-- ScaleLabs, an AI implementation company serving infrastructure heavy industries, has released findings
from its 2026 client work. Across those engagements, the firm reports the clearest operational results
came from workflows that generate revenue, particularly quoting and estimating, rather than from the
administrative processes more commonly selected for automation.
The findings draw on implementation and discovery work with companies in construction,
manufacturing, distribution, steel, valve supply, equipment distribution and print manufacturing.
ScaleLabs describes them as observations from its own client base rather than a survey of the wider
market.
The firm attributes the difference to scale. Administrative automation is bounded by the hours it
removes, while a change in quoting accuracy or win rate is measured against everything the business
bids.
At one company in the steel business, quoting had gone six years without dedicated tooling. Quotes
were assembled by hand as emails or spreadsheets, with no quote catalog and no record of which bids
were won or lost. Close rate was estimated rather than measured, and the same inquiry was routinely
rebuilt for five separate distributors.
A company in the valve industry showed a different version of the same constraint. Its highest volume
line carried a two day quote turnaround, and roughly half of incoming orders required a product
configured from component inventory rather than pulled as a finished assembly. That determination
rests on expertise held by a few technicians.
The pattern appeared outside quoting as well. In heavy civil construction, estimators read hundreds of
pages of specifications by hand to locate cost relevant details. In equipment distribution, a team
manually reviewed roughly one hundred bid invitations a day. In print manufacturing, the purchase
order to invoice handoff required four separate manual entries.
ScaleLabs reports a common structure across the cases. Information arrives as unstructured documents,
only a few experienced employees can interpret it, and volume exceeds what those employees can
process. The firm characterises the result as a limit on how much work the business can pursue rather
than as a staffing cost.
In the implementations that gained adoption, the systems applied a confidence threshold rather than
attempting full automation. Requests the system resolved cleanly were drafted and returned
immediately, and anything below the threshold routed to the specialist who would have handled it, with
the relevant documents already assembled.
ScaleLabs also reports that operations leaders in these conversations often declined to evaluate the
projects on labour savings, redirecting discussion toward throughput, order accuracy and equipment
uptime. On that basis the firm has changed where its engagements begin, opening at the quote rather
than the back office.
“Most companies arrive expecting to automate the back office,” said Dallas Fontaine, founder of
ScaleLabs. “The work that changes their year is usually further forward, at the point where a document
turns into a price.”
Across its 2026 engagements, ScaleLabs found one constraint recurring in different forms. The decisions
that determine whether revenue is won depend on a small number of people reading documents, and
that group does not expand as quickly as the volume arriving. The firm reports that this constraint,
rather than administrative cost, is what its clients most often engaged it to address.
About the company: ScaleLabs builds AI enabled operational software for companies in construction, manufacturing, distribution and professional services. Further information is available at www.scalelabs.dev.
Contact Info:
Name: Dallas Fontaine
Email: Send Email
Organization: ScaleLabs
Website: https://www.scalelabs.dev/
Release ID: 89204079
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