AI-Based Customer Support Automation
Chatbots and agents that actually resolve issues, not just deflect.
Why this service
In customer support, a large share of ticket content is repetitive. AI automation classifies, resolves routine items and routes complex ones to agents — faster and more accurately.
What you concretely get
Every phase of the engagement produces a written or systemic deliverable. No slide-deck show, no promised "later".
Discovery report
Current state, bottlenecks, baseline metrics and a concrete proposed focus. 12–18 pages, written.
Architecture diagram
Technical design: model choices, data flow, integration points, security. Readable and reviewable.
Working production system
Deployed system in your environment — not a demo. Source code and configurations are handed over.
Runbook and documentation
User guide, maintenance procedures, failure-mode checklist, escalation paths. Finnish/English.
Adoption programme
User training per role, internal "AI champion" coaching, 30/60/90-day milestones.
Outcome reports
Monthly: where metrics have moved against the baseline, what adjustments come next month.
How we measure success
Metrics are agreed at discovery and the baseline is captured before implementation. These are the numbers we discuss at the 30/60/90-day check-ins.
- First-response time
- Self-service resolution share (%)
- CSAT (customer satisfaction)
- Ticket volume per agent
- Escalation appropriateness rate
- Agent average handling time for complex cases
Use cases
Tier 1 chatbot
Answers routine questions 24/7 from your knowledge.
Ticket triage
Category, urgency and team auto-assigned.
Reply drafts
Agents get a ready draft to review and send.
Sentiment alerts
AI flags frustrated customers for escalation.
Multilingual support
Same knowledge across all support languages.
Self-service portal
AI helps customers find answers before opening a ticket.
Our delivery process
Discovery
We map the current state, processes and biggest productivity leaks.
Use case selection
We prioritise the highest-value, lowest-risk combinations.
Pilot
We build a working version in 4–6 weeks, with metrics.
Roll-out
We harden it for production and integrate the SaaS stack.
Training
Hands-on workshops and an internal champion for the team.
Optimisation
We measure, tune and scale — AI keeps living.
Technologies used
Frequently asked questions
A typical pilot completes in 4–6 weeks, with full production use in 2–3 months. We give a concrete timeline after the discovery call.
We design the architecture so your data stays under your control. We support self-hosted models and EU-region cloud, GDPR-aligned.
No. We build on top of your existing SaaS stack — we connect them, we don't replace them.
Adoption is part of every engagement. Without it, AI doesn't produce results — and that's already priced in.
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Learn more →Ready to get this in production?
We always start with a free 30-minute discovery call. No sales pressure.
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