AI Model Development
ClickMasters builds and fine-tunes AI models for B2B companies across the USA, Europe, Canada, and Australia. LLM fine-tuning (GPT-4o, Llama 3, Mistral) for domain-specific accuracy on your proprietary terminology and output formats. Custom classification and extraction models (BERT, RoBERTa, DistilBERT) for production efficiency. MLOps pipelines for training, evaluation, versioning, and deployment. Self-hosted models on your infrastructure when data cannot leave your environment.
Years Experience
Projects Delivered
Client Satisfaction
Support Available
Custom AI Models When Off-the-Shelf APIs Are Not Accurate, Private, or Fast Enough
Fine-Tuning vs RAG Choose Correctly Before Investing
Fine-tuning is NOT the solution for giving an LLM access to your data. That is RAG. Fine-tuning is the solution for changing how a model behaves its writing style, response format, domain-specific vocabulary, or reasoning patterns by training on examples of the behaviour you want.
- Fine-tune when: you need the model to respond in a specific format that prompt engineering cannot reliably produce, you need domain-specific vocabulary and reasoning not in the base model's training, or you need to reduce tokens per response
- Use RAG when: you need the model to know current or proprietary facts, you need source attribution, or the information changes frequently
- Most organisations that ask for fine-tuning actually need RAG ClickMasters will identify the correct solution in the scoping engagement
AI Model Development Services We Deliver
ClickMasters operates as a full-stack ai model development partner. Our team handles every layer of the software delivery lifecycle — product strategy, UI/UX design, backend engineering, cloud infrastructure, QA, and ongoing support.
LLM Fine-Tuning
Custom LLM fine-tuning on proprietary datasets: dataset preparation (prompt-completion pairs or chat format), base model selection (GPT-4o via OpenAI API; Llama 3.1/Mistral via HuggingFace), LoRA/QLoRA training, evaluation (ROUGE, F1, human evaluation), and deployment.
Custom Classification & Extraction Models
Lightweight models for specific tasks: text classification (BERT/RoBERTa fine-tuned), named entity recognition (NER for custom domain entities), binary/multi-class classification. 100-1000x cheaper than LLMs, runs on CPU.
RLHF & Preference Alignment
Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimisation (DPO): preference data collection, reward model training, PPO or DPO fine-tuning, and alignment evaluation.
Self-Hosted Model Deployment
Open-source model deployment (Llama 3 70B, Mistral 7B) on your infrastructure. vLLM for 20-40x throughput improvement, GGUF quantisation for CPU inference, OpenAI-compatible REST API.
MLOps Pipeline Development
End-to-end MLOps infrastructure: data pipeline (DVC, Label Studio), training pipeline (SageMaker, W&B), model registry (MLflow), CI/CD for models, blue/green deployment, drift detection.
Why Companies Choose ClickMasters
Amber "choose correctly" callout
Basic: Misleading "fine-tuning for knowledge" advice
LoRA/QLoRA with VRAM reduction specifics (75-90%)
Basic: Full fine-tuning (unnecessarily expensive)
vLLM, GGUF quantisation, OpenAI-compatible API
Basic: Naive HuggingFace inference (slow, expensive)
DVC, W&B, MLflow, CI/CD with regression blocking, drift detection
Basic: Manual training + deployment
100 excellent examples > 10,000 mediocre ones
Basic: "More data is better" (often wrong)
Our AI Model Development Process
A proven methodology that transforms your vision into reality
AI Model Scoping
Use case analysis, fine-tuning vs RAG decision, model selection, dataset requirements definition, success metrics.
Dataset Preparation
Data curation, labelling workflow (Label Studio), dataset formatting, quality review, train/eval/test split. Quality > quantity.
Model Training
LoRA/QLoRA fine-tuning (Llama/Mistral) or OpenAI fine-tuning API. Hyperparameter tuning, evaluation against hold-out test set.
Model Evaluation & Alignment
Hold-out test set evaluation, human evaluation for generation quality, RLHF/DPO alignment if required, regression testing.
Self-Hosted Deployment
vLLM inference optimisation (20-40x throughput), OpenAI-compatible REST API, GPU infrastructure, monitoring dashboards.
MLOps Pipeline (Optional)
DVC for dataset versioning, Weights & Biases experiment tracking, MLflow model registry, CI/CD for models, blue/green deployment, drift detection.
Ongoing Model Retainer
Retraining on new data, evaluation monitoring, model iteration, drift response.
Technology Stack
Modern tools we use to build scalable, secure applications.
Languages & Frameworks
Data Processing
Infrastructure
Industry-Specific Expertise
Deep expertise across various sectors with tailored solutions
Domain-Specific LLM Fine-Tuning
Custom Classification & NER
Self-Hosted Private Models
Continuous Training MLOps
AI Model Development Development Pricing
Transparent pricing tailored to your business needs
AI Model Scoping
Perfect for businesses that need ai model scoping solutions
Package Includes:
- Timeline: 1 - 2 weeks
- Best For: Use case analysis, fine-tuning vs RAG decision, model selection, dataset requirements
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Dataset Preparation
Perfect for businesses that need dataset preparation solutions
Package Includes:
- Timeline: 2 - 4 weeks
- Best For: Data curation, labelling, formatting, quality review, train/eval split
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
LLM Fine-Tuning (GPT-4o)
Perfect for businesses that need llm fine-tuning (gpt-4o) solutions
Package Includes:
- Timeline: 2 - 4 weeks
- Best For: OpenAI fine-tuning API, eval framework, endpoint deployment
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
LLM Fine-Tuning (Open-Source)
Perfect for businesses that need llm fine-tuning (open-source) solutions
Package Includes:
- Timeline: 4 - 8 weeks
- Best For: Llama/Mistral, LoRA/QLoRA, self-hosted deployment, inference optimisation
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Custom Classification Model
Perfect for businesses that need custom classification model solutions
Package Includes:
- Timeline: 3 - 6 weeks
- Best For: BERT fine-tune, labelled dataset, eval metrics, production deployment
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
Self-Hosted Model Deployment
Perfect for businesses that need self-hosted model deployment solutions
Package Includes:
- Timeline: 3 - 6 weeks
- Best For: vLLM, OpenAI-compatible API, GPU infrastructure, monitoring
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
MLOps Pipeline
Perfect for businesses that need mlops pipeline solutions
Package Includes:
- Timeline: 4 - 8 weeks
- Best For: DVC, W&B, model registry, CI/CD, drift detection, model monitoring
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
AI Model Retainer
Perfect for businesses that need ai model retainer solutions
Package Includes:
- Timeline: Ongoing
- Best For: Retraining on new data, eval monitoring, model iteration, drift response
- Dedicated Project Manager
- Quality Assurance Testing
- Documentation & Training
* All prices are estimates and may vary based on specific requirements. Contact us for a detailed quote.
CEO Vision
To build scalable, intelligent custom software development solutions that empower businesses to grow, automate, and transform in a digital-first world.
We are not building software. We are architecting the infrastructure of tomorrow — systems that think, adapt, and grow alongside the businesses they power. Our mission is to make cutting-edge technology accessible to every ambitious team on the planet.
Amjad Khan
CEO
12+
Years
300+
Projects
98%
Retention
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