Solution
For pre-bid and estimation teams in construction and infrastructure: every conflict in a bid set found and evidenced before you price the job — trained on your experts, run in your private cloud.
The problem
A bid runs to thousands of pages once amendments, query answers, and correspondence are counted. Finding every conflict manually costs weeks of senior estimator time.
A completion date that differs between the bid and amendment three means costing a project on a wrong assumption — discovered after the price is committed.
The terms that drive costing are specific to the organization and even the division. Off-the-shelf contract tools do not know what counts as a conflict for you.
The product, not a promise
How it works
The bid and everything related — amendments, query answers, correspondence — load as one document set.
Models trained on the client's own experts read key terms the way the organization defines them.
Terms are checked across the whole set; conflicts and inconsistencies are flagged.
A single summary view lists every discrepancy, each linked to its source page.
Reviewers click through to the source and confirm or dismiss each flag.
Who it's for
Pre-bid analyst
Bid director
IT & security lead
The pre-bid team of a large construction conglomerate had a job that sounds simple and is not: find every place where a bid’s key terms disagree. A single bid runs to thousands of pages once you count the related documents — amendments, answers to bidder queries, ongoing correspondence. The terms that drive costing are specific to the organization and even to the division, so a generic contract tool does not know what to look for. And the documents are sensitive enough that they cannot leave the company’s environment.
Missing one discrepancy can mean pricing a project on a wrong assumption. Catching all of them manually means weeks of expert reading per bid.
Botminds deployed an instance in the client’s private cloud, so no document ever left their environment. In a few weeks, the platform was trained to read bid documents using knowledge captured directly from the client’s own subject matter experts — their terminology, their costing terms, their definition of what counts as a conflict.
From then on, each bid and its related documents load as one document set. The platform reads the whole set, compares key terms across every document, and produces an intelligent summary that surfaces the discrepancies immediately — one view instead of a thousand-page hunt.
A flagged discrepancy is only useful if a stakeholder can verify it fast. Every flag in the summary links back to the exact source passage, so verification is a click. The expert team stays in charge of the judgment calls: the platform does the reading, the flagging, and the evidence trail, and people decide what each conflict means for the bid.
Objections, answered
You verify it against the document itself: every flag links to the exact source passage, so confirming or dismissing a discrepancy is a click. The platform does the reading and the evidence trail; your expert team makes every call on what a conflict means for the bid.
That is how the reference deployment was built. Over a few weeks, the platform was trained on knowledge captured directly from the client's own subject matter experts — their terminology, their costing terms, their definition of what counts as a conflict. It reads bids the way your organization does.
In the reference deployment, an instance runs in the client's private cloud, so no document ever leaves their environment. The same model applies to your deployment: your documents, your infrastructure, your access controls.
Training on your SME knowledge took a few weeks in the reference deployment. From then on, each new bid set loads and is analyzed as a routine run — the setup cost is paid once, and every subsequent bid gets the full comparison automatically.
Watch the full set load, key terms compare across every document, and a real conflict surface with its source pages linked.
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