Idle machines do not grow EBITDA.
We connect pipeline, quoting, scheduling, and job visibility so demand reaches the floor and work keeps moving without the owner relaying every update.
Throughput moved first. EBITDA and value followed.
Lamb's Machine Works is in Memphis, Tennessee. It is proof that the method travels, not a claim of local NEPA work.
Sound familiar?
The machines have room, but the pipeline is inconsistent. Capacity cannot create EBITDA when qualified work never reaches the quote queue.
Sales knows what was promised and the floor knows what is running, but the handoff lives on whiteboards, paper, and conversations. The owner becomes the relay between both sides.
A rush job changes the schedule, but the effect on every downstream job is invisible. People stay busy while the wrong work waits and usable capacity sits idle.
Quoting, job status, and production history live in separate systems. Nobody has one reliable view of what is sold, what is ready, what is blocked, and what should run next.
Services that solve these problems.
CRM & Sales Pipeline Setup
Email threads, sticky notes, spreadsheets... when that person goes on vacation, nobody knows where things stand. Follow-ups get missed. Opportunities fall through the cracks.
Learn moreAI Lead Generation
Lead generation, automated follow-ups, and missed call text back... all the work that turns interest into appointments.
Learn moreWorkflow Automation
Workflow automation connects your systems so data flows between them without anyone touching it. When an invoice comes in, it gets logged. When a job status changes, the dashboard updates. When a report is due, it builds itself.
Learn moreReal-Time Business Dashboards
You don't actually know how your business is doing until someone sits down and puts the numbers together. By the time you see the data, it's already old.
Learn moreCustom Software Development
From scratch. Tailored to how your business actually runs. Not a template. Not a workaround. The real thing.
Learn moreFrequently asked questions
How can AI help a machine shop or small manufacturer?+
Start with the operating constraint, not AI. A shared pipeline can keep demand visible. Connected quoting and scheduling can keep sold work moving. Dashboards can give the owner oversight without making the owner the system. AI is useful only where it improves that flow with a defensible return.
Do we need to replace our existing shop management software?+
Not by default. We first determine whether the current system is missing a capability, poorly connected, or simply not being used consistently. The smallest useful intervention may be a process change, an integration, or a focused layer around the existing system.
Will this replace people on the floor?+
That is not the goal. Cutting people does not load a machine. The manufacturing case is more throughput through the same building: give the existing crew clearer information, reduce stalls, and make room for more work.
What manufacturing results can you verify?+
At Lamb's Machine Works in Memphis, a shared CRM and ERP replaced four whiteboards and one owner's memory as the operating system. The 18-person shop absorbed 50 additional weekly machinery repairs, launched a second shift, grew EBITDA 50%, and exited at a 65x return 14 months after acquisition. Systems were live four months before rapid growth. Those are client-approved facts, not projections for another shop.
What if we need to finish current work, not generate more leads?+
Then flow comes first. We map why work is backed up, improve visibility and handoffs, and hold pipeline work until the floor can absorb demand. The 70-20-10 method starts with the real constraint even when that costs us a lead-generation project.
The questions you should ask before a build.
Risk, security, adoption, capacity, and control should be answered before a proposal, not after a problem.
Is our data safe?+
The answer depends on the architecture. A browser-local tool can keep data on the device. A hosted workflow may send only defined fields to approved systems. We document the boundary and do not claim that nothing leaves your systems unless the implementation actually guarantees it.
Do you have SOC 2?+
Light in the Dark Analytics is not SOC 2 certified today. We will not imply otherwise. If your procurement policy requires it, we determine whether an architecture built entirely on vendors you already approve is acceptable. If it is not, we are not the right fit yet.
What if the project does not work?+
The scope, milestones, acceptance criteria, and engagement-specific terms are written down before work begins. We do not advertise a blanket outcome guarantee. If the operating math or adoption plan does not support the project, the right decision is not to start it.
Will this replace our people?+
That is not the manufacturing case. Cutting people does not load a machine. The goal is more throughput through the same building by giving the existing crew clearer information and removing stalls.
We need to finish current work, not generate more leads.+
Then flow comes first. We fix visibility, handoffs, and scheduling before adding demand. Pipeline work waits until the floor can absorb it. The 70-20-10 method follows the real constraint, even when that means delaying a service we could sell.
How long until we see a result?+
It depends on the constraint and adoption. Lamb's Machine Works went four months from systems-live to rapid growth. VetMyRoof went one month from kickoff to a live web app. Those are real timelines, not promises for a different operation.
We tried AI already and it went nowhere.+
That usually means the experiment started with an impressive use case instead of a costly operating problem. The 70-20-10 method puts most of the effort into proven core constraints, a smaller share into adjacent opportunities, and only 10% into bounded experiments.
Will we lose visibility into our own business?+
Systems that run without constant intervention should not run without oversight. A shared source of truth, clear ownership, and useful dashboards give the owner more visibility while removing the need to relay every update.
Find the constraint that is holding back throughput.
30 minutes. No pitch. We will trace how demand and work move, identify where the owner has to step in, and tell you whether there is a useful next step.