---
title: "Wire your AI to a living data stream — AVCodex"
description: "Static knowledge bases start degrading the moment your source changes. Learn how AVCodex agents stay locked to live pricing, spec sheets, and room data through automated sync."
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Platform  4 min read May 12, 2026 

# Wire your AI to a living data stream

Live Data Sync — move from static knowledge bases to automated refetch.

[Download PDF](https://qtqplxgmqcdoglibodif.supabase.co/storage/v1/object/public/resources/live-data-sync.pdf)

The problem

## The hidden danger of static knowledge bases

Once a file is uploaded to a typical AI system, its accuracy starts degrading the moment the source changes. A pricing sheet exported on Monday is wrong by Wednesday. A spec sheet from last quarter quietly contradicts the manufacturer's current product page.

Your AI's memory fractures from reality — and you don't notice until a customer-facing answer is wrong.

How it works

## The automation pipeline

1.  01
    
    ### External data changes
    
    Dealer pricing sheet, manufacturer spec page (Crestron, QSC, Extron), or internal install standard gets updated at the source.
    
2.  02
    
    ### AVCodex refetches automatically
    
    On the schedule you set, the agent pulls the new version into its knowledge base — no manual re-upload required.
    
3.  03
    
    ### Agents answer with live data
    
    Sales, support, and install crews query the agent and get the current number, not last quarter's. "Updated price is $4,895." "Got it — thanks."
    

Setup

## Activate the live connection

1.  01
    
    ### Open the agent profile
    
    Settings menu in your AVCodex workspace.
    
2.  02
    
    ### Click Sources
    
    Where your knowledge base files live.
    
3.  03
    
    ### Find the file
    
    Spec sheet, pricing doc, install manual — any source you want kept current.
    
4.  04
    
    ### Enable Refetch
    
    Toggle on. Set frequency. Done.
    

Tuning the sync

## How often should you refetch?

There's no single right answer — match the cadence to how often the underlying source actually changes. A good baseline:

Cadence

Data volatility

Example source

When to use

Daily

High

Live dealer pricing, BOM spreadsheets

Anything client-facing with live numbers

Weekly

Medium

Manufacturer release notes, project status

Status that changes on a predictable cadence

Monthly

Low

Install standards, policy docs

Stable foundational guidelines

The outcome

## The continuous intelligence loop

1.  01
    
    ### Team edits source
    
    Pricing sheet or spec page is updated where it normally lives.
    
2.  02
    
    ### Sync engine catches it
    
    Refetch runs on the schedule you set.
    
3.  03
    
    ### User asks the agent
    
    Sales rep, support tech, or install crew member.
    
4.  04
    
    ### Agent answers fresh
    
    Always-current response — every time.
    

> You are no longer managing an AI's memory. You are wiring it into the systems you sell, install, and support.

## Want this in your inbox?

Download the PDF to share with your team, or take our 5-minute AI Readiness Assessment to see where to start.

[Download PDF](https://qtqplxgmqcdoglibodif.supabase.co/storage/v1/object/public/resources/live-data-sync.pdf)[Take the AI Assessment](/scorecard)

Keep reading

[

Programming

### Knowledge Sources vs. System Prompts

Stop defaulting to vectorized RAG for every dataset. Modern 1M+ token windows let you ingest entire chat logs, install standards, and spec libraries directly — and the synthesis quality is in a different league. A field guide to picking the right data layer for the job.

](/resources/knowledge-sources-vs-prompts)[

Strategy

### Your AI agents are guessing

Most AI agents shipped in our channel hallucinate in front of clients. Not because the models are bad — because the data layer is wrong. A field guide to diagnosing your architecture, matching it to intent, and becoming the AI authority in your market before IT or a younger integrator does.

](/resources/cohort-enrollment-storybrand)

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