Making your tools talk to each other.
Your tools should be talking to each other. Stripe to Xero. CRM to email. Bank to accounting. We set them up so data flows reliably, nothing falls through the cracks, and you get told when something goes wrong instead of finding out three months later.
What we actually build.
Most integration projects fail the same way: they work on Tuesday and silently drop a record on Saturday at 3am. We build the version that doesn't. It checks itself, it tells you when something's wrong, and it lets you replay anything that failed — instead of leaving data missing.
What you get
A setup that doesn't double-up records when something goes wrong. A queue that catches failures, so you can replay them later. Alerts when things break. Clear logs so you can see what happened. A document for every connection explaining what data flows where. Old data loaded in where needed. And a 30-day window where we fix anything that comes up.
What you don't get
A Zapier flow that fires "most of the time". A pile of cron jobs no-one understands. A 200-row Google Sheet "the integration". An ESB. A service bus. Microservices. Anything more complex than the problem requires.
How we work is different.
The old way
- 😩Six-month roadmaps before any code ships
- 😟One enterprise platform pretending to do everything
- 😞Hand off the spec, disappear, invoice
- 😔Demos that don't survive contact with reality
- 🙁You depend on the agency, forever
The Intellilabs way
- ✨Safe pipelines with retries and replay
- 🚨Alerts when something quietly fails
- 🧯Failures land in a queue, not a void
- 📜Clear data contracts for every endpoint
- 🔑You own all the connectors and code
Common questions on integration builds.
Why not use Zapier or Make?
For simple, low-volume work — go for it. They're great tools and we use them ourselves. We build the proper version when you need guaranteed no duplicates, a safety net for failures, alerts when something breaks, automatic retries, and a record of what happened. The kind that doesn't quietly drop a record at 3am when an API has a wobble.idempotency keys, dead-letter queues, monitoring, retries with backoff, and audit logs. The kind of integration that doesn't quietly drop a record at 3am when an API blips.
How long does an integration take?
Most run 2 to 6 weeks. A simple two-system connection with good APIs can be 2 weeks. Connecting up several systems and loading historical data is 4 to 6 weeks. Fixed timeline after a scoping call.
Can you fix our existing flaky integration?
Often, yes. We start with a 1-week investigation — find the silent failures, the duplicate records, the missing data — then quote the fix. Sometimes the answer is a patch; sometimes it's a rebuild. Either way, you'll know which after a week.
What about webhooks vs polling?
Both, where appropriate. We use webhooks (push) where data needs to arrive quickly, and polling (pull) where the other system can't be trusted to deliver, and both where the truth is in two places. Every connection is set up so a duplicate message doesn't cause a double-write, and a restart doesn't replay everything.
How do you handle historical data?
Carefully. Loading historical data is usually a one-off script that streams data in batches, respects rate limits, removes duplicates, and produces a report at the end. We don't switch on live sync until the backfill is signed off.
What does running cost look like?
Most run for £40 to £150 a month regardless of how many records flow through. Higher-volume setups can use AWS. We pick what fits and put the running cost in the proposal up front. and cost £40–£150/month, regardless of throughput. Higher-volume jobs can use AWS Lambda + SQS or a Cloudflare Queue. We pick to fit and put the running cost in the proposal.
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Closing the books in days, not weeks.
A 60-person fintech was spending a full working week on month-end. We built software that matches up payments across the bank, Stripe, payroll and currency feeds — and gave the finance team 22 hours back every week.
Software that matches up payments across five systems.
Software that pulled in data from the bank, Stripe, expenses, payroll and Xero each day. It matched up payments automatically — exact, near-matches, and same-day ones. Anything that didn't match was sorted into a review queue for finance to clear. A dashboard showed what was closed and what was still open.
Read the full story →Got tools that won't talk to each other?
Tell us which ones, in roughly which directions. We'll come back within a working day with the shape of a fix.