Most business systems are worth exactly as much as they talk to everything else the company runs. We connect payments, accounting, inventory and public registries so that failures are visible and recoverable by hand.
The average company didn’t build most of its software — it bought it. CRM from one place, ERP from another, payroll from a third, the webshop from a fourth. Each purchase made sense on its own and each system does its own job well. It is just that between them, information moves in somebody’s head and by copy-paste.
This is a separate discipline from building your own API. Here you don’t decide what the other side offers, how it authenticates, when it renames a field, or what happens when it goes down for three hours. The work is building a layer that tolerates those differences — and that tells you before a customer does.
Six areas. Most projects start from one of them and discover halfway through that they need a second — which is why it pays to map the whole picture before building the first connection.
Salesforce, SAP, Microsoft Dynamics, ServiceNow, HubSpot and the other large platforms, wired into the rest of your business. Each has its own data model and its own idea of what a customer is — the work starts with reconciling those.
The smaller cloud services — project management, support, marketing, accounting — connected to the core system so the data moves itself. With the authentication, error handling and monitoring that off-the-shelf connectors usually leave out.
ERP, CRM, HR, payments and analytics joined into one whole where every field has one agreed source of truth. Without it, every department holds its own version of the same number.
Two systems always drift apart — the only question is whether you find out. We build the rules for duplicates, formats and conflicts, plus a reconciliation report that surfaces discrepancies before a financial report does.
When some systems are in the cloud and some in your server room, integration is a network and security question as much as a data one. We cover both sides: AWS, Azure, Google Cloud and whatever runs in-house.
We map what is connected to what today, where information moves by hand, and what costs the most. The output is an order of priority — most of the gain usually comes from two or three connections rather than from all of them at once.
We don’t choose the interface style — the other side does. With legacy systems that often means SOAP or file exchange, and done properly that is perfectly reliable.
The bill for disconnected systems never arrives as a single line. It arrives as hours, as errors, and as decisions made from the wrong number. These four are measurable before and after.
The most expensive integration is the one a person performs today — every day, the same way.
When two systems give different answers to the same question, no decision can rest on either of them.
An integration whose failure you hear about from a customer is worse than no integration at all.
If every new tool requires reworking all the existing ones, you stop buying new tools.
Four stages. First, discovery and an architecture review: which systems are in play, who owns which field, and what happens today when somebody changes something by hand. Second, solution design — the field mapping, error handling, authentication, and whether the flow is synchronous or not. Third, development and testing against a simulated partner. Fourth, deployment with monitoring and alerting.
The time it takes depends almost entirely on the other side. A well-documented API and a narrow scope is two to four weeks of work. Where the partner’s documentation is wrong or there is no sandbox, most of the time goes on establishing how the partner actually behaves rather than on code — and we say so upfront rather than in week three.
When choosing a partner, ask what happens when the other side is down, how the same order is prevented from being processed twice, and where you can see that the integration is working. If the answer to the last one is “the customer tells us”, there is no monitoring.
We assume the other side will be down, slow or wrong. Queues, retries and idempotent writes are the starting point, not a later fix.
We simulate the partner’s interface, so your team can test even when the partner’s sandbox is closed or doesn’t exist.
A reconciliation report compares the systems regularly and shows the differences before they reach a report or a customer.
When there is no proper API and it comes down to file exchange or browser automation, we’ll build it — but we say upfront what it will cost you in maintenance.
API keys, repositories and cloud accounts are yours. An integration must never be the reason you can’t change supplier.
We are in Tallinn, in the same timezone and the same contractual framework. Data can stay entirely inside the EU.
Payment providers and banking interfaces, ERP and accounting systems, CRMs, warehouse management, logistics, and public registries including the Estonian Business Register. For a new system we assess the quality of its interface before committing to a scope.
Whichever we agree. When a partner changes their API, somebody has to be watching — either us under a support retainer, or your team, to whom we hand over the monitoring and alerting setup.
Data moves encrypted, personal data is kept out of logs, and access is role-based. For every integration we document what data moves, where it goes, and on what legal basis.
An off-the-shelf connector covers the standard case: two common systems, default fields, one direction. If your data model is standard, that’s the right choice and we’ll recommend it — cheaper and faster.
The difference shows in the edge cases. What happens when the other side is down for three hours? Does the message queue up, or is it lost? How is a conflict resolved when the same record changed in both systems? Off-the-shelf connectors generally answer those with a shrug, and those are exactly the cases that generate the most work later. A custom integration is where those answers are agreed and written down.
By assuming it’s bad — because it usually is. Two systems that have lived apart for years contain duplicates, inconsistent formats, empty fields and records pointing at things that no longer exist.
So the work starts with mapping: which system is the source of truth for each field, what rules apply to formats, and what happens in a conflict. Those rules are written down before any code. The build also includes a reconciliation report that compares the systems on a schedule and surfaces drift before it reaches a report or a customer — because they always drift apart; the only question is whether you find out.
With a narrow scope and a well-documented API, two to four weeks including tests and monitoring. A data flow across several systems, where sources of truth and reconciliation rules have to be agreed, is more like two to four months.
The time depends almost entirely on the other side rather than on us. Where a partner’s documentation is wrong or there’s no sandbox, most of it goes on establishing how the partner actually behaves. We say so upfront rather than in week three — and where the situation calls for it, we start with a short discovery phase so the number we give holds.
Describe your situation in a couple of sentences. We reply within one working day.