Real Clients. Real AI. Real Growth.
See how The Data Sequence has helped clients across real estate, solar, e-commerce, and FMCG with AI agents, data mining, Meta ads, and automation — with measurable results and ROI.
Real Estate · Mumbai, IN
Aurora Realty Group
−68%
Cost per lead
4.3×
Site visits
₹2.1Cr
Pipeline added
21 days
To first ROI
Meta Ads
WhatsApp Automation
AI Agents
From cold leads to qualified site visits in 21 days.
◆ Challenge
Aurora was burning ad spend on broad Meta campaigns with a CPL of ₹1,840 and a 2% site-visit rate. Their sales team was buried in unqualified leads with no follow-up system.
◆ Solution
We deployed a hyper-segmented Meta Ads funnel with creative testing, layered an AI qualification agent on WhatsApp, and built an automated nurture sequence routed to the right RM.
◆ Execution
Built 14 ad variants across lookalike + interest stacks, trained the AI agent on Aurora’s project FAQs, and automated booking confirmations with calendar sync.
Stack
Meta Ads
WhatsApp Automation
AI Agents
"We went from chasing leads to closing them. The AI agent qualifies prospects better than half my team did manually."
— Rohan Mehta · Head of Sales, Aurora Realty
Data Mining
Meta Ads
AI Agents
Mining intent signals to find homeowners ready to install.
◆ Challenge
SunPath needed homeowners in tier-2 cities with rooftop potential and high electricity bills — a niche Meta’s interest targeting couldn’t reach reliably.
◆ Solution
We mined open data (DISCOM tariffs, satellite rooftop imagery, neighborhood income proxies) to build a custom audience, then layered AI-driven creative generation per cluster.
◆ Execution
Identified 47,000 high-intent households across 6 cities, served localized creatives in 3 languages, and qualified inbound leads via voice AI agent.
Stack
Python
OpenStreetMap
Meta CAPI
Claude
BigQuery
"They didn't just run ads — they engineered an audience that didn't exist on any platform."
— Priya Nair · Founder, SunPath Energy
Solar · Bengaluru, IN
SunPath Energy
11.2×
ROAS
−54%
CPL vs baseline
3,200+
Site surveys booked
₹38L
Spend, ₹4.2Cr revenue
Real Estate · Mumbai, IN
Aurora Realty Group
−68%
Cost per lead
4.3×
Site visits
₹2.1Cr
Pipeline added
21 days
To first ROI
Meta Ads
WhatsApp Automation
AI Agents
From cold leads to qualified site visits in 21 days.
◆ Challenge
Aurora was burning ad spend on broad Meta campaigns with a CPL of ₹1,840 and a 2% site-visit rate. Their sales team was buried in unqualified leads with no follow-up system.
◆ Solution
We deployed a hyper-segmented Meta Ads funnel with creative testing, layered an AI qualification agent on WhatsApp, and built an automated nurture sequence routed to the right RM.
◆ Execution
Built 14 ad variants across lookalike + interest stacks, trained the AI agent on Aurora’s project FAQs, and automated booking confirmations with calendar sync.
Stack
Meta Ads
WhatsApp Automation
AI Agents
"We went from chasing leads to closing them. The AI agent qualifies prospects better than half my team did manually."
— Rohan Mehta · Head of Sales, Aurora Realty
Solar · Bengaluru, IN
SunPath Energy
11.2×
ROAS
−54%
CPL vs baseline
3,200+
Site surveys booked
₹38L
Spend, ₹4.2Cr revenue
Data Mining
Meta Ads
AI Agents
Mining intent signals to find homeowners ready to install.
◆ Challenge
SunPath needed homeowners in tier-2 cities with rooftop potential and high electricity bills — a niche Meta’s interest targeting couldn’t reach reliably.
◆ Solution
We mined open data (DISCOM tariffs, satellite rooftop imagery, neighborhood income proxies) to build a custom audience, then layered AI-driven creative generation per cluster.
◆ Execution
Identified 47,000 high-intent households across 6 cities, served localized creatives in 3 languages, and qualified inbound leads via voice AI agent.
Stack
Python
OpenStreetMap
Meta CAPI
Claude
BigQuery
"They didn't just run ads — they engineered an audience that didn't exist on any platform."
