Unit cost
€0.30 – €0.90 per ticket handled
Methodology v1.0. Counted once per ticket handled regardless of which capability handled it.
Handle first-line customer support at scale — triage, resolve, escalate — across categories, channels, and languages.
Scoped like a hire, not a widget — one metered unit (tickets handled) regardless of which capability did the work, with full escalation transparency.
Response time
sub-minute
Accuracy target
90-97%
Escalation cap
under 60 seconds
Priced per business action
Range reflects variance in ticket complexity, knowledge-base depth, language mix, and escalation rate. Low end assumes stable KB, narrow category set, and majority English. High end assumes multilingual mix and higher escalation volume.
Unit cost
€0.30 – €0.90 per ticket handled
Methodology v1.0. Counted once per ticket handled regardless of which capability handled it.
Human-equivalent reference
Support Agent
EU mid-market
Benchmarked against EU mid-market SaaS and commerce support roles. Fully loaded includes base compensation, employer-side benefits and taxes, help-desk licences, team-lead management overhead, and first-year onboarding ramp.
Live calculator
Demo projection · Methodology v1.0
Capabilities
Activate the capabilities that match your largest repetitive categories. Start with the default set; expand as you prove each one. Metered unit is the role's — adding capabilities never changes the per-action price.
Classifies inbound tickets, identifies request patterns, routes exceptions with full context.
Read the capability
Answers recurring policy, product, and onboarding questions from approved knowledge.
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Handles repetitive plan, invoice, charge, and payment questions with clear escalation for edge cases.
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Resolves shipment and order-status requests automatically against order and carrier data.
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Handles return and refund workflows against policy rules with clear escalation thresholds.
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Handles repetitive support across multiple languages with approved localized knowledge.
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Detects sensitive or high-risk cases early and routes them to the right owner.
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Scenarios
Three business shapes we see most often. Costs are computed from €0.30 – €0.90 per ticket handled and a fully-loaded Support Agent benchmark.
Scenario 1 · SaaS · 40-80
2,000 tickets handled / month
Starting capabilities
Situation
A 40-person SaaS company with 2,000 monthly tickets usually runs with one senior support lead plus one junior handling queue volume. Around 60% of that volume is repetitive: plan questions, password resets, onboarding walkthroughs, basic integration help. The team already has a decent knowledge base, but it is scattered and nobody has time to reshape it.
Agent fit
Support Agent activates the three capabilities that match this company's repetitive core — triage, FAQ resolution, and billing questions — operating inside the existing help desk. Routing preserves team ownership of the 15% of tickets that still need judgement. Knowledge gaps surface automatically so the team finally gets to reshape the KB.
Outcome
Expected outcomes at this volume: 35-45% of tickets handled without human touch, first response under 2 minutes on the automated paths, queue load on the two humans roughly halved. Sentiment and CSAT hold because the escalation path stays clean and context-rich.
Scenario 2 · eCommerce · 80-200
8,000 tickets handled / month
Starting capabilities
Situation
A mid-market commerce brand with 8,000 monthly tickets typically runs 5-7 agents. Repetitive order-status, shipping, and refund inquiries dominate, especially through peak periods where volume can double in two weeks. Temporary agent hiring is slow and rarely matches quality.
Agent fit
Support Agent activates four capabilities — triage, order status, refunds, FAQ — all tied to real order and carrier data. During peaks, the agent absorbs the volume spike without the lead time of hiring seasonal staff. Complex refund disputes and fraud-flagged cases still route to humans with full context.
Outcome
Expected outcomes at this volume: 40-55% deflection on the repetitive core, peak-period backlog held flat rather than growing, existing humans reallocated to high-value cases, SLA compliance protected. Payback measured in weeks once peak hits.
Scenario 3 · Marketplaces · 200-500
20,000 tickets handled / month
Starting capabilities
Situation
A 300-person marketplace serving multiple EU languages handles 20,000 monthly tickets across 5-7 queues, with escalation obligations to operators on both sides of the marketplace. Language distribution creates staffing inefficiency: either the team over-hires to cover less-common languages or response quality suffers outside peak hours.
