LLM Fine-Tuning Services & Custom LLMs

LLM Fine-Tuning &
Custom LLM
Development

Train and adapt open-source and proprietary foundation models on your private domain data to achieve high task accuracy, custom formatting, and low inference latency.

✓

Domain-Specific Precision: Teaches models industry-specific terminology, specialized logic, and custom output structures.

✓

Lower Inference Costs: Replace expensive commercial API calls with lean, highly optimized task-specific Small Language Models (SLMs).

✓

100% IP & Data Ownership: Your model weights, fine-tuning datasets, and checkpoints remain your exclusive property.

Problem & Solution

General Foundation Models Fail on Niche Tasks

Out-of-the-box LLMs are trained on general internet data. They often fail when tasked with strict formatting requirements, specialized medical/legal reasoning, or niche industry terminology.

The Problem

Relying entirely on complex system prompts (prompt engineering) consumes high token volumes, slows down latency, and still results in inconsistent formatting.

The Solution

We apply Parameter-Efficient Fine-Tuning (PEFT/LoRA) and Supervised Fine-Tuning (SFT) to embed your domain knowledge and output formats directly into the model weights.

24/7

Always-On AI Operations

Phases: Audit, Build, Test, Monitor

12+

Years of Hands-On IT Engineering Experience

Offices: Dubai, Karachi & USA

Book a Free AI Strategy Call ›

Technical Specifications

No Component Technical Framework

01 Target Architectures Llama, Mistral, Mixtral, Qwen, DeepSeek, OpenAI Fine-Tuning

02 Training Tooling PyTorch, Hugging Face Transformers, Axolotl, Unsloth, DeepSpeed

03 Quantization & Serving vLLM, TensorRT-LLM, GGUF, Ollama, TGI

04 Deployment Hardware NVIDIA A100 / H100 GPU clusters, AWS Bedrock / RunPod endpoints

Implementation Process

A 6-week path from data strategy to production deployment.

Implementation Process

A 6-week path from data strategy to production deployment.

WEEKS 1–2 01

Data Strategy

Identify target tasks, extract historical records, and construct structured evaluation datasets.

WEEKS 3–4 02

Training Runs

Run LoRA/SFT training runs with hyperparameter optimization.

WEEK 5 03

Evaluation & Alignment

Benchmark task accuracy against commercial baselines using automated evaluation harnesses (e.g., Ragas, DeepEval).

WEEK 6 04

Optimization & Deployment

Quantize weights for low-latency inference and deploy onto your private GPU infrastructure.

01 WEEKS 1–2

Data Strategy

Identify target tasks, extract historical records, and construct structured evaluation datasets.

02 WEEKS 3–4

Training Runs

Run LoRA/SFT training runs with hyperparameter optimization.

03 WEEK 5

Evaluation & Alignment

Benchmark task accuracy against commercial baselines using automated evaluation harnesses (e.g., Ragas, DeepEval).

04 WEEK 6

Optimization & Deployment

Quantize weights for low-latency inference and deploy onto your private GPU infrastructure.

Frequently Asked Questions

Got questions? We've answered the most common ones about working with RixDigi — from services to timelines to support.

When should we use Fine-Tuning instead of RAG?

Use RAG to give an AI access to dynamic, changing knowledge (documents, policies). Use Fine-Tuning when you need the model to learn a specific tone, adhere strictly to complex output formats, or specialize in niche technical reasoning.

Are our training datasets protected?

Yes. Fine-tuning is executed entirely in isolated, non-shared cloud environments. Your dataset is never exposed to public repositories.

LLM Fine-Tuning &
Custom LLM
Development

General Foundation Models Fail on Niche Tasks

Core Capabilities

Technical Specifications

Implementation Process

Implementation Process

Data Strategy

Training Runs

Evaluation & Alignment

Optimization & Deployment

Data Strategy

Training Runs

Evaluation & Alignment

Optimization & Deployment

Related reading

Your Success Story Starts Here
Let’s Begin!

LLM Fine-Tuning & Custom LLM Development

General Foundation Models Fail on Niche Tasks

Core Capabilities

Technical Specifications

Implementation Process

Implementation Process

Data Strategy

Training Runs

Evaluation & Alignment

Optimization & Deployment

Data Strategy

Training Runs

Evaluation & Alignment

Optimization & Deployment

Related reading

Your Success Story Starts HereLet’s Begin!

LLM Fine-Tuning &
Custom LLM
Development

Your Success Story Starts Here
Let’s Begin!