HJC turns a completed example into a repeatable plan-to-table workflow
HJC used a Bidlo agent to extract plan-sheet data, organize it by scope, and populate its preferred table. A process Kevin Lillard described as days of manual work on a comparable large project became an approximately five-minute workflow in the demonstration, according to Bidlo product owner Matt Wolfe.
Bidlo Team
Editorial team, Bidlo
HJC used a Bidlo agent to extract plan-sheet data, organize it by scope, and populate its preferred table. A process Kevin Lillard described as days of manual work on a comparable large project became an approximately five-minute workflow in the demonstration, according to Bidlo product owner Matt Wolfe.
The demonstration’s five-minute timing needs HJC confirmation; active interaction and total elapsed runtime may differ. The table-entry estimate is part of the manual baseline, not an additional saving.
HJC Farms, Inc. is a family-owned Texas TxDOT contractor founded in 1992. Its roadway work includes cable barrier installation and other highway-safety scopes.
Preparing those scopes for a bid requires finding the relevant details throughout a plan set and organizing them into information the team can review.
Kevin Lillard, HJC’s Director of Business Development, described a manual process of going into the plans, finding each location, bringing over the data, and entering it into a table.
On a large project, reading and interpreting the plans could take days. Table entry was another substantial part of that work.
HJC needed the information in its own table format so the team could work with it after extraction.
Austin Shirley used a Bidlo agent to extract the necessary cable-quantity data from the plan sheets into a workbook organized by scope. He then asked Bidlo Chat to fill HJC’s scope table from that workbook.
The team completed one run as an example. Austin used it to show the chat the structure the remaining runs should follow.
The agent gathers the required information from across the plan sheets and organizes it into a workbook by scope. The workbook provides the data; the completed run provides the pattern for HJC’s table.
Bidlo Chat uses those inputs to populate the remaining runs. HJC reviews the generated table before the information moves into downstream bid work.
That review surfaced an ordering issue in the demonstration: run labels appeared as 1, 10, and 11 before 2. The issue was recorded for a product fix. Checking the generated output remains part of the workflow.
HJC could move from filling the table run by run to providing an example and reviewing a generated result. The team’s preferred format remained the basis for the output.
The process was also saved for reuse. Bidlo supports running the same workflow concurrently across jobs in a letting, giving HJC a path to prepare several jobs at once. The evidence establishes that capability, rather than completed use across an entire HJC letting.
Matt Wolfe reported that Austin’s demonstrated workflow took about five minutes. Kevin’s days-long comparison concerned manually working through a large, dense plan set and organizing its information. The timing definition remains subject to HJC’s confirmation.
The narrower manual table-entry component was estimated at approximately two to four hours. Kevin’s account supports at least two hours; Matt supplied the four-hour upper end during draft review.
Austin described the connection between extraction and table preparation:
See how Bidlo can help extract scope information and prepare it in the format your estimating team wants to review.
