Reinforcement Learning from Human Feedback

Aligning GenAI outputs with real-world expectations, safely, accurately, and at scale.

התחל

As generative AI becomes mission-critical, aligning model outputs with human preferences is no longer optional, it’s essential. Qualitest’s Human Preference Optimization services empower enterprises to enhance their LLMs with precision-guided human feedback, ensuring outputs are not only accurate but contextually, ethically, and operationally aligned with business goals.

 

Reinforcement Learning from Human Feedback (RLHF)

Our RLHF framework ensures that your models continuously learn from nuanced human preferences, closing the gap between raw model capabilities and user expectations.

What we offer:

  • Reward Modeling
    Use real-world, expert-labeled examples to train your models on what ‘good’ looks like, factually accurate, relevant, and aligned with business tone.
  • Policy Tuning with Safety Constraints
    Adjust model behavior within defined ethical and regulatory boundaries, reducing hallucinations, bias, and toxicity while maintaining output fluency and coherence.

 

  • Human-in-the-Loop Expertise
    Our curated network of multilingual domain specialists evaluates output in real-time, providing granular preference signals to improve LLM decision-making in complex scenarios.
  • Iterative Feedback Loops
    Deploy ongoing A/B testing, Likert scoring, and pairwise comparisons to fine-tune your models, across modalities, use cases, and demographics.

Direct Preference Optimization

We build intelligent systems to collect, rank, and apply human feedback across large volumes of outputs, fast, securely, and in context.

Key Capabilities:

  • Custom Preference Pipelines
    Create bespoke feedback collection flows using task-specific guidelines and scoring rubrics for tailored optimization.
  • Structured Feedback at Scale
    Implement dynamic labeling, ranking, and free-form feedback, structured to feed into your reward models and reinforce preferred behaviors.

 

  • Expert Crowd Deployment
    Engage a global pool of domain-trained contributors for multilingual, culturally relevant preference evaluations, spanning finance, healthcare, public sector, legal, and more.
  • Bias, Stereotype, and Hallucination Checks
    Assess model responses across sensitive and high-risk content with pre-designed prompt challenges and red teaming inputs.

Beyond the Basics: Enterprise-Grade Alignment

With decades of experience in quality engineering and AI data services, Qualitest brings unmatched rigor and reliability to every stage of human feedback optimization.

  • Contextual Alignment:
    Optimize for correctness, tone, cultural fit, and business relevance.
  • Performance Evaluation:
    Measure accuracy, recall, and toxicity using automated and expert-based scoring systems.
  • Output Control & Trustworthiness:
    Balance creativity with compliance, ensuring safe, predictable, and value-generating AI deployments.
  • Multimodal Optimization:
    Apply feedback and reward modeling across text, image, audio, and video outputs to train consistently intelligent GenAI systems.

Why Qualitest?

No other partner offers the depth of AI domain expertise, quality assurance heritage, and real-world operational scale that Qualitest does. Whether you’re developing customer-facing chatbots, enterprise copilots, or internal knowledge assistants, our human preference optimization ensures your GenAI models speak your language, accurately, safely, and effectively.

Trust GenAI Data services by Qualitest to bridge the final mile between model capability and human expectations.

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