Agentic marketing OS · 2026

Your stores are full of signals.
Your marketing sees none of them.

AI agents that read every in-store conversation, stitch offline + online signals, and autonomously run lifecycle campaigns - with your CMO in the loop.

86%
of walk-ins never followed up - across every premium vertical
3-5x
rise in digital CAC since 2020 - while offline intent stays invisible
$200B+
global TAM across retail, auto, jewellery, BFSI, real estate and more
The agentic loop
Sense -> Decide -> Act -> Learn

Every store signal feeds a unified shopper profile. Agents execute autonomously. Reinforcement learning self-optimises every campaign variant, 24/7.

01 · Sense

Capture every signal

Audio + video AI, field staff, online browse, CRM history, marketplace data - all unified into ShopperDNA™

02 · Decide

Intent scoring

ShopperDNA™ scores each shopper 0-100 per session. Agents prioritise who to reach, on which channel, when.

03 · Act

Autonomous execution

SMS, WhatsApp, Email, Voice AI - triggered by real in-store intent, not static segments. CMO approves edge cases only.

04 · Learn

RL self-optimises

Reinforcement learning auto-selects winning variants across channels. Monday brief to CMO. Zero guesswork.

Three agents, one OS
Every layer of intelligence, coordinated

Each agent specialises. Together they close the full offline-to-online revenue loop - from the moment a shopper walks in, to attribution.

Advisor agent

Senses in-store. Coaches live.

Audio + Video AI · ShopperDNA™
  • Live pitch guidance via audio AI in real time
  • Smart nudges mid-conversation to handle objections
  • Auto lead creation from every walk-in
  • Intent scoring 0-100 per session, zero staff logging
Avani™ · Intelligence

Processes signals. Surfaces insights.

GenAI · Leader dashboard
  • GenAI tells leaders exactly what to fix for conversion & AOV
  • Cross-store analytics and performance attribution
  • Intelligent alerts on footfall drops, high-intent walk-outs
  • Tells each advisor how to improve their own sales
Vaani™ · Campaign

Executes. Self-optimises. Attributes.

GenAI + Reinforcement Learning
  • RL autonomously builds, tests and optimises every variant
  • Omnichannel: SMS · WhatsApp · Email · Voice AI calling
  • Online, offline and omnichannel customer segmentation
  • Closed-loop: store signal -> digital nurture -> attribution
The signal blindspot
Every vertical flies blind. We fix that.

Staff don't log what they should. Systems don't talk to each other. On-Ground.ai passively captures every interaction via audio + video AI - zero staff logging required.

Live & in pipeline
Consumer electronics
Store heads and finance desks mostly update near-purchase cases; field promoters capture partial demo context. Ideal state: passively capture walk-in, comparison, demo, and financing signals before any "hot lead" filtering.
Jewellery
Senior advisors close premium buyers, but trial, preference, and family-influence data from floor interactions is rarely structured. Ideal state: capture trial behavior and preference cues pre-negotiation to drive personalised follow-up.
Automobile
Showroom managers update escalated prospects; early walk-ins, event leads, and failed test-drive journeys stay untracked. Ideal state: capture every walk-in and test-drive attempt before escalation, not just closure-ready opportunities.
Real estate
Site-office teams classify only "hot" buyers while brokers influence attribution and visibility of visits. Ideal state: capture raw site-visit conversations before advisor/broker classification to prevent ghost leads and pipeline distortion.
BFSI
Desk officers and agents tend to hide rejected or low-probability inquiries, making funnel quality look better than reality. Ideal state: capture all inquiries, pre-qualification outcomes, and advisory journey steps including rejects.
Healthcare & education
Counselors and specialists record outcomes, but emotional hesitation, parent influence, and multi-visit drop-off reasons get lost across handoffs. Ideal state: capture full decision lifecycle with emotion and continuity signals across each touchpoint.

"This is the first time in 15 years we can see what's actually happening on the floor in real-time. We can finally identify where intent drops, coach teams at the right moment, and run follow-ups based on real conversations instead of assumptions."

- Head of Retail Ops, live customer
The moat
Built from data, depth and daily dependency

Competitors own one layer. On-Ground.ai is the only full-funnel intelligence OS. Premium brands currently pay five vendors - none can tell them what happened in-store.

01

Audio + video AI fusion

Three simultaneous data streams. No competitor matches this multi-modal depth - trained on 100K+ minutes per month across India's 50+ languages.

02

Real-time coaching and alerts

Live nudge at the exact point of decision. Every interaction trains the RL model - creating a data flywheel that compounds with every store, every day.

03

Full-funnel CAC optimisation

Pre-visit -> in-store -> post-visit nurture -> attribution. One platform. Incumbents (MoEngage, CleverTap, WebEngage) are built for digital-first - in-store signals remain invisible to them, always.

04

Agentic RL A/B testing

Zero solutions autonomously build, test and optimise customer relationships across offline-to-online journeys. Reinforcement learning closes that gap - 15-30% uplift that static campaigns leave on the table.

on-ground.ai · Confidential · 2026 Rashmi Sehgal, CEO · Mukunda Dwarkanath, CTO LinkedIn logo LinkedIn