AI integration
AI Integration Services
Practical AI features that save time — custom assistants, document search, and workflow automation built into your product or operations.
Most businesses do not need generic AI demos. They need AI integrated into real workflows: answering questions across internal documents, generating reports, or automating repetitive operational tasks.
We build AI integration for US companies — including custom AI assistants, RAG-based document search, LLM API integrations, and production-ready AI features inside web applications.
Practical AI use cases
AI work should tie directly to a business process or product feature.
- —Internal knowledge assistants for employees
- —Customer support assistants trained on your documentation
- —Document search across large file repositories
- —Automated report generation
- —AI features inside an existing SaaS product
What AI integration can include
Solutions are designed for reliability, not novelty.
- —Use-case discovery and feasibility assessment
- —RAG pipelines and vector database setup
- —OpenAI, Claude, or other LLM API integration
- —Prompt design and workflow orchestration
- —Security, access control, and data handling
- —Monitoring and iteration after launch
How AI projects are scoped
We start with the workflow you want to improve, then choose the simplest architecture that works.
- —Define the job the AI needs to do
- —Identify data sources and access requirements
- —Build a focused prototype or feature
- —Harden for production use
Frequently asked questions
What is RAG and do I need it?
RAG (Retrieval-Augmented Generation) lets an AI answer questions using your company's documents and data. It is the right approach when answers must be grounded in internal knowledge rather than general model training.
Can you add AI to an existing web application?
Yes. AI features can be added to existing SaaS products, internal tools, and customer portals as part of a broader development engagement.
How do you handle data privacy?
Data handling depends on your requirements. Architecture decisions cover access control, data retention, and which models or services process your content.
Related services
Ready to start?
Send a short description of your project and we'll explain how we'd approach it.
Discuss AI Integration