Services — System Integrations
System integrations
Connecting systems that were never designed to know about each other. The API call is the easy part; the work is in the entity matching, the data quality and the failure modes nobody specified.
Where the work concentrates
Document management platforms
iManage, NetDocuments and OpenText connected to billing, CRM, matter management, search and client portals. The recurring difficulty is that the DMS and the operational system usually share no common identifier — client and matter records were set up independently, across offices, over years. Entity matching against inconsistent naming and numbering is most of the engineering.
Legal time and billing systems
3E, Aderant and Elite hold the canonical client and matter record, which is why so many integrations end up touching them. That centrality brings its own constraints: fiscal period logic, matter lifecycle states, and the requirement that an integration can expose matter and client data without exposing rate information.
Healthcare registries and clinical reporting
Validated registry data moving into reporting and visualization layers. The distinction that governs the architecture is that the registry is the data source and the platform is a presentation layer — which means the integration must never become a place where numbers are silently recomputed.
Commerce, fulfillment and ERP
Storefronts connected to shipping, fulfillment, inventory and accounting systems, including ETL pipelines replacing daily manual processes. Past work covers Shopify to fulfillment pipelines and QuickBooks integrations for membership and event platforms.
What a durable integration includes
Integration specs describe the happy path in detail and leave the rest vague, which is why so many integrations run fine for four months and then quietly stop. Something changes upstream, a record arrives in a shape the mapping didn't anticipate, and the failure surfaces as a user asking why a number looks wrong.
Everything built here includes the parts that get cut from a lowest-bid scope: explicit handling for records that don't match, idempotent retries so a replay doesn't duplicate data, reconciliation that can prove both systems agree, and monitoring that tells you a sync failed before a user does.
The other recurring decision is what an integration should refuse to do. Using the integration layer to paper over a data quality problem that belongs upstream is the single most common source of integrations that become unmaintainable — it works immediately and compounds indefinitely.
Typical stack: .NET, REST and SOAP APIs, Azure Service Bus, Azure Functions, SQL Server, and whatever the systems on either end actually speak.
What needs to connect?
Name the two systems and what the manual workaround currently is. That's usually enough to say whether this is a two-week problem or a two-quarter one.
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