Helpdesk agent
From ticket noise to prioritised actions, with revenue at risk in plain euros.
At a glance#
The Helpdesk agent (Léa) plugs into your Odoo helpdesk module and continuously monitors three signals: SLA compliance, backlog ageing, and customer satisfaction. Every morning it surfaces the tickets that put revenue at risk and the support patterns that erode your margin.
It blends eight backend tools — health score, SLA breaches, backlog ageing, recurrent topics, problem products, costly customers, cost per ticket, and satisfaction — into one weekly brief in plain language.
What the agent detects#
- SLA breaches in progress with revenue at risk per customer (12-month CA)
- Backlog ageing segmented 0-7d / 7-14d / 14-30d / 30-60d / 60d+
- Recurrent topics with deflection potential to FAQ or articles
- Problem products generating disproportionate ticket volume vs sales
- Costly customers whose support cost outweighs the revenue they generate
- Cost per ticket broken down by team, type, agent and month
- Customer satisfaction via CSAT (Odoo
rating) or a proxy score (re-openings + irritation signals)
Detailed capabilities
59 ready-to-use actions across 18 categories. Identical to the prompt library available in the application.
Priorities & Brief
Examples:
- Monday top 5 (HITL) — H15 — 5 activities in the manager's calendar
- Daily brief — Daily condensed summary
- Weekly brief (HITL) — H14 — exec email recap
Health Score
Examples:
- Global score — 0-100 score with A-F grade
- Components detail — SLA, speed, CSAT, backlog, FCR, balance
- Score evolution — Trend and inflection points
SLA Compliance
Examples:
- SLA breaches — List sorted by revenue at risk
- Top revenue at risk — VIP customers in red zone
- SLA evolution — Compliance rate by month
Backlog & Support Debt
Examples:
- Backlog by age — 0-7d / 7-14d / 14-30d / 30-60d / 60d+
- Forgotten tickets — To handle or close
- Oldest tickets — Top 10 by age
Recurrent Topics & Root Cause
Examples:
- Top 10 topics — H4 — automatic clustering of subjects
- FAQ candidates — High volume, standardisable answer
- Deflection potential — Estimated support time savings
+ 2 more actions in this category
Products & Channels
Examples:
- Top 10 products — H5 — ranking by ticket volume
- Defect rate — Tickets ÷ sales per reference
- Pareto channels — H25 — disproportionately expensive channels
+ 1 more action in this category
Costly Customers
Examples:
- Costly customers — Support cost > customer margin
- Profitability ratio — Top loss-making customers
- VIP overview — Tickets, SLA and CSAT for key accounts
Cost & ROI
Examples:
- Cost per ticket — H7 — payroll ÷ ticket volume
- Cost by category — Cost distribution by topic and agent
- Financial ROI — H24 — observed retention 6-9 months
+ 1 more action in this category
Customer Satisfaction
Examples:
- Global CSAT — H8 — 30-day average satisfaction
- Dissatisfied list — Low CSAT or re-openings
- CSAT distribution — Rating histogram
Sentiment & Emotion
Examples:
- Ticket sentiment — H19 — Haiku batch + LRU cache
- Angry customers — Strong-emotion detection
- Emotionally urgent tickets — Emotional triage (≠ Odoo priority)
Resolution & FCR
Examples:
- Resolution speed — Health component (H1)
- FCR rate — H20 — global + per agent / team / type
- Worst non-FCR — Top 10 re-openings
Team Performance
Examples:
- Workload per agent — Open tickets per team member (H1)
- Agent scorecards — H22 — score 0-100 + recommendations
- Team balance — Workload standard deviation
+ 1 more action in this category
Churn Risk
Examples:
- At-risk customers — H18 — score 0-100 (volume/CSAT/speed/recency)
- Weak churn signals — Early detection
- VIP alert (HITL) — H13 — sales activities + exec email
Forecast & Capacity
Examples:
- 30-day volume forecast — H17 — Holt-Winters numpy (weekly seasonality)
- Volume peaks — Predicted spike detection
Customer Actions (HITL)
Examples:
- AI reply draft — H9 — Sonnet → internal mail.message
- Ticket escalation — H10 — priority=3 + manager activity
Tagging, KB & Templates (HITL)
Examples:
- Tag a cluster — H11 — tag + cross-link on all cluster tickets
- KB article — H12 — Sonnet → knowledge.article
- Reply templates — H26 — Sonnet → mail.template
Brief & Reports
Examples:
- Weekly brief (HITL) — H14 — exec email recap
- Monthly report — KPIs, trends and action plan
Multi-domain
Examples:
- Cash impact of late supplier — Crosses finance (cash) and purchasing (delays) in one query
- Stock out vs open quotes — Crosses inventory (availability) with sales (pipeline)
- Customer 360° view — Sales + finance + helpdesk for the same customer
+ 3 more actions in this category
Typical impact#
120,000 €
of customer revenue at risk identified within minutes
Order of magnitude varies by support volume. On demos:
- Services SMBs (10–50 tickets/week): €20,000–€80,000 customer revenue at risk
- Distribution / SaaS SMBs (50–200 tickets/week): €80,000–€300,000
- Mid-market (200+ tickets/week): often above €500,000
The agent does not invent risk: it surfaces revenue tied to customers whose SLAs are breached or whose satisfaction is collapsing.
