. Create large scale training datasets and golden datasets for supervised fine-tuning.
Linguists, taxonomists, and subject matter experts across 85+ languages of native speakers create datasets ranging from simple to highly complex for fine-tuning across an extensive range of task categories and sub-tasks (90+ and growing).
Linguists, taxonomists, and subject matter experts across 85+ languages of native speakers create datasets ranging from simple to highly complex for fine-tuning across an extensive range of task categories and sub-tasks (90+ and growing).
Human Preference Optimization
Rely on human experts-in-the-loop to close the divide between model capabilities and human preferences.
Improve hallucinations and edge-cases with ongoing feedback to achieve optimal model performance through methods like RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Policy Optimization).
Improve hallucinations and edge-cases with ongoing feedback to achieve optimal model performance through methods like RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Policy Optimization).
Model Safety, Evaluation, & Red Teaming
Ensure the reliability, performance, and compliance of your generative AI models. Assess model performance using task-specific metrics to gauge accuracy and identify potential improvements, then allowing for improved accuracy with new data.
Address vulnerabilities with Innodata’s red teaming experts. Rigorously test and optimize generative AI models to ensure safety and compliance, exposing model weaknesses and improving responses to real-world threats.
Address vulnerabilities with Innodata’s red teaming experts. Rigorously test and optimize generative AI models to ensure safety and compliance, exposing model weaknesses and improving responses to real-world threats.
Data Collection & Creation
Supervised Fine-Tuning
Human Preference Optimization
Model Safety, Evaluation, & Red Teaming
Data Collection & Creation
Data Collection & Creation
Naturally curate or synthetically generate a wide range of high-quality datasets across data types and demographic categories in over 85 native languages.
Our global teams rapidly collect or create realistic and diverse training datasets tailored to your unique use case requirements to enrich the training of generative AI models.
Additionally, develop LLM prompts with high-quality prompt engineering, allowing in-house experts to design and create prompt data that guide models in generating precise outputs.
0
%
of respondents in a recent survey said their organization adopted AI-generated synthetic data because of challenges with real-world data accessibility.*
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Data Types:Image, video, sensor (LiDAR), audio, speech, document, and code.
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Demographic Diversity:Age, gender identity, region, ethnicity, occupation, sexual orientation, religion, cultural background, 85+ languages and dialects, and more.
Supervised Fine-Tuning
Supervised Fine-Tuning
Develop data to train and refine both existing and pre-trained models for
task taxonomies. Create large scale training datasets and golden datasets
for supervised fine-tuning.
Linguists, taxonomists, and subject matter experts across 85+ languages of native speakers create datasets ranging from simple to highly complex for fine-tuning across an extensive range of task categories and sub-tasks (90+ and growing).
Linguists, taxonomists, and subject matter experts across 85+ languages of native speakers create datasets ranging from simple to highly complex for fine-tuning across an extensive range of task categories and sub-tasks (90+ and growing).
0
%
of respondents in a recent survey said fine-tuning an LLM successfully was too complex, or they didn’t know how to do it on their own.*
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Sample Task Taxonomies:Summarization, image evaluation, image reasoning, Q&A, question understanding, entity relation classification, text-to-code, logic and semantics, question rewriting, translation…
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SFT Techniques:Change-of-thought, in context learning, data augmentation, dialogue…
Human Preference Optimization
Human Preference Optimization
Rely on human experts-in-the-loop to close the divide between model capabilities and human preferences. Improve hallucinations and edge-cases with ongoing feedback to achieve optimal model performance through methods like RLHF (Reinforcement Learning from Human Feedback) and DPO (Direct Policy Optimization).
0
%
of respondents in a recent survey said RLHF was the technique they were most interested in using for LLM customization.*
-
Example Feedback Types:DPO (Direct Policy Optimization), Simple RLHF (Reinforcement Learning from Human Feedback), Complex RLHF (Reinforcement Learning from Human Feedback), Nominal Feedback.
Model Safety, Evaluation, & Red Teaming
Model Safety, Evaluation, & Red Teaming
Ensure the reliability, performance, and compliance of your generative
AI models. Assess model performance using task-specific metrics to
gauge accuracy and identify potential improvements, then allowing for
improved accuracy with new data.
Address vulnerabilities with Innodata’s red teaming experts. Rigorously test and optimize generative AI models to ensure safety and compliance, exposing model weaknesses and improving responses to real-world threats.
Address vulnerabilities with Innodata’s red teaming experts. Rigorously test and optimize generative AI models to ensure safety and compliance, exposing model weaknesses and improving responses to real-world threats.
0
%
reduction in the violation rate of an LLM was seen in a recent study on adversarial prompt benchmarks after 4 rounds of red teaming.*
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Techniques:Payload smuggling, prompt injection, persuasion and manipulation, conversational coercion, hypotheticals, roleplaying, one-/few-shot learning, and more…
Why Choose Innodata for Your
Generative AI Data Solutions?
Global Delivery Centers &
Language Capabilities
Innodata operates global delivery centers proficient in over 85 native languages and dialects, ensuring comprehensive language coverage for your projects.
Quick Turnaround at Scale with
Quality Results
Our globally distributed teams guarantee swift delivery of high-quality results 24/7, leveraging industry-leading data quality practices across projects of any size and complexity, regardless of time zones.
Domain Expertise Across
Industries
With 4,000+ in-house SMEs covering all major domains from healthcare to finance to legal, Innodata offers expert annotation, collection, fine-tuning, and more.
Linguist & Taxonomy Specialists
Our in-house linguists and create custom taxonomies and guidelines tailored to generative AI model development.
Customized Tooling
Benefit from our proprietary tooling, including our Annotation Platform, designed to streamline team workflows and enhance efficiency in data annotation and management processes.
Why Choose Innodata for Your
Generative AI Data Solutions?
Global Delivery Centers &
Language Capabilities
Innodata operates global delivery centers proficient in over 85 native languages and dialects, ensuring comprehensive language coverage for your projects.
Quick Turnaround at Scale with
Quality Results
Our globally distributed teams guarantee swift delivery of high-quality results 24/7, leveraging industry-leading data quality practices across projects of any size and complexity, regardless of time zones.
Domain Expertise Across
Industries
With 4,000+ in-house SMEs covering all major domains from healthcare to finance to legal, Innodata offers expert annotation, collection, fine-tuning, and more.
Linguist & Taxonomy Specialists
Our in-house linguists and create custom taxonomies and guidelines tailored to generative AI model development.
Customized Tooling
Benefit from our proprietary tooling, including our Annotation Platform, designed to streamline team workflows and enhance efficiency in data annotation and management processes.
Fuel Advanced AI/ML Model Development With Innodata’s Data Solutions for Generative AI.
Fuel Advanced AI/ML Model Development With Innodata’s Data Solutions for Generative AI.
Looking to Implement Generative AI Into Your Business Operations?
Innodata’s team of experts help assist in integrating generative AI models into your business operations.
We will guide you through the process, from identifying strategic opportunities to implementation to ensuring continuous success.
Looking to Implement Generative AI Into Your Business Operations?
Innodata’s team of experts help assist in integrating generative AI models into your business operations.
We will guide you through the process, from identifying strategic opportunities to implementation to ensuring continuous success.
Case Studies
Generative AI Customer Success Stories
Creating Health and Medical Dialogues Across 8+ Specialties
Read More >
Training Text to Image Model By Providing Image Captions, Across 50+ Subject Areas
read more >
Chatbot Instruction Dataset for RAG Implementation
read more >