LLM Application Development
Last updated: February 2026
Full-stack LLM application development including RAG pipelines, AI agents, workflow automation, and custom fine-tuning.
Technologies Used:
Overview
Build sophisticated AI-native applications from the ground up. We specialize in RAG (Retrieval-Augmented Generation) systems, autonomous AI agents, multi-step workflow automation, and custom model fine-tuning. From document Q&A systems to AI-powered research tools, we architect and deliver complete LLM applications optimized for accuracy, cost, and scale.
What's Included
What We Need From You
- 1Use case description and goals
- 2Data sources and document types
- 3Expected user base size
- 4Hosting preferences (cloud/self-hosted)
- 5Security and compliance requirements
Frequently Asked Questions
What is RAG and why does it matter?
RAG (Retrieval-Augmented Generation) connects LLMs to your private data. Instead of relying only on training data, the model retrieves relevant documents before generating answers, dramatically improving accuracy and reducing hallucinations.
Can you build AI agents that take actions?
Yes. We build agents that can search databases, call APIs, send emails, generate reports, and execute multi-step workflows autonomously. We implement safety guardrails and human-in-the-loop approval for sensitive actions.
How do you handle sensitive data?
We support self-hosted deployments, data encryption at rest and in transit, access controls, and audit logging. For regulated industries, we can deploy models locally to keep data within your infrastructure.
What is fine-tuning and when is it needed?
Fine-tuning trains a model on your specific data to improve performance for your domain. It is needed when RAG alone is insufficient, such as specialized terminology, specific output formats, or domain-expert-level responses.
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Ready to Get Started?
Let's discuss your project requirements and provide you with a custom quote tailored to your needs.