We train proprietary AI models on your specific company data. By fine-tuning LLMs on your PDFs, call logs, and support tickets, we create a hyper-accurate intelligence engine that knows your business inside out.
Book a DemoFine tuning an LLM means taking a powerful base model and training it further on your specific business data, so it stops giving generic answers and starts responding like a true expert in your domain. Instead of relying on a model trained on the open internet, our LLM fine-tuning services teach the model your products, your terminology, and your internal logic—delivering accuracy a standard AI simply can't match.
The process begins with data curation. We collect and clean your existing business data—from technical manuals to successful sales transcripts. We then use this data to fine-tune a base model (like Llama 3 or GPT-4), teaching it your specific brand voice, product details, and internal logic. The result is a private, fine-tuned LLM that is significantly more accurate and relevant than any generic AI.
A proven, step-by-step process from raw business data to a live, production-ready model.
We start by understanding your goals, use cases, and existing data. We map exactly what you want the model to do, identify the right data sources, and define clear accuracy targets so success is measurable from day one.
Great models start with great data. We collect, clean, and structure your business data—technical manuals, support tickets, and sales transcripts—into a high-quality training set. If your data isn't ready, we prepare and label it for you.
This is where the real engineering happens. We fine-tune the base model on your data, optimize the key training parameters, and run rigorous testing to ensure the model performs exactly as your business requires—accurate, consistent, and reliable.
Once tested, we deploy your private fine-tuned model into a secure environment and connect it to your existing stack—CRM, helpdesk, or voice agents—configured for fast, real-time performance.
We train the model on labeled, real-world examples from your business so it learns the exact behavior you need—accurate classification, on-brand responses, and reliable comprehension.
We tune only the layers that matter, dramatically reducing compute cost and training time while preserving—and often improving—accuracy. This makes fine-tuning an LLM affordable, not enterprise-only.
For specialized fields like legal, medical, or finance, we adapt the model to your industry's terminology and edge cases for peak accuracy on the tasks that matter most.
Where it adds value, we combine fine-tuning with a live knowledge base so the model can pull real-time, factual answers directly from your documents—eliminating outdated or invented responses.
We refine the model using human feedback loops, continuously aligning its responses with what your team and customers actually expect over time.
Custom support models for complex technical products
Brand-aligned content generation for marketing teams
Specialized reasoning models for legal and medical research
We are experts in the nuances of model training. We don't just "prompt engineer"—we deep-engineer the weights of the model to ensure your fine-tuned LLM performs exactly as your business requires.
SOC2 compliant infrastructure with end-to-end encryption for all data processing.
We don’t use generic APIs. We fine-tune models specifically for your business logic.
Go from concept to live production in weeks, not months, with our modular architecture.
While more is usually better, we can achieve significant improvements with as few as a few hundred high-quality examples.
Absolutely not. Your fine-tuned model and the data used to train it are your exclusive property and are kept entirely private.
Most projects go from concept to live production in a few weeks. The exact timeline depends on the size of the model, the volume of data, and the complexity of your use case—we'll give you a clear estimate after the initial audit.
It depends on your goal. Prompt engineering is quick but limited, RAG is ideal for pulling live facts from your documents, and fine-tuning permanently teaches the model your voice and logic. Often the best results combine fine-tuning with RAG—we'll recommend the right mix for you.
We work with leading open-source models like Llama 3 as well as commercial models like GPT-4. We help you choose the right one to fine-tune based on your accuracy needs, budget, and privacy requirements—no vendor lock-in.
We process all data on SOC2-compliant infrastructure with end-to-end encryption, both in transit and at rest. Your data and your model remain entirely private and are never used to train anyone else's model.
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