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2.0 Plugin

Smart Skill-Based Routing

Auto-assign tickets to the agent most likely to resolve them — based on resolution history, not a static skill matrix.

Static skill matrices age fast — by month six, half the rules are stale and tickets bounce 2-3 times before landing with the right agent. Smart Routing learns from your last 90 days of resolutions and ranks the best candidates per ticket: load-balanced, CSAT-weighted, with a 'why this agent' explanation on every routing decision your managers can audit.

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See it in action

The plugin, live in Freshdesk.

Most skill-based routing systems are spreadsheets pretending to be intelligence. Ours learns from your resolution history. We rank agents by recent first-response time, CSAT on similar tickets, and current load — then route in real time.

yourcompany.freshdesk.com/a/admin/routing
Routing decision · ticket #88421
live · 122 ms
01

Ticket arrives

Subject: 'Damaged pallet on shipment LH-2241'

02

Embed + similarity match

Compared against 90 days of resolutions · 7,412 candidates

03

Rank by CSAT × load × match

Top 3 candidates surfaced · scored 0.69 — 0.88

04

Aisha B. routed

Decision stored with 'why this agent' explanation

Candidate agents

Aisha B.routed
load 62%·CSAT 4.90.88
Marcus K.
load 81%·CSAT 4.60.74
Henrik L.
load 47%·CSAT 4.70.69

Real-deployment numbers

12,000

Tickets/month auto-routed at Northwind

−42%

Reassignment rate

+19%

First-touch resolution

Use cases & outcomes

When you'd use it. What you'd get.

01When

Your skill matrix is over 200 rows and stale

Outcome

Replace it with a learned ranker that updates from every resolved ticket. No more spreadsheet maintenance.

02When

Senior agents keep getting overloaded

Outcome

Load-aware ranking redistributes automatically. Newer agents see growth-stage tickets matched to their skill.

03When

Manager needs to defend a routing decision

Outcome

Every ticket carries match score, load context, and CSAT history. Click 'why this agent' to see the full reasoning.

04When

New-agent onboarding

Outcome

Engine ramps new agents gradually with tickets in their skill range. Onboarding goes from 14 days to under a week.

Problems we solve

The patterns we keep seeing.

  • Static skill matrices go stale within a quarter of being built

  • New agents get stuck in low-difficulty queues for weeks

  • Senior agents get overloaded with the same routing rules

  • Routing decisions are opaque — nobody knows why a ticket landed where it did

How it works

Three moving parts.

Step 01

Learns from your resolution history

Backfills 90 days of resolved tickets to build a baseline before going live.

Step 02

Routes on intake

New ticket arrives → similarity match → top-3 candidate agents → load-balanced final pick.

Step 03

Explains every decision

Each routed ticket carries an explanation tag your managers can audit.

Features

What's in the box.

  • Embedding-based similarity match against historical resolutions
  • Load-aware ranking (won't pile on overloaded agents)
  • CSAT-weighted routing
  • Per-queue policy overrides
  • Transparent 'why this agent' explanation on every ticket
  • Off-hours fallback rules
  • Live preview before going live in production

FAQ

Questions we get asked.

Direct answers. We'd rather you have the information than the sales pitch.

Stop waiting for Freshworks to ship it.

Tell us the workflow that's costing your team time. We'll have a working prototype in your hands inside two weeks.

founders@streamlineworks.io