We build integrations and automations for software companies and SMBs that want systems they can actually afford to run, maintain, and own.
These beliefs guide how we design, what we recommend, and — just as importantly — what we refuse to build. They're shaped by over a decade of real-world work, not tool demos or trend cycles.
If you're looking for absolutes or hype, this probably won't resonate. That's intentional.
Just because a workflow can be automated doesn't mean it should. Automation has a build cost, a maintenance cost, and ongoing cognitive overhead.
Tooling keeps getting easier — which changes the math — but it doesn't eliminate it. Good automation decisions are revisited over time. Bad ones are justified once and ignored.
Moving fast only helps after direction is right. AI and low-code tools don't fix poor decisions — they amplify them.
The most expensive work we see isn't slow execution. It's confident execution in the wrong direction.
Syncing data between systems is foundational, not the finish line. If your integration strategy stops at "the data is flowing," you're leaving value on the table.
Some of the most impactful integrations change how a product feels to use — through UI extensions, embedded workflows, or agent-based behavior — even when they're less efficient to build.
The real cost isn't who builds the system. It's whether the right decisions are made early — and whether someone understands the tradeoffs well enough to avoid expensive rewrites.
Deep expertise collapses decision time. That matters more than hourly rates.
AI can generate output. It can't own scope, judge correctness, or take responsibility for downstream impact.
When no one knows when to correct AI — or is willing to own the outcome — risk increases, not decreases.
Clean abstractions are appealing. Systems that can be understood, debugged, and safely changed months later are more valuable.
We prioritize clarity over cleverness — especially in integrations that sit between teams, tools, and incentives.
Every integration and automation increases surface area. Each one adds something that must be understood, monitored, and maintained.
Knowing where not to connect systems is a core part of expertise — not a lack of ambition.
Hidden complexity creates false confidence. We prefer designs that surface cost, ownership, and failure modes early — even when that makes decisions harder upfront.
If the tradeoffs aren't visible, they don't disappear. They just show up later, when they're more expensive.
These beliefs aren't positioning slogans. They're constraints on our work.
They guide:
If these resonate, we'll likely work well together. If they don't, that's a useful signal for both sides.
Let's discuss how we can help you build systems that last.
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