Integration Services with Temporal

Why Integration Services with Temporal

Durable Temporal integration that survives failure.

Hours of manual re-keying gone, and two systems that finally agree after every transaction, even when one of them was down at the time. That is what durable execution buys you. Temporal records each step of an integration as it runs, so when a payment posts but the ledger update times out, the workflow picks up where it stopped instead of leaving a half-finished mess for someone to chase on Monday. We build on it when a partly completed transaction across your systems is expensive to untangle by hand. When a managed queue or a scheduled job would do the same work for less, we tell you that first.

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Capabilities

What we build on Temporal

End-to-end transaction workflows

Multi-system processes coded as one durable unit, so a five-step transaction either finishes in full or rolls back cleanly. No more orphaned records when step four fails after steps one to three already wrote data.

Smart retries and rollback logic

Retry settings tuned per connected system rather than one blanket rule, with Saga-style compensation so a late failure reverses the earlier writes automatically and your operations team is not cleaning up by hand.

Long-wait and scheduled processes

Integrations that pause for days or weeks waiting on an approval, a settlement window or a third-party callback, holding state safely without a brittle cron job or a long-running script that nobody dares restart.

Inspectable run history

Every step of every workflow is recorded, so when an integration stalls your team sees the exact point it reached and why, instead of stitching the story together from scattered logs.

Where you are stuck

You run an established business on several systems that were never designed to talk to each other. So your team copies the same order into three places, exports a file from one tool to import into another, and reconciles numbers that never quite match. The worst version is the silent one. A transaction starts, gets three steps in, and then a service times out. Now the payment system thinks it is done and the ledger does not, and nobody finds out until a customer complains or a month-end reconciliation breaks.

That is not a logic problem. Your code is fine. It is a state problem. When a multi-step process spans systems, something will eventually fail in the middle, and most integrations have no memory of where they were when it happened.

Why a quick connector alone falls short

The instinct is to wire the systems together with a script or a single queue and move on. For a one-way message hand-off, that is genuinely the right answer. But a queue moves a message and then forgets it. It does not remember that this message was step three of five, that steps one and two already wrote data, and that step four must either complete or undo the lot. So the brittle script breaks the day a connected app changes its response, and you are back to manual cleanup with no record of what actually ran.

Buying a heavier platform does not fix this on its own either. The platform is a starting point. What separates an integration that quietly holds the line from one that becomes a liability is how it handles the failures you cannot see in a demo, and that work does not come in the box.

How we deliver it on Temporal

We treat an integration as durable code. Every step is recorded as it runs, so if a service is unavailable, a node restarts or a deployment lands mid-flight, the workflow resumes from the exact point it reached rather than starting over or losing state. Three principles from our approach shape how we build, in this order.

Healthy data ecosystems (principle #4). Integration is how your data stops living in silos and becomes one view you can trust. We map where each piece of data really lives and which system owns the truth, before a line of workflow code is written, so the integration reflects reality rather than a guess.

Documented, versioned integrations (principle #6). The workflow and activity code is version controlled, the same way we manage any code. When a connected app changes and the integration needs a fix, the change is quick and known, not a mystery outage at 2am. You get an audit trail of how the integration behaves, which matters when the work touches money or regulated data.

Working in small batches (principle #7). We build and prove one real flow before we widen the scope. We map a single integration end to end including its failure modes, build it in a Temporal SDK your team can maintain, then test it against the actual failure cases of a service being down, a slow response or a duplicate event. Only when that flow holds do we move to the next.

A durable Temporal workflow resuming a stalled multi-system transaction after a service comes back online

We decide self-hosted versus Temporal Cloud early, based on your data-residency obligations and how much operational capacity your team has. Temporal Cloud removes the burden of running the cluster. Self-hosting keeps everything inside your environment. We weigh region availability, compliance and the cost of operating it with you before deciding, and we design the deployment to fit Australian requirements where they apply.

When Temporal is the right call, and when it is overkill

Choose it when an integration spans several systems, must not leave them inconsistent, or has to wait a long time for an external event. A payment that posts then updates a ledger and notifies a third party, a settlement that waits days for confirmation, an onboarding that pauses for an approval. Temporal earns its keep on flows like these because the cost of a half-completed transaction is high.

Do not choose it for simple point-to-point messaging, straightforward ETL, or low-stakes automations. A managed queue, an integration platform or a scheduled job will be cheaper to run and easier to staff. Temporal adds a cluster or a Temporal Cloud dependency and a programming model your team must learn, and that overhead is only worth carrying when durability genuinely matters. We will say plainly which side of that line your flow sits on.

This page is about durable, code-based workflows specifically. If you want quick SaaS-to-SaaS connections instead, see our broader integration services and the lighter automation tools in the automation and integration cluster. Temporal is an open-source durable execution platform with SDKs in several languages and a managed offering, Temporal Cloud. The official source is temporal.io.

Explore further

Read more about our Integration Services service and the Temporal technology.

How this looks in practice

Representative solutions.

All solutions

Shipments accounted for

New supply chain management technology that keeps every shipment accounted for

Connected production

How a manufacturer connects SAP to the shop floor with a proper integration layer

Books that balance

A clean Shopify rebuild wired to Stripe and Xero for a retail brand

No stupid questions

Frequently asked.

What are the 4 stages of technology integration?

In practice we work through map, build, test against failure, then widen. We map one real integration end to end including what happens when each step fails. We build that workflow in a Temporal SDK your team can maintain. We test it against the actual failure cases, such as a service being down or a duplicate event arriving. Only then do we widen the scope to the next flow.

Which AI is best for integration?

There is no single best AI for integration, and Temporal itself is durable workflow code rather than an AI. The useful pattern is to use Temporal to orchestrate the steps reliably, and call an AI model from inside a workflow step where judgement helps, such as classifying a document before it routes. We pick the model and platform that fit your task and existing systems rather than pushing one product.

What are the 4 c's of technology integration?

People often frame them as connectivity, consistency, control and cost. Temporal earns its place on consistency and control, because it keeps multi-step transactions in agreement and gives you a clear record of what ran. On cost it can be overkill, so for simple point-to-point connectivity we steer you to a lighter option.

What is AI data integration?

It is connecting your data so that AI can use it, and so that AI-driven steps can write results back into your systems reliably. The connecting and the reliability come first. Temporal handles the durable movement of data between systems, which is the precondition for any useful AI on top, as set out in our approach to healthy data ecosystems.

Can AI do API integration?

AI can help draft integration code and map fields, but it does not run the integration. The integration logic still lives in workflow and activity code that calls your systems through their APIs. We write that logic on Temporal, keep it version controlled, and use AI as an assistant during the build rather than as the thing in production.

What is AI integration service?

It is a service that connects your tools and data so they work as one, and that makes AI features dependable inside those connections. For high-stakes, multi-step flows we build that on Temporal so the work survives failures and restarts. For simple SaaS-to-SaaS connections we use a lighter platform and say so plainly.

Take the next step

Map your riskiest integration with us

Tell us the one integration that leaves systems out of sync when a step fails partway through. We will map it end to end and show you what durable execution would change, or tell you a simpler fix would serve you better.