Choosing the best AI print estimating software

The demand for short-run, on-demand printing is surging as brands increasingly avoid large inventory commitments. According to analysis from Keypoint Intelligence, this fundamental market shift makes slow, manual quoting a significant competitive disadvantage. For print providers, the time it takes an experienced estimator to calculate costs, factor in machine time, and return a quote is now a critical bottleneck that directly impacts revenue. The best AI-powered print estimating software isn't just a faster calculator; it’s a strategic tool that dismantles this bottleneck and transforms your entire production workflow. This software is the central nervous system of a modern, efficient print factory, turning inquiries into profitable, production-ready jobs in seconds. For partners in the GelatoConnect network, harnessing this technology means being able to compete on speed and intelligence, not just price.

Main takeaways

Here’s what operations leaders need to know when evaluating AI-powered print estimating software in 2025:

• It's a workflow engine, not a calculator: The best software moves beyond price calculation. It integrates with your entire tech stack—from web-to-print storefronts to your MIS/ERP—to create a seamless, automated production plan from the moment a quote is requested.

• Data quality is non-negotiable: An AI model's accuracy is directly tied to the quality of the historical job data it’s trained on. A pre-implementation data cleansing project is essential for success.

• Integration is everything: Standalone tools create data silos. The most valuable solutions, like GelatoConnect’s AI Estimator, are built API-first to enable a “smart factory” ecosystem where information flows freely between systems.

• Speed translates to revenue: In a market demanding faster turnarounds, reducing quote turnaround time (QTAT) from hours to seconds directly increases your quote-to-order conversion rate and captures more jobs.

• The goal is hyper-automation: AI estimating is the first step. The ultimate objective is using this intelligence for automating the entire production process, including job routing, scheduling, and procurement.

• It empowers, not replaces, experts: AI handles the high volume of standard quotes, freeing up your experienced estimators to focus on complex, high-value projects that require their deep expertise.

Why traditional print estimating is breaking under pressure

The global commercial printing market is a massive, dynamic industry, projected to reach nearly $499.88 billion in 2024. Yet, many of the core processes that power this industry remain stubbornly manual, especially estimating. The traditional method—relying on a handful of skilled estimators with spreadsheets and decades of experience—is no longer sustainable.

This manual process is a classic example of a workflow bottleneck, a concept defined by the Theory of Constraints. Your entire plant's throughput is limited by its single slowest point, and for many print providers, that point is the quoting desk. While your presses may sit idle, potential jobs are stuck in an estimator’s queue, waiting for pricing. This leads to several critical business challenges:

• Lost opportunities: Customers demanding instant quotes will go to a competitor who can provide them.

• Inconsistent pricing: Quotes can vary between estimators, leading to inconsistent margins and customer confusion.

• Operational inefficiency: Estimators spend most of their time on repetitive, low-value quotes instead of complex, strategic projects.

• High labor costs: The process is entirely dependent on expensive, highly trained personnel.

This is where a solution like GelatoConnect fundamentally changes the operational calculus. By implementing a streamlined order intake process powered by AI, you remove the human delay. The system can process thousands of quote requests automatically, ensuring every potential job receives an instant, accurate, and profitable price, turning a critical bottleneck into a competitive advantage.

Criterion 1: Seamless API integration and ecosystem connectivity

According to the latest drupa global trends report, the future of print is the “smart factory,” an environment defined by hyper-automation and seamless data flow. In this model, the best AI-powered print estimating software acts as the brain, connecting disparate systems through robust APIs.

It is no longer enough for a quoting tool to exist in a silo. It must communicate bidirectionally with your entire technology stack:

• Web-to-print (W2P) portals: Instantly return prices to customers on your website.

• ERP/MIS systems: Automatically create job tickets, reserve materials, and update inventory in systems like Oracle NetSuite.

• Production scheduling software: Feed approved jobs directly into the production schedule, optimizing for machine availability and deadlines.

