LLM Development
Custom large language model development, fine tuning, and deployment. We build domain specific language models that understand your business context and deliver accurate results every time.
Language models built for your domain
From fine tuning existing models to training custom architectures, we build language models that understand your business better than any generic API.
LLM Fine Tuning
We fine tune open source language models on your proprietary data using LoRA, QLoRA, and full parameter training. The result is a model that understands your domain vocabulary, tone, and business logic.
Custom Model Training
For organizations with unique requirements, we train language models from scratch or continue pretraining on domain specific corpora. Custom tokenizers, architectures, and training objectives tailored to your needs.
On Premise LLM Deployment
We deploy language models on your own infrastructure using optimized serving frameworks. All data stays within your network with zero cloud dependencies, meeting the strictest compliance requirements.
Model Evaluation and Benchmarking
Rigorous evaluation against domain specific benchmarks, not just generic metrics. We measure accuracy, latency, throughput, and safety to ensure your model performs reliably in production scenarios.
Prompt Engineering
Systematic prompt design, testing, and optimization for your specific workflows. We build prompt libraries, chain of thought templates, and few shot examples that maximize model accuracy and consistency.
LLM Security and Guardrails
We implement input validation, output filtering, jailbreak prevention, PII detection, and content safety layers. Your language model operates within defined boundaries and rejects harmful or off topic requests.
From raw data to production LLM
A structured approach to building custom language models. Every step is transparent, measurable, and designed to deliver a model that performs in the real world.
Data Collection
We work with your team to gather, clean, and format training data. We identify gaps, remove noise, and create high quality instruction response pairs for fine tuning.
Base Model Selection
We evaluate open source models against your requirements: domain fit, parameter count, inference speed, and licensing. We recommend the optimal starting point for your use case.
Fine Tuning
We train the model on your data using the most efficient technique for your budget and timeline. LoRA for quick iterations, full fine tuning for maximum quality.
Evaluation
We test the fine tuned model against domain benchmarks, adversarial inputs, and real world scenarios. Multiple rounds of evaluation ensure the model meets your accuracy targets.
Deployment
We deploy the model with optimized inference, monitoring, and logging. Whether cloud or on premise, the model is production ready with proper scaling and fallback configuration.
Built with state of the art LLM tools
We use the most advanced training, fine tuning, and serving frameworks to build language models that are accurate, fast, and cost effective.
Domain specific language models
Every industry has its own vocabulary, regulations, and knowledge requirements. We build language models that speak the language of your domain.
Manufacturing
Domain specific language models for technical documentation, maintenance manuals, quality standards, and production process knowledge that general models cannot handle.
Retail
Custom models trained on product catalogs, customer interactions, and brand guidelines for personalized recommendations, customer service, and marketing content.
Healthcare
Medical language models trained on clinical literature, patient records, and treatment protocols. HIPAA compliant deployment for clinical decision support and documentation.
Real Estate and Construction
Models fine tuned on building codes, contract language, project documentation, and regulatory requirements for automated compliance checking and report generation.
Logistics and Supply Chain
Custom models for shipping documentation, customs regulations, supplier communications, and demand forecasting narratives that understand logistics vocabulary.
Security and Surveillance
Language models trained on security protocols, incident reports, threat intelligence, and compliance frameworks for automated analysis and reporting.
Frequently asked questions
Common questions about LLM development, fine tuning, and deployment.
When should I fine tune an LLM instead of using an API?
Fine tuning makes sense when you need consistent domain expertise, lower per query costs at scale, data privacy guarantees, or responses that match a specific style and format. If you process thousands of queries daily in a specialized domain, a fine tuned model typically outperforms generic API calls.
What training data do you need to fine tune an LLM?
We work with instruction response pairs, domain documents, conversation logs, and structured knowledge bases. As few as 500 to 1,000 high quality examples can produce significant improvements. We help you curate, clean, and format your data for optimal training results.
How much does LLM fine tuning cost?
Cost depends on the base model size, training data volume, and compute requirements. A LoRA fine tune on a 7B parameter model with 5,000 examples typically takes 2 to 3 weeks. Larger models and RLHF alignment take longer. We provide detailed estimates after reviewing your requirements.
Can you deploy custom LLMs on our own servers?
Yes. We deploy fine tuned models on your infrastructure using optimized serving frameworks like vLLM and Ollama. This keeps all data and inference on premise, meeting strict compliance requirements. We also optimize models for your specific hardware to maximize throughput.
How does a custom LLM compare to using GPT or Claude APIs?
Custom models offer better domain accuracy, lower latency, predictable costs, and complete data control. API based models are better for general purpose tasks and rapid prototyping. Many clients use both: APIs for exploration and custom models for production workloads with specific requirements.
Ready to build your own language model?
Tell us about your domain, data, and use case. We will design a custom LLM strategy that delivers measurable results.