Monday morning in the inside sales team of a heating and ventilation manufacturer: a GAEB BoQ from a building services (MEP) planner with 140 line items, three installers who want a heat pump for a multi-family building "real quick", and a distributor who sends a spare parts list as a photo. AI for heating and HVAC manufacturers starts exactly here: it reads all requests, matches standard line items to the catalog and separates them from the cases that need real sizing. That way, only what is truly engineering ends up with application engineering.

Key takeaways

• HVAC manufacturers receive very different requests: MEP BoQs, project requests via distribution and trade contractors, spare parts and accessory requests, orders.

• The bottleneck is usually not inside sales alone but application engineering, which also has to check simple line items.

• Many BoQ line items are standard (storage tanks, controls, accessories, piping), some need sizing (heat generators, air handling units, refrigeration systems).

• AI like Mercura matches the standard line items, checks specifications and flags sizing cases. It does not replace a heating load or cooling load calculation.

• Mercura works with several manufacturers in heating, ventilation and air conditioning, including REHAU as a public reference.

Which requests does the inside sales team of HVAC manufacturers handle?

The inside sales team of heating, ventilation and air conditioning manufacturers mainly handles four kinds of requests: bills of quantities from MEP planning, project requests from trade contractors or distributors, accessory and spare parts requests, and orders and call-offs. Each kind needs different knowledge and still often lands in the same inbox.

BoQs from MEP planning. In commercial projects, an MEP planning office puts the work out to tender, usually organized by trade. In cost planning under DIN 276, heating falls under cost group 420 (heat supply systems) and ventilation/air conditioning under 430 (air handling systems). The BoQs come as a GAEB file or PDF and contain many secondary line items in addition to the main unit.

Project requests via the three-tier distribution channel. Many heating manufacturers sell through distributors and trade contractors. The request then comes from the installer or the distributor, often informal: building type, heating load, desired system, date.

Accessories and spare parts. A list with old article numbers, a photo of the nameplate, an exploded view with circled parts. Small amounts, but a lot of searching.

Orders. Orders from ongoing projects, often with customer descriptions instead of your own article numbers.

What makes HVAC requests technically demanding?

HVAC requests are demanding because the products are systems: a heat generator needs a matching storage tank, hydraulics, controls and accessories, a ventilation unit needs matching air volumes, pressures and components. The right selection depends on attributes from the long text, not on an article number.

Typical attributes contained in a request that have to be checked:

On top of that comes the specified brand: MEP planners often name a specific manufacturer with "or equal". Anyone who is not the specified brand has to offer equivalent products with justification.

How does AI concretely help heating manufacturers in inside sales?

Artificial intelligence (AI) helps heating and HVAC manufacturers by reading in every request, matching standard line items directly to the catalog, checking attributes against the specification and flagging line items that need sizing for application engineering. Inside sales receives a prepared draft quote instead of a blank form.

Mercura, an AI software for quote and order automation in technical sales, works in these steps:

Prices and calculation stay in the ERP. Mercura is connected to systems such as SAP S/4HANA, SAP ECC, Microsoft Dynamics 365 or proALPHA; other systems via an API or SFTP. The connection runs only via routes your IT approves. Details on the Integrations page.

The public reference from building technology is REHAU: product suggestions for up to 98% of BoQ line items, a hit rate of up to 90% and up to 60% time savings on quotes. Martin Prigge from inside sales: "With Mercura's quoting AI, we save up to 60% of our time."

Why does this mainly relieve application engineering?

Application engineering is relieved because it only sees the line items that truly need technical assessment. The AI pre-matches standard accessories, storage tanks, control components and spare parts; the engineers check the heat generators, air handling units or refrigeration systems in a targeted way.

In many HVAC companies, application engineering is the bottleneck, because even simple BoQs go across its desk "just to be safe". When the AI already flags which line items are clear and which need sizing, the order of work changes: the difficult cases first, with the simple ones already prepared. More on this bottleneck in the article Relieving inside sales.

When is AI not the right solution for HVAC manufacturers?

AI is not the right solution for HVAC manufacturers if almost every request requires an individual sizing or engineering, for example with custom air handling units or large refrigeration systems. Then a sizing or configuration program is the more important building block, and AI only helps with reading the request.

To be clear about the boundaries:

• Heating load, cooling load and pipe network calculations remain the task of MEP planning and application engineering. Mercura does not calculate systems.

• Manufacturers' sizing programs are often indispensable for exact unit dimensioning. AI complements them but does not replace them.

• CPQ configurators are strong when products are put together according to fixed rules and the customer configures them themselves. The difference is explained in the article CPQ software or AI.

• Very low request volume: With only a few projects a month, rollout pays off less.

AI, on the other hand, fits well if your inside sales team handles many BoQs and project requests with a high share of standard and accessory line items and requests are left sitting today.

How quickly can this be rolled out?

A technical test on your own data is usually possible within two working days, and the first workflows usually run in less than four weeks. A training project beforehand is not needed, and incomplete product data is not an obstacle either, because Mercura also reads data sheets, technical documents and catalog texts.

Mercura reads common data formats such as BMEcat, DATANORM, ETIM and Open Masterdata. The data is stored in Europe, every customer has a separate tenant, and customer data does not train external AI models. Mercura is ISO/IEC 27001 certified.

Bring a real MEP BoQ or a real project request: in 30 minutes we show you how Mercura handles it in your process. Book a meeting

Conclusion

AI for heating and HVAC manufacturers pays off where inside sales handles many BoQs, project requests and accessory requests and application engineering becomes the bottleneck. The AI matches standard line items, checks attributes and flags what needs sizing. Calculation and approval stay with your specialists. That way more requests get answered without quality suffering. The Solutions for manufacturers page gives an overview.

Further reading

• Quotes and tenders: turn every request into a quote

• AI in Plumbing and HVAC Wholesale: Automate Quotes and Orders

• Pricing BoQs for Pipe Systems, Pumps and Valves

• Customer story: REHAU (building technology manufacturer)

Frequently asked questions

What does MEP planning mean? MEP planning is the planning of building services, which includes heating, ventilation, air conditioning, plumbing and electrical. It matters for manufacturers because it is where the BoQs and often the specified brands originate.

Can AI size a heat pump or a ventilation unit? No, Mercura matches line items to existing products and checks required attributes, but does not calculate a heating or cooling load. Line items that need sizing are flagged for application engineering.

How does the AI handle specified brands from other heating manufacturers? It suggests products from your catalog that meet the values in the long text and flags deviations. Your team decides whether a product is offered.

Does this also work for air conditioning manufacturers? Yes, the principle is the same: attributes such as cooling capacity, refrigerant and unit type are read from the request and compared with the catalog. System combinations that need sizing are flagged.

Which ERP systems are supported? Among others SAP S/4HANA, SAP ECC, SAP Business One, Microsoft Dynamics 365, Salesforce, proALPHA and UniTrade, others via an API or SFTP. More in the article SAP order entry with AI.

What happens with orders from projects? Mercura picks up orders from the shared inbox, matches customer descriptions and old article numbers and books the order into the ERP after review. More at Order processing.