Most businesses do not have one system of record - they have four, each holding a version of the same customer, order, or stock level. We build the API layers and middleware that keep them agreed, so reconciliation stops being somebody’s Monday morning.
The symptom is usually the same. Finance quotes one revenue number, the CRM quotes another, and somebody spends Monday working out which is right. That is rarely a data-quality problem. It is two systems that were never told about each other, both writing to their own copy of the truth. The work is deciding which system owns each field, then building the layer that keeps the rest in step with it.
A unified operational layer so your systems agree with each other and nobody reconciles them by hand. Usually that means the ERP at the centre of it, the CRM beside it, and often a storefront that has to reach them both.
We architect “Data Fabrics” that unify your business-critical systems, such as ERP, CRM, SCMs, and more. Event-driven architecture with durable queues and replay means a downstream system being briefly unavailable delays a message rather than dropping it.
When an off-the-shelf connector does not cover the case, we build the API. Versioned REST and GraphQL endpoints with authentication, rate limiting, and monitoring in place from the first release, because retrofitting a version scheme onto a live API is considerably harder than starting with one.
Two-way pipelines between Salesforce, SAP, Oracle and the systems around them. Two-way sync always raises the same question: when both sides changed the same record, which one wins? We answer that per field, in writing, before anything is built.
Modernization does not always mean a total rewrite. We build modernized layers and adopters that allow your battle-tested systems to communicate with modern cloud-native apps, extending the ROI of your core assets.
We unify your SaaS sprawl. Whether it is about connecting your HubSpot to Stripe or AWS, Azure, or GCP to the marketing stack, we use an IPaaS-aligned approach to build modular pipelines that scale according to new tools.
OAuth2 and OpenID Connect for service-to-service and user authentication, with credentials scoped to the specific operations each integration performs. An integration account with full admin rights is the most common finding when we audit an existing setup.
Where the logic between systems is too specific for a connector, a middleware layer handles routing, transformation, caching, and error recovery in one place. That keeps the business rules somewhere you can read and test them, rather than spread across six point-to-point scripts.
Kafka, AWS Kinesis, Azure Data Factory, and RabbitMQ for moving events between services. Durable queues with replay mean a consumer that is briefly down delays a message instead of losing it, which matters more in practice than raw latency.
Integrations are a common point of data exposure. We design each touchpoint with the requirements of GDPR, SOC 2, and HIPAA in mind - encryption in transit and at rest, scoped credentials, and audit logging - so your data-handling obligations are considered at the architecture stage rather than retrofitted later.
Engineering-first approach to system interoperability
Versioned APIs designed as the contract between systems, so a change on one side does not silently break the other.
ETL and mapping between schemas that disagree about field names, formats, and what counts as an empty value.
Adapters that let an older system exchange data over a modern API without changing the system itself.
Event-driven triggers with retry and dead-letter handling, so a failed delivery is visible rather than lost.
Encryption in transit and at rest, with credentials scoped to the specific operations each integration performs.
Distributed tracing across the integration path, so a slow step can be identified rather than guessed at.
What changes when the systems stop disagreeing
Each field has one owning system, and the others follow it. Disagreements get resolved by a rule, not by a meeting.
Work that currently moves between systems as a spreadsheet or a copy-paste moves as a message instead.
Analytics read from the owning system, so two dashboards asking the same question return the same answer.
New tools connect to an existing integration layer rather than adding another point-to-point link to maintain.
Replacing one system does not mean rewriting every connection into it.
Consolidating scattered point-to-point scripts into one layer means fewer places to look when something stops flowing.
A structured, audit-driven approach to designing and deploying reliable, secure system integrations.
The platforms and protocols we use to move data between systems safely
Deep technical analysis, architectural case studies, and strategic perspectives from our senior development teams.
Every growing business faces the same decision: buy off-the-shelf or build custom? It's a strategic choice with massive consequences for your bottom line.
Agile works beautifully for small teams. When the enterprise gets involved, scaling agile isn't about doing more agile - it's a different problem.
Choosing the wrong development partner is an expensive mistake. Here's how to approach the selection process in a way that actually predicts success.
Related work that often sits alongside this one in the same engagement.