New York, USA, April 13th, 2026, FinanceWire
Monce’s next stage of growth depended not just on product capability, but on a cloud setup that could support faster and more efficient rollout, which is why the company worked with Automat-it on the AWS migration examined in this case study. The project focused on lowering infrastructure costs, improving deployment speed, and building a stronger operating foundation for enterprise expansion.
The platform Monce brought to industrial customers
Monce runs B2B commercial operations for major industrial groups across construction, glass manufacturing, surface treatment, aerospace, aluminum, and B2B distribution. Its proprietary multi-agent pipeline reads inbound orders across any format, extracts technical specifications, matches them against product catalogs with customer-specific pricing, and sends the result directly into ERP.
Built by operators who typed orders into AS400 for years, the platform is designed to reduce the manual burden of processing complex industrial orders. Monce says it cuts around 25 minutes of manual data entry per order to under 60 seconds of AI processing. It also reduces order errors from 8% to 12% to under 1% and lowers processing costs by 70%.
Those results helped the company expand from a single factory deployment to multiple enterprise accounts. As Monce grew across more sectors and customer environments, it needed infrastructure that could support enterprise expansion more effectively.
The infrastructure pressures that came with scale
The case study identifies three main constraints in Monce’s Azure environment.
The first was cost scaling faster than revenue. Azure’s container architecture maintained fixed compute costs regardless of processing volume. That meant infrastructure spending increased with each new client even during off-peak hours.
The second was AI inference economics. Monce’s multi-agent LLM pipeline reads full order conversations, performs proprietary catalog matching, applies customer-specific logic, and learns vocabulary and patterns. Running that on Azure AI services was more expensive than equivalent AWS alternatives.
The third was deployment overhead. Every new client required custom infrastructure configuration. That consumed engineering time that Monce wanted to direct toward product development and its expansion into revenue intelligence and multi-channel ordering.
For a company moving deeper into enterprise deployments, these issues became more significant. Infrastructure needed to support scale without creating the same level of repeated cost and manual effort.
The AWS migration delivered with Automat-it
Automat-it addressed those constraints by migrating Monce to AWS serverless architecture, including ECS on EC2. The solution delivered by Automat-it’s engineers and DevOps experts was based on Amazon ECS architecture and implemented through Terraform Infrastructure-as-code.
That allowed the same infrastructure to be created repeatedly while applying different configuration for each deployment. It gave Monce a more repeatable and standardized way to launch new client environments.
The case study also says Automat-it applied best practices developed across hundreds of AWS migrations completed for other startups. These included cost optimization through infrastructure design and FinOps expertise, along with scalability planning intended to support a secure and stable environment.
At the technical layer, Automat-it integrated Monce’s existing Firebase frontend with AWS ECS. The FastAPI Python application structure, which had been part of Monce’s monolithic backend before the migration, ran there. WebSocket connectivity between the frontend and backend was handled through an Application Load Balancer.
The results in cost, continuity, and rollout speed
The migration delivered a significant reduction in monthly infrastructure costs because elastic scaling eliminated fixed compute spend during off-peak hours. That improved the efficiency of Monce’s cloud spending as the company continued to add customers.
The case study also says the migration was completed with zero client downtime, allowing live industrial deployments to continue uninterrupted during the transition. Another major result was faster rollout. Terraform Infrastructure-as-code automated environment creation for each new factory, reducing new client deployment from days to minutes.
The case study also notes that infrastructure costs now scale with order volume rather than rising mainly because more client contracts have been added. That created a better relationship between actual demand and cloud spending.
How the migration supported enterprise expansion
This case study shows how enterprise growth can put pressure on infrastructure even when a product is already delivering strong results. Monce had built a platform that reduced manual work, improved order accuracy, and lowered processing costs for industrial customers. The AWS migration helped strengthen the infrastructure behind that platform so it could support a larger and more demanding customer base.
Automat-it’s work gave Monce lower infrastructure costs, faster deployment, and a more repeatable environment for new client rollouts. For a company expanding across enterprise accounts and industrial sectors, those changes created a stronger infrastructure base for continued growth.
About Automat-it
Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in startups. We deliver professional services to empower DevOps, FinOps, AI and Delivery teams to reduce costs, strengthen security, and simplify cloud operations. All so you can focus on scaling efficiently and confidently.
For 800+ customers, we have strengthened solutions and delivered business value and best practices across security, compliance, agentic AI, cloud architecture, cost optimization, and operational support.