Smart Data finds the money between the systems

The assignment was small: add a code to a file. An Ohio Medicaid health plan needed its Nursing Facility Level of Care process updated for a new state requirement. Smart Data’s engineers began looking at the records. Some concerned members who were ineligible on the relevant dates. Others were duplicates, missing admission dates. Still others asked the state to update records it did not have. The file kept running. The mistakes kept traveling.

According to Smart Data’s account, a developer and business analyst, with senior technical oversight, reconciled the historical file. The health plan confirmed the problem and submitted corrections. More than $16 million in lost revenue came back. The plan then commissioned a SQL Server rewrite to stop the loss recurring. A maintenance request had become a business investigation.

The file was running. The money was missing.

That is a useful introduction to Smart Data. Founded in 2006 by Ravi Manchala, the Dayton-area company builds software for organizations whose existing technology has accumulated obligations: keep the records, calculate the price, submit the claim, preserve the workflow. Its territory includes custom applications, enterprise integrations, data engineering and AI. The interesting action often happens where those categories meet.

The Medicaid example illustrates a particular kind of failure. Nothing had to crash for money to disappear. Records could leave the building on schedule and still be wrong. For a business deciding where to spend its technology budget, that changes the question. Alongside uptime, ask whether the information arriving at the other end represents what actually happened.

The ten-minute tax

At robotics manufacturer Yaskawa Motoman, the friction was easier to see. Salesforce and Epicor could take up to ten minutes to synchronize. The connection was error-prone, and small changes could require weeks. Smart Data rebuilt it over ten development sprints. The company reports synchronization below ten seconds, delivery one week early and a result six percent under budget.

The mechanics deserve attention. Developers knew Salesforce and integrations, but had to learn Epicor. Meetings connected Ohio mornings with India evenings. Documentation supported handoff and internal testing. This is a more useful account of offshore development than a promise of cheaper hours: someone has to absorb unfamiliar systems, schedule decisions and make the result maintainable for the people left operating it.

Customers span healthcare, manufacturing, distribution and finance. Google’s internal sales team received a custom learning-management tool with Google Drive integration and two-way synchronization. Davey Tree’s customer portal joins SAP, Dynamics CRM and content-management data. These are different businesses with a similar complaint: the organization owns the necessary information, but using it involves too many disconnected steps.

Buy the work. Choose who owns it.

Smart Data occupies the services side of enterprise technology. Customers pay for engineering and ongoing responsibility. In a scoped project, Smart Data manages delivery against agreed milestones, using a fixed bid or time-and-materials pricing. Managed services usually carry a monthly contract. Staff augmentation puts its engineers inside the customer’s team; direct placement helps the customer hire permanent staff.

Those distinctions matter more than the vocabulary. A company that lacks project leadership needs something different from one missing two experienced developers. Smart Data’s process starts with a conversation, an engineer’s examination of the current systems and a written proposal. The commercial unit is a defined piece of work or continuing service, with the team’s responsibilities established up front.

Winsupply shows how that relationship can grow. Smart Data helped establish the distributor’s Hyderabad development center, recruiting more than 40 engineers in its first year; the center subsequently grew past 100. The work included infrastructure, onboarding, workshops and coordination across five business domains. Hiring people was only part of making the new operation useful.

“They go beyond just delivering our projects or expanding our teams.”Christopher Schrameck, VP, Information Technology, Winsupply

The dashboard comes last

For an EV charging provider, Smart Data connected Synop, Geotab and Ampcontrol through AWS serverless pipelines into Snowflake. The five-month engagement included a secured customer dashboard, Jira support workflows and recruiting an in-house data warehouse architect. The visible screen depended on less visible work: collecting data consistently, modeling it and deciding who would own it afterward.

Smart Data formalized a Snowflake Select Tier services partnership in 2025 and announced a Databricks partnership in May 2026. Its current offering also includes Microsoft Fabric. This gives it several platforms on which to solve a customer’s problem, alongside the application and integration work needed to connect the platform to daily operations.

Its AI work includes maintaining existing software. For an unnamed distributor, Smart Data reports that one senior engineer using AI-assisted methods cleared more than 620 known vulnerabilities. Removing unused Azure resources cut annual spending by over $25,000. A further consolidation was projected to bring total annual savings to about $78,000; that conversion remained in testing in the published account. A forecast and a realized saving belong in separate columns.

Start with the rejected record

There is a practical method here that another team can copy. Choose a consequential handoff. Trace a record through it. Examine rejections and duplicates. Ask a business owner whether the output is correct. Agree how to test the change and who will maintain it. The Medicaid discovery began with that kind of attention, before it became a rewrite.

Custom engineering also requires access to systems and people who understand their rules. If a standard product already meets the requirement, commissioning bespoke work may add unnecessary maintenance. Smart Data’s most persuasive position is where the organization’s actual workflows require careful adaptation. Its case studies make that work tangible: a corrected file, a faster connection, a team able to take over.