The average mid-sized business runs 8–15 software platforms. None of them were designed to integrate with each other. The result is a patchwork of manual processes: CSV exports, copy-paste workflows, and staff who know exactly which system to check first, second, and third to get a complete picture. When any of those staff members leave, the institutional knowledge leaves with them.
Years in Production
Since 2006. Fortune 15 first client. Every industry on this page, in production.
Your Software Stack Is Held Together with Manual Processes.
Your CRM has the customer data. Your billing system has the invoices. Your ERP has the inventory. They don't talk to each other. Someone (or multiple someones) transfers data between them manually, on a schedule, because that's how the workflow was set up years ago and nobody's had time to change it.
The direct cost is the hours: data entry, export/import cycles, reconciliation runs at month end. But the indirect cost is higher: delayed decisions because the integrated view isn't available until tomorrow morning when the export runs, errors that slip through because manual data entry at volume is inherently error-prone.
Legacy systems compound the problem. Platforms that are no longer supported (EOL ERP systems, deprecated CRMs, unsupported data warehouses) create technical debt that makes every integration harder. The longer modernization waits, the more dependent the business becomes on workarounds that are themselves fragile.
“Your CRM has the customer data. Your billing system has the invoices. Your ERP has the inventory. They don't talk to each other. Someone (or multiple someones) transfers data between them manually, on a schedule, because that's how the workflow was set up years ago and nobody's had time to change it.”
A common situation we hear in discovery
Connect First. Migrate Carefully. Replace Only What Needs It.
A structured process built from 20 years of doing this work.
Integration Audit
We map every system in your environment: what data it holds, what data it needs, what currently bridges the gap between them, and what happens when that bridge breaks. We document the manual processes that are doing integration work the software doesn't.
Integration Architecture
We design the target integration architecture: which systems connect directly via API, which require ETL pipelines, which need transformation layers to reconcile different data models.
Phased Build
We integrate in priority order, starting with the connections that eliminate the most manual work or the highest error risk. Each integration is tested in isolation and as part of the broader data flow before it goes live.
Legacy Modernization
For systems that need to be replaced rather than integrated, we build the migration path: documenting business logic from the legacy system, building to the replacement, and migrating data with validation against the source.
Monitoring & Support
Every integration includes monitoring and alerting. When a data feed breaks, you know before it affects operations. We offer ongoing support for maintenance and updates when underlying platforms change.
What You Get
Concrete outcomes from every engagement.
Unified Data Environment
Your systems share data reliably, on schedule, without manual intervention. Staff work from current information rather than yesterday's export.
Manual Data Bridges Eliminated
The CSV exports, copy-paste workflows, and end-of-day reconciliation runs that exist to cover integration gaps, gone.
Documented Integration Architecture
Every connection is documented: what flows where, when, and why. When a platform updates, you know what integrations to test.
Safe Legacy Migration
A migration path that captures business logic before it's lost, validates data before it moves, and provides rollback capability if something isn't right.
Integration That Survives Updates
We design integrations with version tolerance and test against updates before they hit production.
Technologies We Use
Tools selected for fit and reliability, not to pad a capabilities list.
Integration & ETL
Automation Layer
Data & Databases
Development
A Representative Scenario
How this type of work plays out in practice.
The Situation
A Dallas-based employee benefits provider was running their core operations across three systems (a benefits administration platform, an HR data feed from each employer client, and an internal SQL Server reporting database) with manual synchronization between all three. The manual sync process took 4+ hours per week, produced regular discrepancies, and was owned entirely by one employee whose departure would have created a significant operational problem.
What We Did
Built automated ETL pipelines that pulled HR feed data from employer clients on a scheduled basis, transformed it to match the benefits administration platform's data model, loaded records automatically, and updated the reporting database in real time. Built exception handling that flagged discrepancies for human review rather than failing silently.
The Result
Manual synchronization eliminated. Monthly reporting discrepancies dropped to near zero. The employee who had owned the manual process was redeployed to higher-value client management work. The system now handles employer clients at 3x the previous volume without additional staff.
Common Questions
Things clients typically want to understand before starting a conversation.
Let's Map Your Integration Gaps.
We'll spend 30 minutes understanding your current system environment, where the manual processes are filling integration gaps, and what a realistic integration or migration roadmap looks like. No commitment required.