Demo in four steps#
- 1
Connect to your Odoo
Secure authentication via dedicated API key. The agent detects whether the rating and sale modules are installed and adapts its outputs.
2 min
- 2
Initial helpdesk scan
The agent computes a 0–100 health score across 6 weighted components: SLA compliance, resolution speed, FCR, CSAT, backlog pressure, agent balance.
30 sec
- 3
Revenue-at-risk prioritisation
Each open ticket is scored by SLA breach severity x customer 12-month revenue. Top 10 tickets are surfaced with VIP and product context.
15 sec
- 4
Brief, recommendations, validation
You get a weekly executive brief with concrete actions (re-route, FAQ candidates, agent re-balancing). HITL: nothing is changed in Odoo without you.
your call
Required Odoo data#
Modules requis
- helpdeskhelpdesk
Modules optionnels
- ratingrating
- Ventessale
The agent detects optional modules at runtime. Without 'rating' it falls back on a proxy CSAT score (re-openings + client irritation). Without 'sale' it skips the customer revenue-at-risk views.
Supported versions: Odoo 15, 16, 17, 18, 19 (Community and Enterprise).
Human validation#
Agent
Agent prépare
Humain
Vous validez
Agent
Agent exécute
● Aucune action n'est envoyée vers votre Odoo sans votre validation explicite.
In practice, the Helpdesk agent can:
- Surface SLA-breach tickets with revenue at risk → you decide which one to escalate
- Suggest ticket re-routing between teams or agents → you validate before any change
- Propose FAQ / article candidates based on recurrent topics → your knowledge team writes
- Compute the cost per ticket by team / agent / month → input for your team plan
The agent never automatically:
- Closes or merges tickets
- Reassigns tickets without your confirmation
- Sends communications to customers
Frequently asked questions#
Do I need the Odoo rating module to use the agent?
No. If rating is installed, the agent uses real CSAT scores. Otherwise it computes a proxy satisfaction score from re-openings and client message irritation signals, and clearly flags the result as 'degraded'.
How is revenue-at-risk computed?
For each open or breached ticket, we look up the customer's 12-month revenue from your sale module (when available). The score blends SLA severity × revenue exposure, so a 2-hour breach on a €500K customer outranks a 3-day breach on a €1K customer.
Does the agent re-route tickets automatically?
Never. It proposes re-routings (between teams or agents) with the rationale, and you validate. Even at the highest plan tier, all ticket-state changes are HITL — no client communication or status change is performed without you.
Does my support data leave my Odoo?
The agent reads your data via the Odoo API. Analysis runs on our infrastructure hosted with Infomaniak in Belgium. No data is used to train a model. Each customer has an isolated tenant. More in our security page.
Can the agent draft a customer reply?
Reply drafting is on the roadmap and out of scope for the v1 Helpdesk agent. Today the agent focuses on prioritisation, root-cause patterns and team-level efficiency.
À lire ensuite
See this agent working on your Odoo data
30-minute live demo. Free. No commitment. € numbers visible from first connection.