The client.
Construction has been slow to digitize, which is exactly why the recent shift has produced such large efficiency gains where it has landed.
Our client is a leader in construction AI technology, known for their work across the construction supply chain. They engaged us to automate the most laborious part of their customers’ workflow: proposal development.
The challenge.
The industry runs on time-consuming processes and labour-intensive collection of the data those processes need. Gathering material specifications alone can absorb days before a proposal is written.
The client’s brief was to accelerate proposal development, produce precise project records, and address the broader friction in the construction workflow around it - reducing both workforce requirements and delivery delays.
The crawler reads specs the way an estimator would - matching what a designer asked for against what a distributor can actually supply.
Specifications read automatically, matched to materials, and assembled into a proposal.
The solution.
Algoscale built an AI-driven SaaS platform in five parts.
AI-informed web crawler. A crawler using computer vision to read designers’ specifications, identify the best-matching construction materials, and hand distributors the strategic picture.
Centralized repository. A single store for construction datasheets, growing continuously as new data arrives.
OCR extraction. Automated data extraction that removed manual entry from storage and retrieval entirely.
Custom modules. Predefined formats and templates that standardize how a proposal is put together.
Workflow automation. APIs for customization, plus collaboration and version control, so a proposal has one current copy rather than five.
Business value delivered.
55-80% time savings. Proposal development compressed from days to a fraction of that.
5.6X return on investment. Measured against annual labour savings.
5X higher productivity. The same team covering considerably more work.
Lower operational cost. Manual data gathering removed from the critical path.
