Custom AI Development
Specialized Model Fine-Tuning & Private Cloud Deployment
Overview
For companies with strict compliance, proprietary codebases, or specialized domains, relying on public APIs is not an option. Custom AI Development builds bespoke models tailored specifically to your corporate protocols. We fine-tune models, perform quantization for lower latency, and deploy private inference endpoints on AWS, Azure, or GCP.
Primary Challenges Solved
High API usage costs for large-scale summarization or data processing workflows.
Strict regulations preventing the transmission of data to external AI servers.
Off-the-shelf models lacking deep understanding of proprietary industry terminology.
The Altimet AI Solution
We design end-to-end model pipelines: curating training data, executing fine-tuning runs (QLoRA), verifying model performance, and deploying containerized models via vLLM inside your private cloud.
Technical Pipeline Flow
Data Curation
Cleans, structures, and formats your internal datasets into training inputs.
Fine-Tuning Loop
Runs parameter-efficient fine-tuning on enterprise cloud clusters.
Evaluation Matrix
Compares model accuracy, speed, and cost parameters against baseline metrics.
Inference Server
Deploys models using vLLM in Docker container configurations.
Quantifiable Metrics
72%
Model API Cost Savings
0%
Data Privacy Risk
40ms
Inference Latency
Delivery Timeline
Security & Latency FAQs
Common operational concerns for enterprise deployments.
Ready to Implement Production-Grade AI?
Schedule a technical discovery session with our engineering team to review model schemas, latency specs, and VPC safety deployment strategies.