Automate Customer Requests — from chaotic inbox to closed ticket
To automate customer requests means every inquiry — from a web form, email, chat or phone call — lands in one central queue, an AI classifies it by topic and urgency, routes it to the right team and creates a CRM record without anyone copy-pasting data. The solution replaces manual triage in Gmail and Excel with a full ticketing process with SLA, escalations and an audit trail. Roll-out in 4-6 weeks, from €3,400, no per-seat fees.
Symptoms that tell you it is costing money
When your team runs requests from a shared office@ inbox, the picture always looks the same. These are the signals we use to scope business process automation around support and sales.
- ✓Lost emails in the shared inbox — 8-15% of requests go unanswered for 48+ hours because four people watch one inbox and each assumes a colleague will reply.
- ✓No SLA, no visibility — you cannot answer "how many tickets did we close last week and who was the slowest" because there is nowhere to count it.
- ✓No triage by topic or urgency — a broken-delivery complaint, an invoice question and a B2B quote for €40,000 sit in the same folder, handled in arrival order.
- ✓Manual CRM data entry — an operator copies name, phone, company and issue from email into Excel or the CRM, makes 6-9 typos a day and burns 30-45 minutes per 20 requests.
- ✓Duplicate requests across channels — one customer writes by email, Viber and Facebook about the same issue; three operators give three different answers and your brand takes the hit.
- ✓No escalation on silence — a customer waits five days, no one is notified, and the complaint hits the owner directly at the next meeting.
If you recognize three or more of these, manual handling already costs more than the rollout. Move to a tiered path — ticketing form, AI classification, CRM auto-creation, then a full chatbot wired into your CRM system.
Who it works for
200-1,500 customer requests per month — quotes, warranty cases, complaints, parts orders. AI detects whether an email is a quote (to sales), a service case (to a technician) or accounting, opens a ticket with the right SLA. Cuts first-response time from 6-10 hours to under 30 minutes.
Inbound from the website, LinkedIn and demo forms. The system classifies the lead (cold/MQL/SQL), enriches it via firmographics API, assigns the rep and writes the CRM card in under 90 seconds. Result: 2-3x more leads answered in the first five minutes.
"Where is my order", "how do I return", "is this in stock" — the AI chatbot answers from live warehouse and courier APIs and only opens a ticket for true human cases. 65-75% of requests close without an agent.
How we build it — tiered, never big-bang
We do not drop a chatbot and call it done. We start with the cheapest layer and upgrade only where the logs justify it. This is the path we apply for every client, regardless of industry.
1. Ticketing form + single queue (week 1-2)
We replace the shared office@ inbox with a web form and a single ticket queue. Every request gets a unique ID, status and SLA timer. Emails to the existing address are converted into tickets via IMAP forwarding so customers see no change. This alone fixes 30-40% of lost requests.
2. AI classification and routing (week 2-3)
We add an LLM layer (GPT-4 or Claude) that reads each request and assigns category (sales, support, accounting, complaint), priority (P1-P4) and language. Rules route the ticket to the right team with the right SLA — 1 hour for P1, 24 hours for P3. Accuracy 92-96% after the first 200 training examples from your real mail.
3. Auto-create record in CRM (week 3-4)
For every ticket the system extracts name, phone, company, VAT ID and product from the email body and signature, validates them and creates or updates a CRM card — your own, HubSpot, Pipedrive, Salesforce. The full thread attaches to the card. End of manual copying and its errors.
4. AI chatbot for full self-service (week 4-6)
For the top 12-15 topics we ship a RAG chatbot over the website and knowledge base. It answers 60-75% of standard requests (order status, prices, stock, returns) and only opens a ticket when it does not know or the customer asks for a human.
5. SLA monitoring and escalations (ongoing)
We wire automatic escalations — if a P1 ticket is unpicked after 1 hour, a Telegram/Slack ping fires to the manager. A weekly email report: new tickets, first-response time, in-SLA percentage, top 5 topics, AI accuracy. You see the process in numbers, not feelings.
Why Saitami
You own the stack — your backend, your vector store, no per-seat fees. If support is the bottleneck, see AI chatbot for customer service; if email is the main channel, start with AI email automation.
Frequently asked questions
Where do I start — chatbot or ticketing?
Always with ticketing and a single queue with SLA. A chatbot in front of a chaotic inbox just speeds up the chaos. Once every request is a numbered ticket, we add AI classification, then auto-CRM, then full self-service chat. Each step is measured and pays back on its own.
How accurate is the AI classification?
After 150-250 training examples from your real mail we hit 92-96% accuracy on category and priority — enough for unattended routing. The 5% edge cases are flagged "needs review" and routed to a supervisor; their decision becomes a new training example.
Does it work with our existing CRM?
Almost always. We have ready integrations for HubSpot, Pipedrive, Salesforce, Zoho, Bitrix. For local or custom systems we build an API bridge. If you have no CRM yet, we ship a lightweight built-in module or a full CRM system as part of the project.
How much does it cost and what is included?
From €3,400 for ticketing form + single queue + AI classification + basic CRM integration. The full bundle with RAG chatbot, SLA dashboard and multi-channel intake (email, Viber, WhatsApp, Facebook) starts from €6,800. Operational cost: €40-€180/month for LLM tokens and hosting. No per-seat fees.
How fast do we see results?
The first effect — no more lost emails — shows in week 2 when the ticketing form goes live. A 60-75% drop in first-response time arrives by week 4-6 once AI classification is calibrated. The full 70%+ self-service from the chatbot is reached around month 3, after RAG covers your top 15 topics.
Ready to end the chaotic inbox?
Send a brief on your current setup — channels (email, form, phone), monthly volume and the top 5 request topics. Within 48 hours we deliver a phased rollout plan with price and ROI projection tailored to your case.
Request an automation plan →Related services: AI chatbot for customer service · AI email automation · CRM system