From weeks to hours.
How the Hälg team uses flint to take control of unstructured data and cut repetitive work — without sacrificing quality.
capture
«What used to take weeks, we now finish in just a few hours — with flint it's faster, more cost-efficient, and structured.»
A growing portfolio — but no structured foundation.
As part of Hälg Group with more than 1,200 employees, Hälg Facility Management AG manages buildings across Switzerland — from offices and logistics sites to public properties. Every new mandate started practically from zero: a site walk, Excel lists, photos on people's phones, all pieced together by hand.
With every additional mandate, effort and complexity grew faster than the team could scale. A comparable, portfolio-wide data foundation was missing — and with it, the basis for efficient operations and lifecycle management.
Inventory capture as the bottleneck.
Capturing a mid-sized building took more than five days — site walks, data entry, follow-ups, alignment with clients. Data quality and level of detail varied by inspector. There was no image trail, no versioning, no portfolio-wide comparability.
That capped the downstream value too: lifecycle planning, CAFM upkeep and customer reporting were all running on data that was already out of date the moment it was entered.
A walkthrough — not an inventory list.
Instead of translating site walks into Excel, the team now walks the building with a smartphone — video, audio, photo. flint extracts assets, components and conditions from the recording, maps everything to eBKP-H, BKP and DIN 276, and populates the building's Living Twin at the push of a button.
Every entry stays linked to its source material — image, video, document — and remains traceable at any time. From a single capture come defect reports, CAFM exports and portfolio reports.
- More than 5 days of effort per building for a manual inventory.
- Inconsistent and variable data quality across teams.
- Data not verifiable — no image trail, no history.
- Lots of repetitive work, high costs, hard to scale.
- Current, detailed asset and component data — with image, video and condition.
- Portfolio-wide standardised data quality and increased transparency.
- Faster mandate implementation; higher operating margins.
- New automation and AI use cases built on that foundation.
A data foundation you can build on.
What used to take several days now takes a few hours. Mandates can be implemented up to six times faster — at higher data quality and with a full image trail. Hälg gets back not just time, but the operating margin previously tied up in repetitive data work.
On top of that structured data foundation, the company is now building new automation and AI use cases — from proactive maintenance routing to portfolio-wide lifecycle planning.