Caliente AI - 2026 Pricing, Features, Reviews & Alternatives

Caliente AI is an artificial intelligence powered copilot software designed to perform construction takeoff operations directly within established estimating platforms. The solution employs a model that interprets construction drawings and generates measurement calculations in the native environment of host applications. The software targets construction estimators and general and specialty contractors across trades such as concrete sitework drywall framing mechanical electrical roofing glazing and flooring. The system addresses professionals who mark up drawings and compute project costs based on measured quantities from plan sets.

The platform relies on natural language interaction to capture scope requirements in plain English while the model processes drawings and produces native editable markup objects. These objects include area polygons linear measurements count annotations and callouts that align with sheet scale and application standards. The model extracts existing markup objects and text layers through direct document data. This approach ensures measurement accuracy by avoiding reliance on visual images. A confirmation protocol prevents any destructive modifications without explicit approval.

A highlight function leverages the host application full text search to locate specified tags or text occurrences across drawing sets and applies native highlight markups at each instance. A read back feature extracts area and perimeter values from existing markups without altering original content. All additive markup operations are immediately reversible through a single step undo command.

Caliente AI integrates directly with Bluebeam Revu and will extend support to PlanSwift and Autodesk Revit in subsequent releases. The software does not require a plugin or additional interface panels and controls the host environment through existing workflows. File structures markup configurations and layer organizations remain unchanged. Autodesk Revit integration maps quantities to model elements and returns results as schedules on model based data. The architecture maintains native file formats and markup standards of each platform while enhancing estimator productivity.