Integrations & Automation

Who it's for

Teams where systems technically "work" — but rely on manual steps, fragile integrations, or hidden dependencies to stay in sync. Especially where small failures cascade into larger issues, and where the integrations that hold everything together were written by someone who isn't around anymore.

What we actually build

A reliable interaction layer between systems — not just a collection of integrations. Designed so integrations don't silently break or depend on tribal knowledge to keep running.

• Systems exchanging data consistently One system's changes reach the others reliably — no drift, no "eventually correct" six hours later when someone notices.
• Reduced manual intervention The daily "fix-it-by-hand" routine either disappears or becomes an exception you notice, not a rule you depend on.
• Controlled, observable workflows Every step tracked — you can see what ran, what didn't, and where the data is in the flow at any given moment.
• Clear handling of failures and retries Retries that make sense, dead letters when they don't, and alerts when something actually needs a human. No silent drops.

What's included

• Integration mapping Identify how systems interact today — and where it breaks. Including the parts nobody realized were load-bearing.
• API integrations Reliable connections between systems using proper authentication, error handling, and versioning — not glued-together scripts that die on the next token rotation.
• Event-driven workflows Trigger-based actions across systems — not just scheduled scripts running every 10 minutes and hoping for the best.
• Background processing Jobs, queues, and async handling for reliability under load. Work that fails gets retried; work that can't be recovered gets surfaced.
• Error handling & retries What happens when things fail — defined up front, not discovered during an outage. Every failure mode has a planned response.
• Monitoring & visibility Basic insight into whether integrations are working or failing, in views your team actually checks — not buried in a console nobody opens.
• Documentation & handover Clear explanation of flows — not just the code. So the next person can reason about it without reverse-engineering three years of accumulated patches.

Typical problems we fix

Every setup has its own quirks, but these show up almost every time. Most of this goes unnoticed until something critical breaks.

• Systems "connected" but drifting out of sync The integration runs, but after a while the two sides disagree about the state of things. Nobody notices until a customer complaint arrives.
• Manual steps required to complete processes Someone has to log in, click a button, run a script, or copy data every day to keep things flowing.
• Fragile scripts breaking without warning A cron job that's been running for three years quietly stops working after a library update — and nobody knew it was critical.
• No visibility into failures When something breaks, the only signal is downstream weirdness. By the time you find the root cause, the data damage is already done.
• Duplicate or inconsistent data across systems Each system thinks it has the truth. Three systems, three versions of reality, and no clear way to reconcile them.
• Integrations that only one person understands Written by someone who left two years ago. Still running. Nobody wants to touch it.

What you walk away with

What you have at the end of the engagement:

• Systems that stay in sync reliably Data that changes in one place propagates to the others predictably, with clear expectations for timing and ordering.
• Fewer manual interventions The routine button-pushing shrinks or disappears entirely.
• A clear understanding of how systems interact You can draw the map of the flows without asking three different people what happens after step 4.
• Reduced risk of silent failures When something breaks, you know about it — before the business does.
• More predictable operations Integrations that behave like part of the system, not an afterthought bolted onto the side.

Where it makes sense, automation can be extended with AI — for summarization, routing, or decision support — but only where it adds real value over a straightforward rule or script. Most integrations don't need it; some benefit quietly.

Tools we work with

Tool choice depends on scale and complexity — the goal is reliability, not a specific platform. Common setups include:

Also custom API services · webhooks · message brokers