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BidUnity is vastly superior to the glass industry's present means of price discovery and estimating.

Unparalleled Bidding Efficiency

Glazing contractors are ready to abandon manual material quoting processes. Material suppliers have been searching for the means to deliver accurate pricing to their customers on demand. BidUnity's supplier API connects material suppliers to their customers in the cloud.

In contrast to software which captivates a buying audience, BidUnity is open and unbiased. Our only interest is in equally informing contractors. We do this by enabling simultaneous comparison of alternates. Every supplier can quote every project without imposing the burden of correspondence on their customer. Glazing contractors quickly discover the best value, significantly increasing their probability of winning the bid.

Software Made Simple

You'll probably never train another estimator without BidUnity. Just like real life, the estimating process is broken down into a series of logical steps. Each step has a help video. When users hover their mouse over terminology, BidUnity displays definitions and puts the information in context with the estimating process.

BidUnity's interfaces display relevant options based on what you are doing. We don't think adding extra things to click makes software better. For example, you can't send a proposal until it's created. Eliminating distraction enables smarter decision making.

We're Just Getting Started

BidUnity will extend the functionality of estimating software beyond its current definition. In our opinion, tracking time and progress will become an essential component of estimating software in the future; BidUnity's form of technology is required to get there.

Best practices dictate tracking the time to complete work and updating production rates for future bidding. The problem with best practices is that too many variables influence productivity.

One of our ambitions is to enable BidUnity to enhance the predictive accuracy of your labor estimates. It will take a lot of data and maybe even a few years before a machine can become helpful in this area, but we are building the technology to make estimating more accurate than humanly possible.