01 — Problem
The friction
Support volume outpaces staffing and tone consistency suffers.
Supportly
Supportly keeps queues calm. It triages intent, drafts on-brand replies, and escalates the moments that need a human — so response time drops without losing empathy.
- First response
- −50%
- Deflection
- 35%
- Reopen rate
- −12%
Demo
See it in motion
A short walkthrough of the agent loop — from signal in to decision out.
Demo reel
Queue triage & reply draft
Overview
Case at a glance
Target users: Customer support leads, front-line agents, and CX ops.
02 — Solution
The approach
A support agent that classifies intent, drafts brand-safe replies grounded in your help center, and escalates high-stakes issues with full context.
03 — Value
Why it matters
Lower queue pressure with consistent tone and smarter escalation.
How it works
The agent loop
From raw signal to a decision Supportly can defend.
- 01
Classify
Reads the ticket, resolves the account, and assigns intent plus priority within seconds.
- 02
Retrieve
Finds the relevant help center article and the closest past resolution for this exact problem.
- 03
Draft
Writes a reply constrained by the tone guide and the policies that apply to this plan.
- 04
Route
Sends low-risk drafts to the agent queue and escalates churn, legal, or VIP signals first.
Capabilities
What Supportly actually does
Built for Customer support leads, front-line agents, and CX ops.
- 01
Intent triage
Routes billing, product, and account issues into the right lane instantly.
- 02
Tone-controlled drafts
Writes replies that match brand voice and policy constraints.
- 03
Knowledge grounding
Pulls answers from the help center and past resolutions with citations.
- 04
Critical escalation
Flags churn risk, legal threats, and VIP accounts for humans first.
Architecture
How the system thinks
Data flows left to right: sources feed the orchestrator, specialists reason in parallel, tools execute, and one artifact comes out.
Sources
- DataTicket stream
- DataHelp center
- DataResolution history
Orchestration
- OrchestratorSupport orchestrator
- LLMReasoning LLM
Specialists
- AgentTriage agent
- AgentReply agent
Tools & output
- ToolCRM lookup
- ToolMacros
- OutputDraft or escalation
- Data
- Orchestrator
- LLM
- Agent
- Tool
- Output
In action
A real exchange
An abbreviated conversation, close to what the agent actually returns.
Supportly Session active
- You
I was charged twice this month and nobody has replied in three days.
- Supportly
Classified as duplicate charge, priority raised for the three-day wait. I located both payments, drafted a reply with the refund amount and an apology in your tone guide, and escalated to a human because this is an annual enterprise account.
- You
Could it just refund automatically?
- Supportly
Refunds stay manual by design — the agent gets one click with amount and reason pre-filled, so money never moves without a person.
Design decisions
Trade-offs worth naming
The constraints that shaped the system — and what was deliberately left out.
- 01
Draft, do not send
Replies land in the agent queue rather than the customer inbox. Speed gains come from preparation, not from removing review.
- 02
Tone as a hard constraint
The brand voice guide is enforced at generation time, so quality does not depend on how each ticket was phrased.
- 03
Escalation rules are explicit
Churn risk, legal language, and VIP accounts route to humans through written rules, not model discretion.
Honest limits
Where it stops, where it goes
What the agent does not handle today, and what comes next.
Current limitations
- Answer quality is bounded by help center coverage.
- Voice and phone channels are unsupported.
- Refunds and account changes always require human action.
On the roadmap
- Voice call summarization
- Proactive messaging during outages
- Per-segment tone profiles
Stack
Technology
Nothing added without a concrete requirement behind it.
NuxtLangGraphOpenAIZendeskStripe