40+ dealer labels refreshed weekly. Rep Copilot ranks every visit. Dealers order on WhatsApp in Hindi. Admins chat with their reports in plain English, all live in production today.
Orders, visits, payments, scans and WhatsApp messages across reps, dealers and influencers: one data layer, no silos.
Churn risk, next-order dates, visit priorities and label-driven alerts surface automatically, before they hit your P&L.
An NSM alert, a rep's pre-visit brief, a dealer's WhatsApp thread. Not another dashboard nobody opens.
Scoring weights rank today's beat: high-value, at-risk and overdue dealers surface first.
Before each visit, Copilot generates a plain-language brief from order history, labels and graph data.
Churn risk, dormant SKUs and visit gaps from the Labels Engine appear inline, no separate dashboard.
Graph data shows trajectory per dealer so reps lead with evidence, not guesswork.
from opening the beat list to a visit-ready brief, powered by /copilot APIs and live dealer graph data.
40+ rule-based labels (churn risk, dormant SKUs, visit/order patterns, scheme behaviour) batch-refreshed on cron.
High-risk dealers surface in NSM dashboards with order frequency, payment cycle and redemption signals.
Statistical next_order_date labels flag dealers due to reorder: reps and managers act before the gap widens.
Inactive dealers, high-visit-low-order and churn-risk nudges route to the right manager with a recommended action.
dealer labels computed from real order, visit, payment and scheme data, not a black-box ML slide deck.
Admins type plain English: NL→SQL runs against your warehouse and returns answers with conversation history.
Query results render as charts automatically, no BI tool export, no analyst queue.
DSR and CL/JP reports get Groq-powered executive summaries on download: the headline in 10 seconds.
Chat with any downloaded report: full ingest, then NL→MongoDB Q&A on the actual numbers inside.
for admin analytics and report Q&A, powered by /analytics and reporting-service AI modules.
Every product below maps to production code in ai_service and reporting-service, not roadmap slides.
Visit prioritization, LLM dealer briefs and graph context: ready before every beat.
40+ rule-based labels (churn risk, dormant SKUs, visit gaps) refreshed weekly on cron.
Order frequency, payment cycles and scheme behaviour flagged early, with NSM alerts and save playbooks.
Statistical next-order date and probability labels, so reps chase dealers before the reorder window closes.
WhatsApp voice & text in Hindi, Hinglish and English. 15+ intents: balance, invoice, schemes, place order, product search.
Dealer-scoped natural language → SQL on WhatsApp for open questions beyond fixed intents.
Admin NL→SQL with auto charts and conversation history: ask distribution questions in plain English.
AI summaries on DSR & CL/JP downloads plus report chat: Q&A on the actual report data.
Indian distribution runs on WhatsApp, so Nexxio made it a first-class channel, not a workaround. Dealers order, track and redeem without installing anything. No competitor has built this properly.

dealer labels refreshed weekly from real order, visit and payment data.
WhatsApp intents: voice, order, balance, schemes, invoices and more.
of AI: field copilot, labels & alerts, analytics & report intelligence.
Every system runs on the same distribution data layer you already use.