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intellisane Annotate

RLHF Services for LLMS & LVMS

Refine generative AI models with Reinforcement Learning from Human Feedback (RLHF) using expertly curated, human-labeled datasets that improve safety, alignment, and response quality.

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Everything you need to deploy your app

  • Preference Ranking

    Preference Ranking

  • Error Annotation
  • Content generation
  • Attribute Feedback
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Agile Process

We adapt quickly to your evolving project needs. Whether you're launching a proof of concept or scaling to millions of annotations, our agile workflow ensures speed, flexibility, and consistent quality — without the bottlenecks

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Highest Data Security

Your data is your asset — and we treat it that way. We follow strict data privacy protocols, secure infrastructure practices, and industry-grade compliance standards to ensure your information stays protected at every step.

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Cost-Effective for Startups to Enterprises

From emerging startups to global enterprises, we offer scalable pricing models that align with your budget and goals. You get top-tier annotation quality — without the enterprise-only price tag.

Power Optimizing Accuracy for LLMS & LVMS

A Complete Solution for AI SaaS Startups erent types of Industries annotation. erent types of Industries annotationerent types of Industries annotation. erent types of Industries annotationerent types of Industries annotation.

High-quality prompts and responses to fine-tune intelligent behavior.

We create high-quality prompt-response pairs tailored to your domain and model objectives. Each dataset is designed to teach AI how to respond in a helpful, honest, and safe manner.

This forms the foundation of effective reinforcement learning from human feedback.

2.5x

Cost reduced
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~99%

Model Efficiency
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96%

Returning Client
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Wall of love

What Our Clients Says

Our clients share how Intellisane AI’s precise and reliable annotation services boosted their AI projects, showcasing our commitment to quality and trust.

  • Intellisane AI played a key role in helping us reach 97% accuracy in automating foundation layout detection. Their deep understanding of spatial data and labeling precision brought measurable improvements to our AI pipeline. The team was communicative, detail-oriented, and delivered everything ahead of schedule.
    Sr. ML Engineer
    S. RagavanSr. ML Engineer
    S. Ragavan
  • Our fashion AI model required pixel-level segmentation across 72 garment categories—and Intellisane AI handled it flawlessly. They quickly adapted to our complex annotation guidelines and delivered consistent, high-quality labels at scale. Their domain focus, speed, and attention to visual detail were exactly what we needed.
    Sr. AI Scientist & Team Lead
    Valerio ColamatteoSr. AI Scientist & Team Lead
    Valerio Colamatteo
  • For our ADAS project, Intellisane AI delivered precise vehicle annotations across diverse traffic scenes, including multiple object classes and occlusion scenarios. Their expertise in automotive data workflows and quality-first mindset helped us pass all validation checks, with timely delivery and professional communication throughout.
    Co-Founder & CTO
    Raphael LopezCo-Founder & CTO
    Raphael Lopez
Transportations and Navigations

Transportations and Navigations

Power your transportation and navigation solutions with the highest quality training data and accelerate ML developments.

Robotics and Manufacturing

Robotics and Manufacturing

Transform your manufacturing and robotics operations with our precise data annotation services, driving efficiency, enhancing safety, and powering your machine learning models for optimal performance.

Medical and Healthcare

Medical and Healthcare

Transform healthcare solutions through accurate and comprehensive medical data annotations, ensuring enhanced diagnostic capabilities and improved patient outcomes.

Food and Agriculture

Food and Agriculture

Enhances the capabilities of AI systems with best-quality training data to monitor crop health, predict yields, and automate processes, ultimately driving efficiency and sustainability in the agricultural sector.

Questions About RLHF?

Frequently Asked Questions

RLHF aligns generative AI with human values by training models using real human feedback—improving relevance, safety, and output quality.

What is RLHF, and why is it important in Generative AI?

Reinforcement Learning from Human Feedback, is a method used to fine-tune generative models like ChatGPT to behave more usefully and safely. It involves humans ranking or rating outputs, which are then used to teach the model preferences—aligning AI responses more closely with human expectations.

How does RLHF improve the quality of AI-generated content?

By integrating human judgment into the training loop, RLHF helps models understand context, tone, and appropriateness better than rule-based approaches. It filters out harmful, biased, or irrelevant outputs and boosts response accuracy, safety, and user satisfaction.

What kind of human feedback is used in RLHF processes?

Feedback can include ranking multiple AI responses, providing preference scores, flagging harmful or biased outputs, or offering corrections. This data trains a reward model that guides the AI to prefer outputs that better match human expectations.

How is RLHF different from traditional annotation?

Traditional annotation focuses on labeling existing data (e.g., tagging named entities or bounding boxes), while RLHF involves judging the quality of model outputs. It’s more subjective, requiring trained humans who understand nuance, ethics, and domain context.

How does Intellisane AI ensure quality and consistency in RLHF projects?

We apply a multi-layered quality control process involving reviewer calibration, inter-rater agreement scoring, and continuous feedback loops. Every RLHF project is managed by domain experts to ensure that feedback is consistent, scalable, and aligned with your model’s purpose.
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