LLM Engineering

Custom Model Fine-Tuning & Private Deployment

Hugging FaceGCPAWSGroqDocker

Key Results

  • Zero per-token API costs at scale
  • Complete data privacy — no data leaves client infrastructure
  • Domain-specific performance exceeding generic hosted models
  • Full version control and rollback capability

Tech Stack

Hugging FaceGCP Vertex AIAWS BedrockEC2DockerKubernetesGroqFastAPI

The Problem

For clients who need domain-specific performance, cost efficiency at scale, or data privacy that prohibits using external APIs, standard hosted LLMs are not an option.

Our Solution

We fine-tune and deploy open-source language models on private infrastructure. We have fine-tuned models across domains including legal, financial, healthcare, and specialized NLP tasks. Deployment targets include GCP (Vertex AI), AWS (Bedrock, EC2), and private cloud environments.

Our fine-tuning process covers: data preparation and cleaning, instruction tuning, evaluation framework setup, and deployment with monitoring and version management.

Currently accepting new projects

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