agentic business use cases

Stop reading dashboards.
Start asking your business.

agucsagentic business use cases

An AI agent wired into your Shopify orders, Meta & Google Ads, shipment tracking and WhatsApp. You ask in plain English — it investigates, decides, and acts. No SQL. No dashboards. Just answers.

Enroll me for a demo scroll — watch the agent work

Four things you'd normally do yourself.
Now you just say them.

Every query below is real product behaviour. As each one lights up, the agent runs it — connecting to your stack, reasoning through the data, and finishing the job.

use case 01 · scheduled intelligence
you “Can you schedule a message every morning at 10 which gives me insights about my Meta and Google ads — ROAS, non-performing ads, amount spent yesterday.”
aagucs agentworking
  1. Connecting to Meta Ads & Google Ads accounts
  2. Defining briefing: ROAS · yesterday's spend · underperformers
  3. Creating recurring job — daily, 10:00 AM IST
  4. Sending today's briefing as a preview
Daily ads briefing scheduled · 10:00 AM
Spent yesterday
₹18,420
Blended ROAS
2.8×▲ 0.3
Meta / Google
₹12.8k / ₹5.6k
Non-performing ads — flagged below break-even
  • Carousel — Bestsellers v2ROAS 0.9× · ₹2,140 spent
  • Static — Sale 20% (broad)ROAS 1.1× · ₹1,680 spent
  • Reel — Hook B (Tier-2)0 purchases · ₹940 spent
use case 02 · autonomous customer ops
you “Can you send the customer a message about the reason for return when they initiate a return for a product?”
aagucs agentworking
  1. Watching Shopify for return-initiated events
  2. Return detected — order #18243, Priya S.
  3. Sending WhatsApp message to capture reason
  4. Logging reply against the order & product
WhatsApp · sent automatically live
Outcome logged

Reply received: “1 — size too small.” Tagged on the order, added to the product's return-reason history, and a size-chart review flag raised — this product's size-related returns just crossed 20%.

use case 03 · deep investigation
you “Why is my ROAS dropping? Can you dig deep and find out?”
aagucs agentworking
  1. Pulling 30 days of Meta + Google performance
  2. Splitting ROAS by campaign, ad set and region
  3. Checking CPM, CTR and conversion-rate trends
  4. Cross-checking Shopify inventory & landing pages
  5. Isolating the root cause
Diagnosis root cause found
ROAS · 12 days
3.1× → 1.9×▼ 39%
CTR
stable
CPM
+6%

Your ads are fine — your inventory isn't. Conversion rate on the top ad set's landing product fell 41% after its two best-selling sizes went out of stock on June 2. Traffic kept arriving; it just couldn't buy. CTR and CPM barely moved, ruling out creative fatigue and auction pressure.
→ Fix: restock sizes 38–39, or point the ad set to an in-stock product. Draft swap ready.

use case 04 · campaign on command
you “Can you send a marketing WhatsApp message to shoppers who shopped during the festive season last year?”
aagucs agentworking
  1. Querying Shopify: orders between Oct 18 – Nov 15 last year
  2. Building audience · removing opt-outs & recent buyers
  3. Drafting WhatsApp template for approval
  4. Queuing send for tonight, 7:00 PM
Audience built 1,284 customers

Festive-season buyers from last year, minus 96 opt-outs and 142 who purchased in the last 30 days. Average past order value: ₹3,240.

WhatsApp template · ready to send queued · 7:00 PM
Plugged into your stack
ShopifyMeta AdsGoogle AdsWhatsApp BusinessShipment APIsRazorpay

Every question above ran itself.
Imagine your whole business doing that.

Real-time shipment status, true ROAS with RTO deduction, automated inventory and customer ops — driven by plain English.

Enroll me for a demo