Agent fit
Support Agent runs full multilingual coverage, triage, and escalation routing. Routing respects the dual-sided operator obligations. Human team focus shifts to operator relationships and complex adjudication while sub-minute response is maintained across 30+ languages.
Outcome
Expected outcomes at this volume: 30-50% deflection across languages, 24/7 response coverage without night-shift staffing, consistent quality across languages tracked per language so drift never goes silent. Senior team focus returns to complex adjudication.
First response time
70-90% faster
Repetitive ticket deflection
30-55%
Coverage
24/7, sub-minute
Languages supported
30+
Correct-route rate on escalations
90-97%
Weekly maintenance
2-4 hours
Reviewable decisions
100% of actions logged with confidence band and routing rationale
How it works
Workflow summary
The agent classifies inbound tickets, identifies known request patterns, routes exceptions, and handles low-risk repetitive cases. Operator owns escalation policy and reviews weekly.
Exceptions
Low-confidence or policy-sensitive tickets are routed to a human queue with context attached. Escalation rules are explicit and reviewable.
When humans step in
Humans step in on low confidence, policy-sensitive cases, VIP customers, and anything outside activated capabilities.
Connected systems
Agent operates inside existing help desk + CRM + knowledge base. Writes resolutions and routing decisions back to source systems.
Data inputs
Ticket content, customer tier, account context (order or subscription state), help-center corpus, escalation history.
Decision logic
Uses issue classification, business rules, and customer context to decide whether to resolve, ask, or escalate. Every decision carries a confidence band.
Readiness
Clean support categories, help-center coverage for top issues, defined escalation paths, approved wording for sensitive topics.
Integrations
No new systems to learn. The role connects to the platforms your team already uses.
What "working" looks like
Deflection rate in target range
30-55%
Percentage of tickets handled by the agent without human touch within the stated impact range.
Source · Help desk reporting + agent execution log
First-response under threshold
under 2 minutes
Median time to first response on automated paths.
Source · Help desk reporting
Escalation accuracy above target
90-97%
Share of escalated tickets routed to the correct owner on the first hop.
Source · Internal QA review + client feedback loop
No CSAT regression vs baseline
CSAT parity within ±2 points
Customer satisfaction on agent-handled tickets meets or exceeds pre-deployment baseline for comparable categories.
Source · CSAT surveys
Governance & compliance
AI Act posture
Subject to transparency obligations: clear AI disclosure to end users where the agent interacts directly.
GDPR legal basis
Legitimate interest
DPIA
Recommended before deployment. We'll run one as part of the Launch Program.
Questions we get
It handles the job of a first-line support agent at scale: triage, FAQ resolution, billing questions, order status, refunds, multilingual, escalation routing. You activate the capabilities that match your business. It runs inside your existing help desk.
A chatbot answers questions. The Support Agent handles whole tickets end-to-end — classifying, resolving, escalating with full context, and updating your systems. It is scoped like a hire, not like a widget.
On low confidence, on policy-sensitive cases, on VIP or high-tier customers, and on anything outside the capabilities you have activated. Escalation rules are explicit and reviewable.
Pure usage: EUR 0.30-0.90 per ticket handled. A one-time launch fee covers capability activation, integration, and evaluator design. An optional operating retainer covers weekly optimization.
No. Start with the capabilities that cover your largest repetitive categories, prove the deflection, then activate more. Launch fee scales with the number of capabilities at go-live.
A supported help desk (Zendesk, Intercom, or similar), CRM access for customer context, and your knowledge base. Optional: order or subscription systems for commerce or SaaS context.
The agent operates inside your existing systems and writes back to them. Decisions and actions are logged with confidence bands and routing rationale. Data residency follows your help desk's region.
Yes. Usage scales linearly with volume and there is no hiring lead time. Most commerce clients activate Support Agent before peak precisely for this reason.
Chat opens with your role context already loaded. Scope a launch set of capabilities, review integrations, and get a timeline in one conversation.