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.

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Years Experience

Projects Delivered

Client Satisfaction

0/7

Support Available

Who We Are

ClickMasters provides top artificial intelligence ai services for businesses that need reliable digital solutions for their operations, customers, and growth. Our team works with startups, small businesses, and growing companies to plan, design, and develop software that solves real business problems.

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.

01 / 05

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. We build software that scales with your ambition from first-user MVPs to enterprise-grade, cloud-native systems. Whether you need a multi-tenant SaaS platform, a custom ERP, an API-first integration layer, or a cross-platform mobile app, our approach remains the same, clean architecture, production-ready quality, and infrastructure designed for 10x growth.

02 / 05

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. We build software that scales with your ambition from first-user MVPs to enterprise-grade, cloud-native systems. Whether you need a multi-tenant SaaS platform, a custom ERP, an API-first integration layer, or a cross-platform mobile app, our approach remains the same, clean architecture, production-ready quality, and infrastructure designed for 10x growth.

03 / 05

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. We build software that scales with your ambition from first-user MVPs to enterprise-grade, cloud-native systems. Whether you need a multi-tenant SaaS platform, a custom ERP, an API-first integration layer, or a cross-platform mobile app, our approach remains the same, clean architecture, production-ready quality, and infrastructure designed for 10x growth.

04 / 05

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. We build software that scales with your ambition from first-user MVPs to enterprise-grade, cloud-native systems. Whether you need a multi-tenant SaaS platform, a custom ERP, an API-first integration layer, or a cross-platform mobile app, our approach remains the same, clean architecture, production-ready quality, and infrastructure designed for 10x growth.

05 / 05

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. We build software that scales with your ambition from first-user MVPs to enterprise-grade, cloud-native systems. Whether you need a multi-tenant SaaS platform, a custom ERP, an API-first integration layer, or a cross-platform mobile app, our approach remains the same, clean architecture, production-ready quality, and infrastructure designed for 10x growth.

Why Companies Choose ClickMasters?

We blend deep engineering, design clarity, and business-aligned delivery to build products that define industries.

Enterprise

Fine-Tuning vs RAG Clarity

Amber "choose correctly" callout

Architecture

Parameter Efficiency

LoRA/QLoRA with VRAM reduction specifics (75-90%)

KPI-Driven

Inference Optimisation

vLLM, GGUF quantisation, OpenAI-compatible API

Intelligence

MLOps Rigor

DVC, W&B, MLflow, CI/CD with regression blocking, drift detection

Design

Dataset Quality Guidance

100 excellent examples > 10,000 mediocre ones

Our AI Model Development Process

A proven methodology that transforms your vision into reality

Phase 1

Week 1-2

AI Model Scoping

Use case analysis, fine-tuning vs RAG decision, model selection, dataset requirements definition, success metrics.

Phase 2

Week 2-6

Dataset Preparation

Data curation, labelling workflow (Label Studio), dataset formatting, quality review, train/eval/test split. Quality > quantity.

Phase 3

Week 3-8

Model Training

LoRA/QLoRA fine-tuning (Llama/Mistral) or OpenAI fine-tuning API. Hyperparameter tuning, evaluation against hold-out test set.

Phase 4

Week 6-9

Model Evaluation & Alignment

Hold-out test set evaluation, human evaluation for generation quality, RLHF/DPO alignment if required, regression testing.

Phase 5

Week 7-10

Self-Hosted Deployment

vLLM inference optimisation (20-40x throughput), OpenAI-compatible REST API, GPU infrastructure, monitoring dashboards.

Phase 6

Week 8-12

MLOps Pipeline (Optional)

DVC for dataset versioning, Weights & Biases experiment tracking, MLflow model registry, CI/CD for models, blue/green deployment, drift detection.

Phase 7

Ongoing

Ongoing Model Retainer

Retraining on new data, evaluation monitoring, model iteration, drift response.

Technology Stack

Modern technologies and frameworks we use to build secure, high-performance digital experiences.

Frontend Development

React.js

Next.js

Angular

TypeScript

Tailwind CSS

Vue.js

Backend Development

Node.js

Python/Django

Laravel

Java/Spring

Ruby on Rails

Mobile Development

React Native

Flutter

Swift/iOS

Ionic

Kotlin/Android

Database & Storage

PostgreSQL

MongoDB

MySQL

Firebase

Elasticsearch

Redis

Cloud & Infrastructure

AWS

Google Cloud

Azure

Kubernetes

Terraform

Docker

DevOps & Monitoring

GitHub Actions

Jenkins

Prometheus

New Relic

Grafana

Industry Expertise

Deep expertise across multiple industries with tailored AI and software solutions

Domain-Specific LLM Fine-Tuning

Custom Classification & NER

Self-Hosted Private Models

Continuous Training MLOps

AI Model Development Pricing

Transparent pricing tailored to your business needs

AI Model Scoping

4,000 – 8,000

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
Budget Range: 4,000 – 8,000 AUD
Dedicated Project Manager
Quality Assurance Testing
Documentation & Training

Best Value

Dataset Preparation

5,000 – 20,000

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
Budget Range: 5,000 – 20,000 AUD
Dedicated Project Manager
Quality Assurance Testing
Documentation & Training

Custom Enterprise Plan

Custom

Tailored solution for your unique business needs

Custom Package Includes

Fully customized solution
Dedicated support team
Unlimited revisions
Priority response time
SLA agreement
On-site training available

Transparent Pricing

No Hidden Costs

Flexible Engagement

30-Day Support

CEO Vision

To build scalable, intelligent ai model 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

FAQ's

Everything you need to know about our process, timelines, technology stack, and post-launch support.

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