12
Support Copilot & Autonomous Agents
Customer supportIn build- The problem
- Agents retrieve information across fragmented systems while the customer waits. Handling times run long, and the cost base of a large support organisation is enormous relative to the value of the average interaction.
- What it does
- Real-time call transcription, live retrieval across product knowledge, autonomous handling of first-line tickets, and partial automation of second-line workflows. Deployed as an in-call copilot with a queryable interface for instant lookup.
- What changes
- Average handle time falls, first-contact resolution rises, and the agent stops apologising for the search.
13
Support Email & Chat Agents
Customer supportIn build- The problem
- Staff read and answer email queries one at a time and field repeat questions on usage and purchasing. Round-the-clock coverage is impossible without night shifts nobody wants.
- What it does
- An agent pair handling email and chat at all hours, with a human-in-the-loop escalation path for anything it cannot close.
- What changes
- Hours per person per day return to the work that needs a person, and coverage extends to every hour without adding a shift.
14
Voice & Chat Service Agent
Customer supportIn build- The problem
- Service teams handle inquiries manually across voice and chat, with volume spiking hard in season. Staffing for the peak means overstaffing for the year.
- What it does
- Handles routine inquiries end to end across voice and chat, with human escalation for the rest. Designed to absorb seasonal volume without proportional staffing.
- What changes
- Faster resolution, lower handle time, and peak capacity that does not need to be hired for.
- Marxen note
- This is the agent where the Indic advantage is most visible. Voice systems built on foreign corpora fail on Indian accents, code-switching and the way people actually phrase a complaint. Ours are trained on speech our own network collected, in the field, in the conditions the agent will meet.
