Supervised Fine-Tuning Services
Teach your models what “good” looks like – at scale.
Before aligning AI with preferences, you need to show it the right answers.
LXT’s Supervised Fine-Tuning (SFT) services deliver high-quality instruction-response pairs curated by experts – so your generative models learn to respond with relevance, accuracy, and clarity from the start.
Why leading AI teams choose LXT for supervised fine-tuning services
Instruction-response pairs, ready for training
We create or validate clean, structured samples that demonstrate the behavior your model should learn – from factual QA to task execution.
Multilingual, multimodal coverage
Fine-tune across languages, domains, and modalities with data built by native speakers, domain experts, and certified annotators.
Domain-specific expertise
Tap into 250K+ specialists across technical, legal, medical, and user-facing domains to ensure contextually relevant examples.
Bias-aware dataset construction
Balance, diversity, and cultural nuance are baked into our sourcing and review workflows to support fair and inclusive model outputs.
Secure, enterprise-ready delivery
All SFT projects follow strict privacy and compliance protocols, with optional secure facility execution for sensitive instruction data.
Scalable production pipelines
Whether you need 1,000 or 1M+ pairs, we deliver consistent, model-ready training sets with version control, metadata, and traceability.
LXT for supervised fine-tuning services
Supervised Fine-Tuning is the foundation of any performant LLM.
It teaches models how to respond, reason, and communicate effectively – before preference-based tuning or deployment testing begins.
At LXT, we specialize in building and validating high-quality instruction–response datasets tailored to your use case, domain, and target audience.
From curated question-answer pairs to complex multi-step tasks, our global experts deliver the clean, consistent inputs your model needs to learn reliable behavior – fast and at scale.
Our supervised fine-tuning services include:
From data creation to quality review, we support every step of your supervised fine-tuning pipeline with scalable workflows and expert input.
Instruction generation
Designing clear, relevant prompts that reflect your use case – ranging from open-ended questions to complex task commands.
Response drafting
Crafting accurate, context-appropriate responses that demonstrate ideal model behavior in domain-specific or general-use scenarios.
Instruction–response pairing
Matching inputs and outputs for optimal training quality – structured, token-balanced, and metadata-tagged.
Response validation & scoring
Verifying factual accuracy, completeness, tone, and task relevance through expert human review.
Bias and safety checks
Reviewing training pairs for potential demographic, cultural, or topical bias to support fair and responsible AI behavior.
Multilingual fine-tuning data
Creating SFT datasets in 1,000+ language locales with native-language reviewers and culturally adapted examples.
How our supervised fine-tuning project process works
Every supervised fine-tuning project at LXT follows a structured, collaborative workflow – designed to deliver clean, aligned, and ready-to-train instruction – response pairs.
We start by discussing your goals, data requirements, use cases, and quality expectations – so the project can be scoped and structured around your specific needs.
Our team sets up the workflow on LXT’s secure platform, creates detailed reviewer briefings, and assigns qualified linguists or domain experts based on your target use case.
We build task guidelines, launch a small-scale pilot, and use calibration rounds to refine clarity, coverage, and reviewer consistency.
Prompt–response creation and validation begin at scale—following your requirements for structure, length, tone, and metadata.
We apply gold tasks, reviewer overlap, and audit sampling to ensure output consistency, accuracy, and readiness for training.
Final datasets are anonymized, version-controlled, and delivered in your preferred format—ready to plug into your fine-tuning pipeline.
We support evolving goals by updating guidelines, scaling to new tasks, and providing new data variants over time.
Secure services for supervised fine-tuning projects
Supervised fine-tuning often involves proprietary prompts, customer data, or domain-specific instructions. At LXT, every project is run with enterprise-grade security by default.
Our infrastructure is ISO 27001 and SOC 2 certified, with role-based access controls, encrypted storage, and audit-ready workflows.
For sensitive data, we offer secure facility options – where trained annotators complete tasks in controlled environments.
All instruction–response data is anonymized, versioned, and handled under mutual NDAs to ensure full confidentiality and compliance.
Industries & use cases for supervised fine-tuning services
LXT’s supervised fine-tuning services support organizations building reliable and domain-adapted generative AI systems.
We help teams train models that respond clearly, correctly, and safely – across languages, industries, and applications.
Technology & Generative AI
Fine-tune LLMs and chatbots with instruction–response pairs tailored to product, coding, or general-knowledge tasks.
Healthcare & Life Sciences
Train models to generate summaries, answer clinical questions, or interpret structured data with domain-accurate language.
Finance & Insurance
Build assistants that respond clearly and compliantly to customer queries about policies, transactions, or risk explanations.
Media & E-Commerce
Teach models how to write product descriptions, summarize reviews, or assist in content moderation workflows.
Public Sector & Legal
Create instruction data that reflects local policy, legal terminology, or multilingual service contexts for government and law.
Automotive & Robotics
Train assistants and control systems to follow task-specific prompts and provide clear, contextual responses in technical domains.
Further validation & evaluation services
Supervised fine-tuning is one step in building robust, aligned AI systems.
LXT offers a full range of services to support data readiness, safety evaluation, and post-deployment tuning.
AI data validation & evaluation
Explore our full-service portfolio for AI data quality and model performance evaluation.
AI training data validation
Ensure your datasets are clean, consistent, and representative before model training begins.
Search relevance evaluation
Evaluate how effectively your systems retrieve and rank content based on real user intent and expectations.
AI model evaluation
Assess model responses for factual accuracy, safety, and cultural relevance – across text, speech, and vision.
Human in the loop
Integrate expert human feedback into live systems for ongoing validation and performance improvement.
RLHF services
Collect structured human preferences to train reward models and align LLM outputs with user expectations.
LLM red teaming & safety
Validate the impact of your training data by testing how models respond to unsafe, biased, or adversarial prompts.
Prompt engineering & evaluation
Evaluate prompt candidates before including them in SFT datasets – ensuring clarity, diversity, and task coverage.
FAQs on our supervised fine-tuning services
Supervised fine-tuning (SFT) is the process of training a model on curated instruction–response pairs to teach it how to answer prompts correctly and consistently.
We create and validate instruction–response pairs across domains, languages, and modalities—including open-ended prompts, factual QA, task-based instructions, and multilingual tasks.
Yes. We can build on your existing data, validate it, or create new samples based on your structure and domain-specific needs.
We use reviewer calibration, gold tasks, multi-layer QA, and audit reviews to ensure consistency, accuracy, and training-readiness.
Yes. All projects are ISO 27001 and SOC 2 certified, with NDA protection, secure infrastructure, and optional secure facility workflows.