Attentive.ai

Shiva Dhawan is the Co-Founder and CEO of Attentive.ai, a company that is transforming how the construction industry operates through AI-powered preconstruction platforms.

A mechanical engineer turned entrepreneur, Shiva started Attentive.ai based on three core beliefs: AI will change industries, images have huge untapped potential, and solving the customer’s problem should always come first.

With Shiva leading the way, Attentive.ai has become one of the fastest-growing AI companies in construction technology. Its flagship platform, Beam AI, supports takeoff and estimating for over 1,200 customers, while its newest launch, BIM CoPilot, handles the entire BIM workflow, from multi-trade modeling and coordination to shop drawings. The company now has more than 900 team members and more than $12 million in annual revenue, helping contractors use AI to improve how they bid, build, and grow.

Before founding Attentive.ai, Shiva worked as a business consultant at Kearney and then later became CEO of a deep-tech services company, where he grew the business to $2 million in annual revenue. He earned his Mechanical Engineering degree from IIT Delhi and has built a career focused on technology, design, and industry transformation.

The Bid Window Forces the Wrong Trade-off

Ask most estimators to choose between a fast bid and a carefully checked one, and they will tell you the choice isn't really theirs. Time makes it for them.

Spend too long checking every quantity, and the bid window starts closing. Move too quickly and mistakes creep in. For years, the industry has worked around that tension as though it were simply part of estimating: more accuracy meant more time and more speed meant accepting more risk.

That assumption has shaped how firms staff estimating teams, how many opportunities they pursue and how much attention they can give each bid.

When measuring and counting take up most of the bid window, estimators are left with too little time to review the scope and pricing. Reducing that manual workload can give them more time to check the bid before it is due.

The Bottleneck was Never Judgment

On a manual takeoff, the same estimator may have to work through multiple drawing pages, measure walls, count fixtures, check schedules, trace revisions and make sure quantities match the scope. Some of that work needs experience and interpretation. Much of it is repetitive. The problem is that it all has to fit within the same deadline.

“A faster bid does not have to be a less accurate one. It can be a bid where experienced estimators have more time for the decisions that actually require their judgment.”

An estimator who spends six hours working through doors and windows has six fewer hours to think about labor productivity on a difficult site, check a scope gap, or call a subcontractor before locking in a number for the bid.

That workflow put speed and accuracy in competition: the longer measurement took, the less time remained to check and price the bid.

Consider what happens when an addendum arrives late in the bid window. Even a small drawing or scope change can send an estimator back through measurements and counts they have already completed. Checking how the addendum affects the bid still requires their attention, but repeating the measurement work uses up time before they can make that call.

Reducing that repetitive work leaves more of the bid window available to understand the change, check the affected scope and revise the price. That is where automated takeoff can make a difference.

What Automated Takeoff Actually Changes

The difference shows up early in the bid process. Traditionally, the estimator must establish quantities before much of the pricing can move forward, so scope checks, supplier conversations, risk review and pricing all compete for whatever time remains.

Automation gives the estimator a different starting point: instead of measuring every item from scratch, the estimator can start with quantities already extracted and focus on the parts of the drawings, scope, or project conditions that need a closer look.

Beam AI customers describe a massive change in their day-to-day work. Carolina Site Utilities reports saving 24 to 48 hours per takeoff, giving its team more time to refine proposals and work through pricing with vendors. Tremont HVAC reports saving 20 to 30 estimating hours a week and doubling its weekly bid volume. Its CEO, Tim Sughrue, says the team now has more time to review projects thoroughly because fewer hours go into scaling ductwork.

For these teams, faster takeoffs did more than shorten the bid process. They created more room for the review and pricing decisions that depend on an estimator's experience.

Beam AI supports takeoffs through two workflows. The DIY (do-it-yourself) workflow lets estimators generate AI-based takeoffs instantly, giving them a starting point, they can review against the drawings and adjust where project context calls for it. The DFY (done-for-you) workflow adds human QA for teams that want quantities reviewed before they come back to the estimating desk.

The estimator still makes the decisions that software cannot make on its own.

That matters because a rushed bid can go wrong in very different ways. A missed quantity may become obvious when material is ordered or work starts.

A poor pricing decision is harder to spot: an overlooked scope item, an unrealistic labor assumption, or incomplete subcontractor coverage may not show up until the job is underway.

Software can help with repetitive measurement, but the estimator still has to understand what those quantities mean for the job.

Why This Matters More as Margins Tighten

On a job with a thin margin, there is not much room for an estimating mistake.

That is why contractors have traditionally protected accuracy by adding review time, being selective about opportunities, or putting more estimators on a deadline when capacity allows. Those choices made sense when the surest way to tighten a bid was to give estimators more time.

Automation changes that calculation: the question becomes less about how quickly an estimator can count and more about where that estimator's experience matters most.

That might mean catching a scope condition hidden in the notes, challenging a labor assumption that looks too optimistic, checking a supplier number before the deadline, or taking another look at an area of the drawings where the design is unclear.

Those decisions can change a bid's outcome, and they're also the ones most likely to get rushed once the takeoff has already consumed most of the bid window.

None of this means every trade-off disappears. Drawings can still be incomplete, addenda still arrive late, and unusual projects still require extra review. What changes is the assumption that moving faster automatically means checking less.

For years, speed and accuracy competed because the same estimator had to fit measurement, review, and pricing into the same limited bid window. As repetitive measurement becomes less manual, review and pricing no longer have to fight for whatever time is left.

A faster bid does not have to be a less accurate one. It can be a bid where experienced estimators have more time for the decisions that actually require their judgment.