How a RAG agent works
RAG stands for retrieval-augmented generation. A general AI model answers from what it learned in training, and it knows nothing about your business. A RAG agent first retrieves the relevant passages from the documents you connect, then uses an advanced language model to write the answer from them.
The result is an assistant that answers specific questions about your services, equipment and policies, and can show which document the answer came from.
What you can use a RAG agent for
Answers for technicians in the field
Techs can look up procedures, specs or equipment manuals from their phone instead of calling the office.
Faster employee onboarding
New hires get instant answers from your handbook and procedures while they learn the job.
Internal research
Staff find the right policy, warranty term or past answer in seconds instead of digging through folders.
Customer support
Put it on your website or support desk to answer customer questions from your own content.
Compliance and policies
Keep answers consistent with your compliance manuals and company policies.
Connects to the information you already have
We connect the agent securely to the sources you choose:
- PDFs and other documents
- Databases
- Notion workspaces
- Compliance manuals and company policies
What's included
Setting up every API, connecting your sources, the answer logic, testing and implementation are all part of the project.
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STEP 01
Gather your sources
We work out which documents and systems the agent should draw on, and who will be asking it questions.
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STEP 02
Build the agent
We set up the APIs, connect your sources and build the logic that finds the right passages and writes the answer.
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STEP 03
Test it
We test it with the real questions your team and customers ask, and refine it until the answers hold up.
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STEP 04
Launch
We implement it where it's needed: on your website, as an assistant for your team, or both.
Timeline: most RAG agents take 2–3 weeks from start to launch, depending on how many sources are involved and how complex the setup is. Every project is custom, so we scope it with you first.
FAQ
RAG Agents: common questions
What is a RAG agent?
RAG stands for retrieval-augmented generation. A RAG agent looks up the answer in your own material, such as PDFs, databases, Notion workspaces, or compliance manuals, before it responds, so its answers come from your sources rather than a general AI model's best guess.
How is a RAG agent different from ChatGPT?
A general AI chatbot answers from what it learned in training and knows nothing specific about your business. A RAG agent looks up the answer in your own documents before it replies, so it can answer questions about your services, procedures and policies.
What documents can a RAG agent use?
PDFs, databases, Notion workspaces, compliance manuals and other company material. We connect it to the sources you choose.
Can a RAG agent be used as a chatbot on my website?
Yes. We can put a RAG agent on your website so visitors get answers from your own content, or set it up as an internal assistant for your team.
How long does it take to build a RAG agent?
Most RAG agents take 2–3 weeks from start to launch, depending on how many sources are involved and how complex the setup is. That includes the APIs and logic, testing, and implementation.
How much does a RAG agent cost?
Every RAG agent is custom, so pricing depends on the project. Contact us and we'll scope it with you.
Related services
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Bridgewater, NJ 08807