Case StudyHVAC ManufacturingTech Support

How ACOND reduced support calls by 30% — without hiring

A Czech heat pump manufacturer was drowning in repetitive support calls. Junior technicians struggled to find answers. TechBuddy turned their existing documentation into an AI assistant that serves both their team and their customers.

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15–30%

Reduction in call duration, depending on technician seniority

~30%

Fewer inbound support calls thanks to a customer-facing chatbot

Faster onboarding for junior support operators during and after training

Location

Czech Republic / CEE

Industry

Heat Pump Manufacturing

Users

Tech Support Teams

Use case

Support + Customer Chatbot

The challenge

Hiring couldn't keep up. Knowledge wasn't scaling.

ACOND builds premium Czech-made heat pumps and prides itself on high customer satisfaction. But as their install base grew, so did the volume of support calls — and the complexity of keeping a team of technicians both knowledgeable and available.

The core problem wasn't product quality. It was a knowledge bottleneck: technical support required deep expertise, yet 70% of calls were about the same repetitive issues. And hiring experienced technicians was becoming harder by the month.

  • Difficulty hiring qualified tech support staff — a recurring bottleneck
  • Junior technicians slow to onboard due to the depth of product knowledge required
  • Repetitive calls consuming senior staff time that could be spent on complex issues
  • Answers scattered across PDFs, service manuals, old tickets, and tribal knowledge
  • No easy way for customers to self-serve before calling
The solution

One AI assistant. Two audiences. All their existing data.

TechBuddy connected ACOND's internal documentation, historical service tickets, client data, and training materials into a single AI assistant — deployed both internally for tech support and externally as a customer-facing chatbot.

Crucially, there was no need to rewrite documentation or create new content. TechBuddy ingested what already existed and made it instantly searchable and conversational.

Model-specific lookup

Technicians query by VIN, model number, or series — getting answers specific to the exact unit in front of them.

Cited answers

Every response references its source — manual page, ticket number, or training doc. Nothing is taken on faith.

Ticket intelligence

Historical service tickets feed the AI with real resolution know-how that never appears in official docs.

Issue pattern insights

Management can see which problems occur most often, across which series — turning support data into product intelligence.

The AI knows our products the way our best senior technician does — and it's available at 2am.

Head of Service, ACOND (placeholder)

How it works

From scattered documents to a single source of truth

1

Data ingestion

TechBuddy connects to ACOND's internal docs, service tickets, customer data, and training materials. No migration needed — it reads from existing sources.

2

AI processing

The TechBuddy engine builds a metadata layer that understands relationships between documents, models, error codes, and resolutions — even across unstructured files.

3

Dual deployment

Internal tech support gets a desktop interface; customers get a chatbot embedded in the service portal. Both run from the same knowledge base.

4

Continuous improvement

New tickets, firmware updates, and documentation are automatically synced. The assistant gets smarter with every resolved issue.

Results

Less time searching. More time solving.

Within the first months of deployment, ACOND saw measurable shifts across their support operation. Call duration dropped significantly — especially for junior technicians who previously needed to escalate or search manually before they could answer.

The customer-facing chatbot deflected roughly a third of incoming calls entirely. Customers could now find answers to common questions — how to reset the unit, error code explanations, filter replacement schedules — without ever picking up the phone.

For management, the side effect was unexpected but valuable: a clear view into which questions come up most often and for which product series, giving the product and documentation teams actionable input for the first time.

We weren't just solving today's support problem. We were building institutional knowledge we'll still be using in ten years.

Head of Service, ACOND (placeholder)

Want to see results like ACOND in your own manufacturing or service operation?

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How ACOND reduced support calls by 30% — without hiring