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Retrieval-Augmented Generation (RAG)

An AI architecture that combines information retrieval with large language models to generate responses grounded in external knowledge.

Why Retrieval-Augmented Generation (RAG) Matters

A language model knows only what it was trained on, which excludes your prices, policies and product details, and it will sometimes answer confidently anyway. RAG fixes this by looking up the relevant source material first, so the answer is based on your content, and can cite it.

How Retrieval-Augmented Generation (RAG) Works

When a question arrives, the system searches a knowledge base for the most relevant passages, adds them to the prompt, and asks the model to answer using only that material. Updating the answer then means updating the documents, not retraining the model.

How SMPPCenter Uses This

SMPPCenter's AI Agent Builder works this way: agents answer from the knowledge base you provide, with guardrails and citations, and you can test them before they go live on WhatsApp, RCS, SMS, Telegram or your website.

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Related Terms

Vector Database LLM Prompt Engineering AI Agent

FAQ

Frequently Asked Questions

No. Fine-tuning changes the model itself using training data. RAG leaves the model unchanged and supplies relevant documents at question time, which is cheaper to maintain and easier to keep current.
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Client Feedback

What Our Clients Say

Our clients run regulated, high-volume messaging infrastructure and prefer not to be named publicly. These testimonials are shared with permission while keeping commercially sensitive details confidential.

The delivery reports and routing controls give us the visibility we were looking for. The system has integrated well with our internal applications.
Head of Technology, Enterprise Communications Company South Africa 4 operator routes Runs SMPP Server Client since 2021
Excellent documentation, responsive technical support, and an enterprise-grade platform that scales as our business grows.
Engineering Manager, SaaS Provider Canada 5 million notifications per month Runs Messaging Platform Client since 2022
The platform has been reliable for business-critical messaging. Multi-connection support and detailed logging have made daily operations much easier.
Infrastructure Manager, Enterprise Messaging Provider Russia 15 million messages monthly Runs SMPP Client Client since 2019
API integration was straightforward and the support team assisted us throughout deployment. We now manage multiple operator connections from a single platform.
Technical Director, SMS Aggregator UAE 12 SMPP connections Runs SMPP Client & Server Client since 2022

Names and company details are withheld at our clients' request. This is common among telecom providers, SMS aggregators, fintech companies, and enterprises that consider their messaging infrastructure commercially sensitive.

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