Applied AI & LLM Engineering
From Data to Deployment
We build the AI applications, pipelines and inference systems that turn GPU infrastructure into real-world impact.
Start Your AI ProjectCore Services
Custom LLM Fine-Tuning
Custom LLM fine-tuning & instruction tuning
RAG Pipelines
Retrieval, embeddings, vector store setup, indexing
Embedding & Vector Search
Embedding, vector search & semantic search systems
Secure Model Deployment
Secure model deployment & hosting (on-prem / hybrid / GPU-cloud / cloud)
Inference API Development
Inference API development & deployment (internal / external)
Performance Tuning
Performance tuning & cost optimisation for inference and training
Enterprise-Ready AI Delivery
Data Ingestion & Preprocessing
Data ingestion & preprocessing pipelines
Feature Stores & Dataset Versioning
Feature stores & dataset versioning
CI/CD for ML
CI/CD for ML / MLOps / LLM-Ops workflows
Monitoring & Observability
Monitoring, logging, observability for models in production
Governance & Compliance
Governance, access control, audit logging, compliance (especially for regulated industries)
Use Cases
Private LLM for Enterprise Knowledge Base
Secure, internal LLM deployment for organizational knowledge
Internal Copilots / Virtual Assistants
AI-powered assistants for employee productivity
Document Search / Analysis Tooling
RAG, vector search for document intelligence
AI-Enhanced Data Analytics
Predictive modelling and advanced analytics
Custom AI Products
Custom AI products requiring training + inference + compliance
Our Approach
We work iteratively — from proof of concept through to production deployment and ongoing improvement.
Scope
Define the AI use case, success metrics and data requirements
Prototype
Build proof of concept with rapid iteration and testing
Deploy
Move to production with monitoring, logging and CI/CD
Improve
Refine models, prompts and pipelines based on real-world usage
Technology Stack
We work with modern AI frameworks and tools to build production-ready systems.
Frameworks
- • PyTorch & Hugging Face
- • LangChain & LlamaIndex
- • OpenAI, Anthropic APIs
- • vLLM & TGI inference
- • Ray for distributed training
MLOps
- • MLflow experiment tracking
- • Weights & Biases
- • DVC for data versioning
- • GitHub Actions CI/CD
- • Docker & Kubernetes
Data & Vector DBs
- • Pinecone, Weaviate, Qdrant
- • PostgreSQL with pgvector
- • Elasticsearch for search
- • S3 for data lakes
- • Airflow for pipelines
Example Use Cases
Real-world AI applications we've built for clients across industries.
Document Intelligence
RAG system for legal contract analysis — extracting clauses, identifying risks and answering questions across 10,000+ documents.
LlamaIndex, GPT-4, Pinecone
Customer Support Automation
Fine-tuned Llama 3 model for technical support responses — reducing ticket resolution time by 60%.
Llama 3 70B, LoRA fine-tuning, vLLM
Financial Risk Modeling
Custom transformer model for credit risk prediction on sovereign Australian data — meeting APRA compliance.
PyTorch, TerraGPU, PostgreSQL
Research Paper Search
Semantic search engine for academic papers — enabling natural language queries across 500K+ publications.
Sentence Transformers, Weaviate, FastAPI
Why Partner with Salt Labs for AI Engineering
Deep Infrastructure + Model Engineering Expertise
Understanding of GPU, hybrid-cloud infrastructure and model engineering
End-to-End Delivery
Hardware, platform, application stack — all integrated
Sovereign, Secure and Compliant
Environment for sensitive data and regulated industries
Reduced Complexity
We handle infrastructure and ML stack, you get business-ready AI
Ready to Build Your AI System?
Start your AI project with Salt Labs.