AMELA | AIStaff CASE STUDY
Open the demo →
Construction & interiors × AI agents

Hand manual work to AI staff.
People focus on judgment.

Input, transcription, tabulation, matching and sorting — non-value-adding work is handed to AI staff (agents). Your on-site methods (paper, handwriting, MFP scanning) stay completely unchanged, reclaiming up to ~1,300 hours every year.

Try drawing takeoff → See the three AI staff
Drawings & design
90%
Drawing-takeoff effort cut
THE PROBLEM

"Work no human needs to do" was stealing our time

Off-the-shelf SaaS doesn't fit the field and never sticks — only expert-dependent manual work piles up.

129–193h
Manual entry of CS surveys

Each paper survey takes 15 minutes to hand-key, transcribe and tabulate into Excel. 514 a year — up to ~193 hours.

270h
Tallying thank-you cards

6,252 handwritten cards a year, visually checked line-by-line for duplicates, with points awarded and tallied by hand.

400–1,000h
Drawing takeoff

4–10 hours per project. Reading floors, rooms, areas and specs was slow and dependent on individual experts.

THE SOLUTION

A shared processing pipeline that leaves the field unchanged

Every AI staffer follows the same flow. Whatever the input format, automation runs on one common structure.

People step in only for the "exceptions"

Low-confidence reads are flagged automatically, so people review only a few percent — 10–20% at most. The rest is processed fully automatically.

A no-code × custom-build hybrid

Standard tasks are built fast in Dify (no-code). High-precision drawings, estimation logic and core-system integration come via custom development — so you can scale up in stages.

INTERACTIVE DEMO

Try the three AI staff

Click to experience the actual processing flow (mock data) right in your browser.

THE IMPACT

Turn reclaimed time into work that matters

1,300h
Hours saved per year (max)
90%
Drawing-takeoff time cut
97%
CS survey time cut
89%
Thank-you card time cut
Tech stack
Dify (LLM Orchestration) VLM / handwriting OCR RAG Python Teams / Excel integration