— Priya Nair · Founder, SunPath Energy
FMCG · Pan-India
Harvest Foods
−92%
Order errors
+27%
Reorder frequency
₹6.8Cr
Revenue recovered
<8s
Spend, ₹4.2Cr revenueAvg order time
WhatsApp Automation
Data Mining
AI Agents
A WhatsApp distributor network that runs itself.
◆ Challenge
Harvest managed 1,800 distributors via spreadsheets and phone calls — order errors, stockouts, and missed reorders were costing 14% of monthly revenue.
◆ Solution
Built a WhatsApp-native ordering agent with inventory awareness, automated reorder nudges, and a back-office dashboard mining order patterns to forecast demand.
◆ Execution
Onboarded distributors in 4 languages over 6 weeks, trained the agent on SKU catalog + pricing tiers, and shipped a forecast model recalibrated weekly.
Stack
WhatsApp Cloud API
Supabase
GPT-4o
n8n
Metabase
"Our distributors love it. Orders happen at midnight, on Sundays, in Marathi. We just ship."
— Vikram Shah · COO, Harvest Foods
Real Estate · Mumbai, IN
Aurora Realty Group
−68%
Cost per lead
4.3×
Site visits
₹2.1Cr
Pipeline added
21 days
To first ROI
Meta Ads
WhatsApp Automation
AI Agents
From cold leads to qualified site visits in 21 days.
◆ Challenge
Aurora was burning ad spend on broad Meta campaigns with a CPL of ₹1,840 and a 2% site-visit rate. Their sales team was buried in unqualified leads with no follow-up system.
◆ Solution
We deployed a hyper-segmented Meta Ads funnel with creative testing, layered an AI qualification agent on WhatsApp, and built an automated nurture sequence routed to the right RM.
◆ Execution
Built 14 ad variants across lookalike + interest stacks, trained the AI agent on Aurora’s project FAQs, and automated booking confirmations with calendar sync.
Stack
Meta Ads
WhatsApp Automation
AI Agents
"We went from chasing leads to closing them. The AI agent qualifies prospects better than half my team did manually."
— Rohan Mehta · Head of Sales, Aurora Realty
E-commerce / Beauty · DTC, India
Nessa & Co.
3.7%
Conversion rate
−41%
Return rate
2.8×
AOV uplift
6.4×
Blended ROAS
Meta Ads
Web Dev
RAG
A storefront that sells, and a stylist that never sleeps.
◆ Challenge
Nessa’s Shopify store had a 1.1% conversion rate and high return rates due to shade mismatches. CAC was climbing on Meta with creative fatigue.
◆ Solution
Rebuilt the PDP with a RAG-powered shade advisor trained on 12,000 product reviews, paired with a fresh Meta creative engine producing 30 variants/week.
◆ Execution
Migrated storefront to a headless stack, indexed product + review corpus into a vector DB, deployed conversational shade-finder, and ran weekly creative sprints.
Stack
Next.js
Pinecone
GPT-4o
Meta Ads
Klaviyo
"Customers ask the AI questions they'd be embarrassed to ask a salesperson. Conversion speaks for itself."
— Anaya Kapoor · CEO, Nessa & Co.
E-commerce / Beauty · DTC, India
Nessa & Co.
3.7%
Conversion rate
−41%
Return rate
2.8×
AOV uplift
6.4×
Blended ROAS
Meta Ads
Web Dev
RAG
A storefront that sells, and a stylist that never sleeps.
◆ Challenge
Nessa’s Shopify store had a 1.1% conversion rate and high return rates due to shade mismatches. CAC was climbing on Meta with creative fatigue.
◆ Solution
Rebuilt the PDP with a RAG-powered shade advisor trained on 12,000 product reviews, paired with a fresh Meta creative engine producing 30 variants/week.
◆ Execution
Migrated storefront to a headless stack, indexed product + review corpus into a vector DB, deployed conversational shade-finder, and ran weekly creative sprints.
Stack
Next.js
Pinecone
GPT-4o
Meta Ads
Klaviyo
"Customers ask the AI questions they'd be embarrassed to ask a salesperson. Conversion speaks for itself."
— Anaya Kapoor · CEO, Nessa & Co.
◆ Your turn
Want results like these or your business?
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