trace @ gyandhan — 1,559 whatsapp groups, 15 minutes a day.
How an education-lending B2B ops team replaced 2.5 hours of daily ops load with a multi-agent system across 1,559 partner WhatsApp groups, at two cents a query.
GyanDhan runs an education lending platform with partners across India. Most of the partner communication happens on WhatsApp. Before TRACE, the ops team spent 2.5 hours a day handling queries across 1,559 active groups. After TRACE, it's 15 minutes.
the problem
Each partner is in a WhatsApp group. Each group can ping at any time with status queries, escalations, new lead registrations, duplicate-detection flags. Multiply by 1,559 groups and ops cost gets unsustainable.
Hiring more humans doesn't scale linearly — the cost per message becomes dominated by context-switching and routing, not by the actual answer.
the system we built
TRACE — Aminobots Assist under a GyanDhan brand — runs four agents in series. An Identifier classifies every message by intent and sentiment. A T0 rule layer pre-filters about half the traffic before any LLM is called — exact-match FAQ hits, intent-allow-list lookups, partner SLA template responses. Of what remains, a Support agent handles L1 resolution against the partner FAQ + CRM. An Expert agent handles edge cases — context that the L1 agent doesn't have. A HIL handoff routes the remainder to a human on the ops console.
Tiered LLM routing keeps cost down. About 80% of model calls go to the cheapest tier (DeepSeek). 15% to mid-tier (Qwen). 5% to a frontier model for edge cases. Average cost per query: $0.02.
↓
t0 rules (50% deflection)
↓
identifier → support → expert → hil
↓
crm + freshdesk + audit log
the outcomes
Daily ops load: 2.5 hours → 15 minutes. Automation rate: 99%+. Cost per query: $0.02. No additional ops hires required when partner-group count grew from 800 to 1,559 — the system absorbed the load.
We added 760 partner groups and didn't add a single ops hire. The team works less and the partners get answers faster. — Operations Lead
what's underneath
- Aminobots Assist (the multi-agent ops engine)
- T0 pre-filter rules engine (50% deflection)
- Tiered LLM routing (T1 OSS · T2 mid-cloud · T3 frontier)
- Freshdesk + CRM integration
- Blueprint System (AWS Bedrock target)
start with a diagnose.
If you're in the same shape — same task, same scale, same constraints — we can probably ship a working system in eight weeks. Two to three weeks to find out.
request diagnose