Solution · 06
Customer Support Assistant
Help support teams answer faster and stay consistent.
The problem
Why this exists
Agents read long ticket histories, answers vary between people, and managers cannot review enough conversations.
- Agents spend time reading long ticket histories.
- Answers vary between team members.
- Knowledge is hard to find.
- Tickets are routed slowly.
- Managers cannot review enough conversations.
What it does
- Ticket summary, suggested category and priority
- Relevant knowledge search
- Draft response for the agent to approve
- Routing, escalation rules and quality checks
- Performance dashboard
How it works
The steps we run
- 01
Choose the ticket types
- 02
Connect approved support and knowledge data
- 03
Define tone, rules and escalation
- 04
Test drafts with agents
- 05
Launch gradually and monitor quality
Services combined
Built from our core capabilities
Measures of value
How we measure success
Lead industries
Where it fits best
See what customer support assistant would look like for you
Tell us the problem, the systems and the target. We come back within one business day with scope, first result and timing.
Other solutions
01
Web & Market Data Monitoring
Know when important prices, products, suppliers, sellers or rules change.
02
Model-Ready AI Training Data
Give your ML and LLM team clean, labeled and reliable data.
03
AI-Ready Business Data
Create one trusted data base for reporting, automation and AI.
04
Document Processing Automation
Process invoices, orders, contracts and forms with less typing.
FAQ
Customer Support Assistant questions, answered
How this solution scopes, integrates, and proves value.
It is a tool that summarizes tickets, suggests category and priority, searches your knowledge base, and drafts a response for an agent to approve, so support teams answer faster and more consistently. We connect your support and knowledge data, define tone and escalation rules, then test drafts with agents before a gradual launch. Managers get a dashboard to review quality. Most teams see faster handle times within the first month of use.
It can be set to draft-only with agent approval, or to send limited automatic replies for low-risk, well-defined cases, based on your policy and risk tolerance. Most clients start with drafts only, so agents stay in control while the assistant does the searching and summarizing. As trust builds and quality is proven with a test set, some clients expand automatic replies to a narrow set of routine questions.
We need access to your ticket history, your knowledge base, and a description of your tone and escalation rules, plus a small group of agents to test drafts before wider rollout. Historical tickets help us build the initial test set used to measure draft quality. The clearer your escalation rules are up front, the smoother the gradual launch across the wider team.
Pricing is based on ticket volume, the number of knowledge sources connected and the level of ongoing quality monitoring, quoted after reviewing your support volume. Most clients test drafts with a small group of agents within three to five weeks, then expand once acceptance rate and quality score are measured. This staged approach means you see real numbers before deciding to widen the rollout.
A generic AI chat plugin usually answers from general knowledge and does not connect to your ticket history or internal knowledge base. A customer support assistant is built from your own data, follows your tone and escalation rules, and keeps agents in the loop through draft approval rather than fully automatic replies. Value is tracked through first-response time, handle time, draft acceptance and escalation rate, not just usage numbers.
Next step
Discuss your use case
Bring one pain point, a data source, a workflow, a margin question. We'll come back with a focused assessment and a clear ROI hypothesis.