LLM Instruction Datasets & RLHF
Building responsible, high-performing LLMs starts with the right data. We create high-quality instruction datasets and apply RLHF techniques to help your models align better with human intent, nuance, and safety.

The World’s Most Trusted LLM Instruction Datasets & RLHF Services
From carefully crafted instruction data to fine-tuned reinforcement learning with human feedback, we deliver high-quality datasets that shape LLMs for accuracy, alignment, and real-world usability.
Explore Our ServicesTrusted by the World's Most Innovative Companies
Pushing the Boundaries Beyond "Acceptable"

Instruction Dataset Creation
We create diverse, high-quality instruction datasets that guide LLMs to perform specific tasks effectively, from summarization and reasoning to translation and classification.
- Generate 50,000+ diverse instruction-response pairs with 98% accuracy validation.
- Cover 15+ task categories including reasoning, creative writing & technical analysis.
- Ensure balanced representation across difficulty levels and use cases.
- Implement rigorous quality control with multi-expert review processes.
Prompt Engineering Support
Our experts design and test optimized prompts that enhance LLM performance and ensure consistent, context-aware outputs for your use case.
- Achieve 40-60% improvement in response quality through systematic prompt optimization.
- Test 100+ prompt variations to identify the most effective formulations.
- Create reusable prompt templates for consistent performance across applications.
- Provide detailed documentation and best practices for prompt management.


Reinforcement Learning with Human Feedback (RLHF)
We fine-tune your models with real human feedback to align them with ethical standards, user intent, and safety guidelines, improving response quality and control.
- Deploy expert human evaluators with domain-specific expertise for nuanced feedback.
- Implement multi-round feedback loops to continuously improve model alignment.
- Reduce harmful outputs by 95% while maintaining model creativity and usefulness.
- Establish comprehensive safety protocols and bias detection mechanisms.
Multi-Turn Conversation Dataset Generation
Train your LLMs to handle realistic, flowing conversations. We build high-quality multi-turn dialogue datasets that reflect how users interact in the real world.
- Generate conversation flows spanning 5-15 turns with natural context progression.
- Include diverse conversation scenarios: customer service, technical support, casual chat.
- Maintain conversation coherence and context awareness throughout extended dialogues.
- Test conversation quality with real user interactions and feedback validation.


Domain-Specific Instruction Tuning
Whether you're in legal, healthcare, finance, or education, we create tailored datasets that align your LLMs to the language, tone, and accuracy your domain demands.
- Leverage subject matter experts with 10+ years of experience in target domains.
- Ensure 99%+ accuracy for domain-specific terminology and regulatory compliance.
- Create specialized datasets covering industry workflows, protocols, and best practices.
- Validate outputs against industry standards and professional benchmarks.
Dataset Quality Review & Iteration
Our team continuously reviews and refines your instruction datasets based on model performance and evolving objectives, keeping your AI sharp and relevant.
- Conduct systematic quality audits using automated tools and human expert review.
- Track performance metrics and identify improvement opportunities through A/B testing.
- Implement continuous feedback loops with regular dataset updates and refinements.
- Guarantee dataset freshness with quarterly reviews and objective-based iterations.

data production
happy experts
precise task matching
perspectives
Why Choose Hurix.ai for LLM Instruction Datasets & RLHF Services
Purpose-Built Datasets for Smarter Language Models
We don’t offer one-size-fits-all data. Our team curates high-quality, domain-specific instruction datasets tailored to your Large Language Model (LLM) goals — from conversational agents to enterprise-specific tasks.
Human Feedback That Actually Teaches Your Model
With a trained pool of domain experts and linguists, we collect Reinforcement Learning from Human Feedback (RLHF) with precision. This helps your models generate more useful, safer, and context-aware responses.
End-to-End Control: From Prompting to Alignment
From instruction tuning to ranking outputs for preference modeling, we handle the complete RLHF cycle — giving you full control over model alignment and ethical output behavior.
Scalable Annotation & Evaluation Workflows
Whether you're fine-tuning a small custom model or a billion-parameter LLM, our scalable data pipelines support high-volume annotation, multi-turn dialog evaluation, and complex reasoning benchmarks.
Built-In Quality, Security & Compliance
We combine multilayered quality assurance, data validation, and privacy-compliant workflows — ensuring your datasets meet regulatory standards and enterprise-grade reliability.
Train Your LLM the Right Way — With the Right Data
Stop relying on generic data. Our curated instruction datasets and expert-tuned feedback help your models deliver accurate, context-aware results.
Get StartedTop Use Cases
AI Research Labs & Innovation Teams
- Building state-of-the-art LLMs that require custom instruction tuning.
- Need high-quality datasets and human feedback to align outputs with research goals.
- Experimenting with RLHF to improve model behavior in sensitive applications.
Conversational AI & Virtual Assistant Teams
- Developing chatbots or voice assistants that require natural, multi-turn interactions.
- Need instruction-rich training data and human-ranked responses to fine-tune intent and tone.
- Looking to improve response safety, consistency, and contextual relevance.
Enterprise AI Product Teams
- Building internal LLMs for summarization, search, knowledge management, or support automation.
- Require custom instruction sets that reflect domain-specific tasks and language.
- Need scalable RLHF workflows to align models with enterprise policies and tone.
Customer Support Automation Teams
- Training LLMs to handle support queries, troubleshoot issues, or escalate tickets.
- Need clear, instruction-rich datasets to teach models how to respond accurately and empathetically.
- Require RLHF to fine-tune tone, intent detection, and escalation logic.
Industries we Serve

Healthcare
Predict patient risks, optimize resources, and improve care with smarter forecasting and supply management.

Retail & E-commerce
Anticipate customer behavior, manage inventory, and drive sales with predictive demand and pricing insights.

Banking & Finance
Strengthen credit scoring, detect fraud early, and forecast market trends to make confident financial decisions.

Manufacturing
Reduce downtime, improve quality, and optimize energy use with predictive maintenance and demand forecasting.

Transportation & Logistics
Enhance routing, delivery accuracy, and fleet management through advanced traffic, fuel, and maintenance predictions.

Telecom
Predict churn, prevent fraud, and boost network performance with data-driven customer and usage insights.

Insurance
Optimize risk assessment, pricing, and fraud detection to deliver smarter, fairer insurance solutions.

Energy & Utilities
Balance supply and demand, protect grids, and unlock renewable energy potential with accurate load forecasting.

Education
Identify at-risk students, personalize learning, and predict enrollment trends to drive student success.

Travel & Hospitality
Forecast bookings, personalize experiences, and optimize pricing to delight travelers and maximize revenue.
See Why Industry Leaders Trust Hurix.ai

Nolan Everhart

The custom instruction datasets we received played a key role in refining our LLM's performance across multiple use cases. The level of detail and alignment with human expectations was outstanding.

Mathew Quinlan

We needed a partner who understood both the nuance of language and the technical rigor of RLHF. The team delivered datasets that not only improved response accuracy but drastically reduced post-training iterations.

Griffin Daley

Thanks to the high-quality prompt engineering and RLHF support, our LLM now performs consistently better in both user engagement and safety benchmarks. It's been a game-changer for our GenAI roadmap.