Back to Work
Construction & HVAC|Detroit, MI

Automating Bid Ingestion for a Commercial HVAC & Plumbing Subcontractor

A Detroit-based HVAC and plumbing subcontractor with commercial clients across the Midwest was drowning in manual bid processing. We built an intelligent pipeline that transformed their estimating workflow.

Automating Bid Ingestion for a Commercial HVAC & Plumbing Subcontractor

Industry

Construction & HVAC

Location

Detroit, MI

Timeline

10 weeks

Challenge

60+ hours/week on manual bid processing, missing 60% of opportunities

Strategic Approach

Knight

Knight Labs' approach

Rook

End-to-end pipeline execution

Bishop

Precision document classification

Queen

Full-scope system integration

Client

Midwest Mechanical Services

Timeline

10 weeks

Focus Areas

Document ProcessingComputer VisionWorkflow AutomationSystem Integration

Tech Stack

PythonGPT-4 VisionLangChainAWS LambdaS3PostgreSQLFastAPI

The Challenge

The client's estimating team was spending 60+ hours per week manually reviewing incoming RFPs, construction drawings, and bid invitations from general contractors across Michigan, Ohio, Indiana, and Illinois. Each bid package contained hundreds of pages of architectural plans, mechanical specifications, and scope documents that needed to be parsed, categorized, and entered into their estimating software. The manual process meant they were only able to respond to roughly 40% of incoming bid opportunities, leaving significant revenue on the table. During peak season, estimators were burning out and making costly errors in scope interpretation that led to underbid projects.

The Solution

We designed and deployed an end-to-end bid ingestion pipeline that automatically receives bid invitations via email and FTP, extracts and classifies documents using computer vision and large language models, and structures the data for their estimating platform. The system parses architectural drawings to identify HVAC and plumbing scope, extracts key project details (square footage, building type, mechanical specifications), flags addenda and change orders, and routes categorized bid packages to the appropriate estimator based on project type and capacity. We integrated directly with their existing estimating software via API, eliminating manual data entry entirely.

The Result

Bid processing time dropped by 90%, from an average of 4 hours per bid package to under 25 minutes. The team went from responding to 40% of opportunities to over 85%, capturing an estimated $2.3M in previously missed commercial contracts in the first year. Estimator overtime was eliminated, and scope interpretation errors decreased by 75%.

90%

Bid Processing Time Reduced

85%

Bid Response Rate

$2.3M

Revenue Captured (Year 1)

75%

Scope Errors Reduced

Start a Project

Let's build something that actually moves your business forward.

Tell us about your challenge. We'll show you how AI can solve it.