• Shipping & logistics APIs: Incorporate real-time shipping costs into the final quote using platforms like ShipEngine.

A true measure of a top-tier AI estimator is its ability to facilitate a complete guide to print workflow automation. GelatoConnect was designed with this API-first philosophy at its core, ensuring that data from the initial quote flows effortlessly through every stage of production without manual intervention.

Criterion 2: Data-driven accuracy beyond simple cost-plus

The old cost-plus model of estimating—materials + labor + markup = price—is a blunt instrument in today’s complex production environment. True profitability lies in understanding the nuanced costs of every job on every specific piece of equipment. As highlighted by Printing Impressions, the quality of your data is paramount for successful AI implementation.

The best AI estimating software leverages deep data analysis to generate truly intelligent quotes. It considers variables that are impossible for a human to calculate consistently in real-time:

• Historical production data: Actual run speeds, setup times, and waste percentages from thousands of previous jobs.

• Machine-specific performance: The unique cost profile and efficiency of each press and finishing machine in your plant.

• Substrate and consumable costs: Real-time material prices, factoring in trends like the fluctuating Producer Price Index for Pulp and Paper.

• Labor and overhead: Dynamic allocation of overhead costs based on current plant utilization.

This is the power behind the print industry’s first AI-powered quoting engine from GelatoConnect. It doesn’t guess; it learns from your unique operational fingerprint to produce quotes that are not only fast but also precisely optimized for maximum profitability. This granular approach also helps you better calculate and reduce the cost of raw materials by aligning quotes with the most cost-effective production paths.

Criterion 3: Transforming quotes into actionable production plans

A major theme at drupa 2024, noted by industry experts at WhatTheyThink, was the evolution of estimating software from a pricing tool to a production planning engine. A price is useless without a clear, efficient path to production. The best AI software generates not just a number, but a complete recipe for manufacturing the job.

This includes:

• Intelligent job routing: Automatically selecting the most cost-effective press and finishing line based on the job’s specifications and real-time machine availability.

• Imposition and layout planning: Generating optimized layouts to minimize substrate waste.

• Scheduling integration: Placing the job into the production queue with an accurate time estimate, contributing to a reliable on-time delivery (OTD) rate.

A fictional case study:

*** Print, a multi-site print partner in Germany, struggled with inconsistent quoting and inefficient capacity utilization across its three facilities. By implementing GelatoConnect, they leveraged GelatoConnect’s AI Estimator to standardize pricing instantly. More importantly, the system began automatically routing new orders to the most appropriate facility and press based on job specifications, cost profiles, and real-time capacity data. This shift to intelligent automation allowed them to increase their throughput by 15% without adding new equipment, truly automating the entire production process from quote to shipment.

A practical roadmap for deploying AI estimating software

Successfully implementing an AI-powered system requires a structured approach. It's not a simple plug-and-play solution but a strategic partnership between your team and your technology provider.

1. Data audit & cleansing: Begin by analyzing and standardizing historical job data. An AI is only as smart as the information it learns from.

2. System integration: Use APIs to connect the AI estimator to your core systems. Consider low-code platforms like n8n.io for building custom connections if needed.

3. Model training & calibration: Work closely with your software vendor to train the AI on your specific equipment, costs, and materials.

4. Pilot program: Run the AI estimator in parallel with human estimators. Validate its accuracy on live quotes to build trust and identify areas for refinement.

5. Phased rollout: Start by empowering teams with automated quotes for standard product types, gradually expanding as the model proves its reliability.

6. Continuous monitoring: Use analytics tools like Microsoft Power BI to track KPIs like quote turnaround time, conversion rate, and estimating accuracy, continuously feeding insights back to refine the AI model.

The key to navigating this process is choosing a partner, not just a vendor. The GelatoConnect team works alongside your operations staff throughout this journey, ensuring the technology is calibrated to your unique environment and that your team understands how AI and machine learning automate decisions in print.