AI-Powered Data Infrastructure Doubles Capacity and Fuels a $150M Raise

As the world’s largest bulk waste and sustainability operator, CheckSammy manages complex, high-volume operations across North America, serving enterprise customers that demand speed, transparency, and measurable sustainability outcomes.

By partnering with PrimeAI to build a modern data infrastructure and deploy custom AI/ML engines, CheckSammy doubled operational capacity without adding headcount, accelerated process automation, and strengthened the data story that supported a $150 million Series B raise and landing Amazon as a customer.

Data Infrastructure & AI Transformation: CheckSammy

100%

$150M

6

Increase in operational capacity with no additional headcount

Series B supported by AI-enabled data infrastructure

Months to ROI after AI/ML deployment

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The Challenge

CheckSammy’s nationwide operation relied on disparate, unconnected data sources and highly manual processes to manage jobs, vendors, pricing, and customer reporting. Operational data lived inside third-party SaaS tools with no unified, internal data infrastructure, making it difficult to standardize workflows, gain real-time visibility, or use data to drive optimization.

This fragmented environment limited how quickly teams could quote, route, and execute jobs at scale, and made it harder to deliver the granular sustainability and diversion analytics their enterprise customers expect. Without a central source of truth, leaders lacked the foundation needed to reliably apply advanced analytics and AI across the business.

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PrimeAI’s Solution

PrimeAI designed and implemented a new secure cloud environment as the backbone of CheckSammy’s data strategy, consolidating all critical data into a centralized model and database. This unified infrastructure integrated feeds from third-party SaaS platforms and operational systems, creating a single source of truth for jobs, routes, pricing, vendors, and sustainability outcomes.

On top of this new data layer, PrimeAI deployed a suite of AI/ML solutions tailored to CheckSammy’s growth and efficiency goals, enabling automated, data-driven decisions across the full job lifecycle. The architecture was built for scale and extensibility, allowing new AI use cases to be added quickly as the business and customer requirements evolve.

AI/ML Engines & Deployment

PrimeAI rapidly connected CheckSammy’s previously siloed data and implemented AI agents to automate and optimize key operational workflows end to end.

Deployed AI capabilities included:

  • Routing Optimization: Automatically selects optimal routes and job sequencing to increase daily throughput and reduce downtime.

  • Product Recommendations: Suggests the right sustainability and diversion services for each customer and material profile to maximize value and landfill diversion.

  • Pricing Optimization: Dynamically recommends price points that reflect cost, capacity, and market conditions while protecting margins.

  • Selection & Scoring: Scores and recommends the best haulers and facility partners based on performance, cost, geography, and sustainability outcomes.

  • Service Quoting: Automates quote generation using historical data, materials profiles, and AI-driven recommendations to respond faster and more accurately.

    The full solution was deployed over 8 months, with CheckSammy achieving ROI in just 6 months as automation and AI-driven decisions scaled across the network.

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By transforming fragmented data into an intelligent, automated operating system, PrimeAI enabled CheckSammy to move faster, execute more consistently, and position its technology and analytics as a core competitive advantage in the sustainability and bulk waste market.

The Results

With a modern data platform and targeted AI/ML engines in production, CheckSammy unlocked a 100% increase in operational capacity without adding headcount, allowing the company to process more jobs and serve more customers on the same staffing base.


The new AI-powered infrastructure strengthened CheckSammy’s ability to demonstrate scale, efficiency, and data-backed sustainability outcomes to investors, contributing to securing a $150 million Series B round and winning Amazon as a flagship customer.

Customer Success Stories

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    CheckSammy Pricing Optimization & Workforce Routing

    CheckSammy’s manual routing, scheduling, and non-optimized pricing limited capacity and profitability. With our scheduling, routing, and pricing optimization, they doubled operational and revenue capacity without adding headcount or infrastructure, supporting a $150M capital raise as revenue rose and costs fell.

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    Marmic Technician Scheduling & Routing

    Marmic struggled with inefficient manual technician scheduling & routing caused lost technician availability, overtime, and excessive travel costs. By using our workforce scheduling & routing  optimizer, they increased revenue 10%, cut overtime by 91%, and enabled 90 days of forward visibility instead of just 48 hours.

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    Aeroméxico Dynamic Pricing

    Aeroméxico’s rigid fare classes failed to reflect real customer price sensitivity across routes and seasons. Our dynamic pricing optimization algorithm improved offer relevance, demonstrated higher conversion, and lifted passenger revenue by approximately 1–3% on targeted flows.

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    Hotel Demand Forecasting & Pricing Optimization

    A Major Hotel Group struggled with static pricing and weak demand forecasts that left rooms underpriced or empty. After deploying our forecasting and dynamic pricing optimizers, this hotel group grew revenue by 2.7% and significantly increased adoption of advanced pricing tools among global hotel managers.

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    Forto Demand Planning & Pricing Optimization

    Freight forwarder Forto faced inaccurate container demand forecasts and suboptimal pricing that constrained margins and growth. By using our demand forecasting and dynamic pricing optimizers, they added over $1M in monthly revenue, enabling a profitable, scalable growth trajectory.

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