Domain-specific AI models fine-tuned on your proprietary data — delivering performance that generic foundation models simply cannot match for your specific use case.
Foundation models like GPT-4 and Claude are extraordinarily capable at general tasks — but they've never seen your contract templates, your product catalogue, your medical records, your support ticket history. Fine-tuning adapts a foundation model to your specific domain, vocabulary, format, and task requirements, achieving dramatically better performance on your use case.
Dawnovation AI manages the entire custom model lifecycle: dataset curation, fine-tuning, rigorous evaluation, deployment, and continuous improvement. The result is a proprietary model that understands your business — and stays entirely under your control.
We work with your existing data — documents, logs, records, labelled examples — to curate high-quality training datasets, with cleaning, deduplication, and format standardisation.
Fine-tune foundation models (OpenAI, Llama, Mistral, Gemma) on your labelled examples using state-of-the-art techniques including LoRA and QLoRA for efficiency.
Reinforcement Learning from Human Feedback to align model behaviour with your specific quality standards, tone requirements, and domain expertise.
Before deployment, models are evaluated on held-out test sets with task-specific metrics. We benchmark against baseline foundation models and track improvement rigorously.
Models are quantised, compiled (ONNX, TensorRT), and served behind low-latency inference APIs — often 10x smaller and faster than the base model.
As your data grows, models are periodically retrained with new examples. All model versions are tracked with MLflow for full reproducibility and rollback.
Define the precise task the model must perform, assess your available training data, identify gaps, and determine the right base model and approach.
Collect, clean, format, and annotate training data. This is often the most important step — model quality is fundamentally bounded by data quality.
Run controlled fine-tuning experiments, tracking hyperparameters and evaluation metrics. Multiple variants are trained and compared.
Rigorous evaluation on held-out data, adversarial testing, bias assessment, and performance benchmarking vs the baseline foundation model.
Production deployment with inference API, latency and cost monitoring, automatic retraining triggers based on performance drift detection.
Models trained to classify your specific document types — contracts, invoices, claims, tickets — with accuracy exceeding human performance.
Extract proprietary entity types from your text — product codes, internal identifiers, industry-specific terms — that generic models miss entirely.
Generate content in your specific format and style — product descriptions, legal clauses, medical summaries, financial commentary — matching your brand and standards.
Fine-tuned models that answer questions about your products, policies, and processes with precision — outperforming RAG-only approaches on structured, stable knowledge.
Core stack used for Custom AI Models
Everything you need to know about our custom ai models service.
Still have questions? →It depends on the task. Instruction fine-tuning can be effective with as few as 500–2,000 high-quality examples. Classification tasks often need 1,000–10,000 labelled examples per class. We assess your data during discovery and advise on collection strategies if needed.
Never. Your training data and resulting model are entirely private. Fine-tuning is performed in isolated environments, and the resulting model is exclusively yours. We can also perform training entirely within your own cloud account if required.
RAG excels at grounding answers in large, frequently updated document collections. Fine-tuning excels at adapting model behaviour, format, tone, and reasoning patterns to your domain. The two are often complementary — many of our best systems use both.
We work with Llama 3, Mistral, Gemma, Qwen, OpenAI GPT series, and others depending on your requirements around cost, speed, privacy, and capability. We recommend the right base model for your specific task.
Ready to get started?
Book a free discovery call — we’ll scope your project and outline a clear path forward.
Book Free Consultation