The things people actually ask.

We work with you to find where the work is slowing your business down, decide what the right fix is, and help put it into practice.

Most of the job is diagnosis, and most of the diagnosis is listening. You know your business better than any consultant will after thirty minutes. What you may not have is someone asking the questions that make the bottleneck obvious, or someone who has seen the same shape of problem somewhere else. Usually you already suspect where the worst of it is. Often there is a second thing nobody had thought to question, because it has always been done that way.

The visible part is building an automation or an integration, but the part that determines whether it was worth doing is working out which process to change and whether it should be automated, redesigned, or removed. A consultant who arrives already knowing the answer is selling their tool, not solving your problem.

Cost is driven by how many systems have to talk to each other and how messy the data between them is, far more than by the number of steps or the size of the company.

Connecting two systems that both have good APIs is a small piece of work. Connecting two systems where one exports inconsistent CSVs and the other needs data in a format nobody documented is a much larger one, even though from the outside they look like the same job. This is why an honest estimate comes after a diagnostic conversation rather than off a price list.

Alongside the build there is a running cost: platform subscriptions, and model usage if AI is involved. We size that before building, because a design that works at one volume can stop making sense at ten times the volume.

Redesign first, almost always.

Automating a bad process makes a bad process run faster and more often, and it makes the bad process permanent, because now it is encoded in software nobody wants to touch. A surprising share of the work we are asked to automate should instead be deleted, merged into a neighbouring step, or handled by a setting in a tool you already pay for.

Whichever one the specific job needs, which is a question worth answering after the process is understood rather than before.

Zapier has the widest set of integrations and the gentlest learning curve, and it gets expensive as volume grows. Make handles branching and multi-step logic more comfortably. n8n can be self-hosted, which changes the cost profile at high volume and matters when data cannot leave your infrastructure.

For a lot of jobs the honest answer is none of them. A direct integration avoids a monthly bill and a layer of indirection. We have no house platform to sell you.

When the thing that makes your business work is the thing no product supports, and the workarounds cost more than the software saves.

If an off-the-shelf product covers most of what you need and the gap is preference, buy the product. Custom software carries a maintenance cost that a subscription externalises. Building wins when per-seat pricing means growth costs more than the work it does, when several overlapping tools plus a person are approximating one system, or when the workaround has become a documented internal procedure.

That is not what we build, and for a growing business it is usually the wrong goal.

The businesses we work with are not trying to shed people. They are trying to grow without every new customer creating proportionally more coordination work. The aim is capacity: the same team handling more volume, spending their time on the parts that need judgment rather than the parts that need retyping.

Yes. We are based in Los Angeles and work with businesses across the United States.

This work is mostly conversation, systems access, and iteration, all of which happen remotely without loss. Being local is convenient, not required.

You walk us through how the work actually gets done, and we ask a lot of questions. That is genuinely the whole call.

Thirty minutes, no charge, no preparation needed, though it helps to arrive with one process in mind that costs your team the most time. Expect to be asked how each step really runs: who touches it, where it waits, what the exceptions are, and which parts hold together only because a particular person remembers.

What it is not is a free set of recommendations. We are building an accurate picture of the work and naming where it is getting stuck, not solving it on the spot. Deciding what to change, what that is worth, and how to implement it takes research, and comes back afterwards as its own piece of work.

By the end of the call you will know whether there is something here worth doing together, and what the next step would involve.

A single well-defined automation is usually days to a few weeks. Work spanning several systems runs longer, mostly because of access and edge cases rather than build time.

The largest variable is rarely the code. It is how quickly credentials and system access arrive, and how many exceptions to the process surface once someone writes it down. Processes that "always work the same way" reliably turn out to have four special cases nobody had mentioned.

Growing businesses, from a handful of people to a few hundred. What matters is not headcount but whether growth is creating more coordination work instead of more capacity.

The work changes shape with size. Smaller companies usually need one bottleneck removed, with the result obvious within weeks. Mid-sized ones more often have several systems that each work fine individually, a process running across all of them, and nobody who owns the whole path end to end, so the job is as much mapping and ownership as it is building.

Earlier than that, the manual version is genuinely fine and we will say so. Much later, there is usually an internal team already doing this.