Fig. 1

The factory floor has a data problem. We solve it.

Bloomfield builds custom AI software for manufacturers. Quoting tools, knowledge engines, production dashboards, and equipment intelligence built around your data, your workflows, and the way your team actually operates.

Why Bloomfield Exists

There are roughly 250,000 small and mid-size manufacturers in the United States. The vast majority run on the same fragile architecture: a handful of experienced people carrying decades of operational knowledge that lives nowhere except their heads. ERP databases hold partial records. Spreadsheets hold the rest. Critical process details get passed between shifts verbally, written on sticky notes, or stored in personal notebooks that go home every night. The systems never talk to each other. The people who hold it all together are aging out of the workforce.

This is a structural failure, and the consequences are measurable. An estimator with 30 years of experience carries thousands of past jobs, customer preferences, material behaviors, and margin histories in their memory. When that person retires, the shop loses the equivalent of an entire decision-making system overnight. The replacement starts from zero on every quote. Win rates drop. Lead times stretch. Margin erosion accelerates in ways that take months to show up on a P&L.

The technology to fix this exists today. Custom AI software built on a manufacturer's own data can connect ERP records, job histories, process specs, and floor-level knowledge into tools the team uses every day. Deploying these tools used to require seven-figure budgets and multi-year timelines. The economics shifted. We started Bloomfield because the builders who keep American industry running deserve tools that match the sophistication of what they produce.

How We Think

The floor comes before the code.

We walk your operation before we open a text editor. Who makes which decisions, what data feeds those decisions, where handoffs break, and what happens when the second shift runs a job the first shift quoted. Every tool we build originates from what we observe inside the operation, never from a product roadmap.

Your team shapes every tool we build.

The estimator, the production manager, the shop floor lead. They know where the process breaks and what a fix actually needs to look like. We learn their workflows, their language, their constraints. We iterate on working software until the tool fits the way they already think about the job.

Define the problem with physics-level precision.

Before we scope a single feature, we reduce the problem to its components. What data exists, where it lives, who needs it, and what decision it informs. Vague problem statements produce vague software. We get specific enough that the scope, the timeline, and the cost are all determined by the problem itself.

Working software at every checkpoint.

Each phase ends with a tool your team can use and evaluate. You see working software early, you test it against real jobs, and you tell us what needs to change before we move forward. No phase runs longer than eight weeks. No deliverable is abstract.

Who We Work With

Precision Machining Aerospace Defense Hydraulics Fluid Power Metal Fabrication CNC Manufacturing Medical Devices Industrial Components

We work with manufacturers running 20 to 500 employees and $5M to $200M in annual revenue. Job shops, mixed-mode operations, custom parts with variable processes. The common thread: the expertise that keeps the shop running lives in people, and the systems those people rely on were never designed to talk to each other.

The problems repeat across every sector we enter. Quoting depends on one or two estimators and grinds to a halt when they are unavailable. Institutional knowledge disappears with every retirement. Production status lives in three disconnected systems. Scheduling runs on gut feel because assembling the data to make a real decision takes longer than making the call without it.

How We Engage

We scope every engagement around the specific problem and the specific operation. Two paths, depending on where you are.

Track A

Advisory & Strategy

For operations that need clarity before committing to a build. We audit your workflows, inventory your data, and deliver a roadmap that tells you exactly what to build first and why.

AI readiness assessment across workflows
Workflow audit and bottleneck identification
Technology roadmap with build priorities
Team training and AI literacy sessions
Delivered in 2 to 4 weeks

Track B

Custom Build

For operations ready to deploy. We build custom AI software, integrate it with your existing systems, and deliver working tools in phased sprints your team evaluates against real jobs.

End-to-end development of custom AI software
Integration with existing ERP and data sources
Defined scope, timeline, and deliverable for every phase
Ongoing iteration, support, and refinement
First phase typically 6 to 8 weeks

Our Principles

The data already exists inside every manufacturer we have worked with. The failure is always in the system, never in the information.
If a tool cannot be explained in one sentence to the person who will use it every day, the scope is wrong.
The people running the floor know where the bottleneck is. Our job is to listen before we build.
Software that asks the operator to change how they work has already failed. The tool adapts to the operation.
Adoption is the only metric. A delivered tool that nobody uses is a delivered failure.
If a tool requires a manual, the interface is broken. We rebuild until it does not.