Connect the Systems You Already Run
Ignyte Software connects ERP, CRM, accounting, databases, and third-party APIs so data entered once flows to every system that needs it. We build integrations in .NET and SQL Server with logging, retries, and alerting, so a failure lands in someone's inbox instead of in your data.
What we deliver
- Re-keying orders between ERP and CRMtoTwo-way synchronization
- Nightly spreadsheet exportstoScheduled pipelines and ETL jobs
- Vendor systems with no APItoDatabase, file, or export-based integration
- Partner data sent by emailtoEDI and automated partner exchange
- Failures nobody noticestoLogging, retries, and alerts
- Lexington, KYCentral Kentucky & nationwide
- Built to fail loudlyLogging, retries, and alerting on every integration
- .NET, SQL Server, and RESTPlus Dynamics 365 and message queues
- First conversation is freeWe reply within one business day
Last updated September 3, 2026
Integration Work We Take On
Most integration requests start with a person who types the same thing into two systems, or a report that never matches because the two sources were updated at different times. These are the engagements that fix that.
Customers, orders, pricing, and status kept in step between systems such as Dynamics 365 and your ERP, with one agreed owner for every field.
REST and SOAP services that expose your data safely to partners and applications, and clients that consume third-party APIs with authentication, paging, and rate limits handled.
Extract, transform, and load jobs that move data between databases, files, and services on a schedule, with each run logged and repeatable.
Automated exchange of orders, invoices, and shipment notices with trading partners, replacing the attachments someone retypes.
Queues and events for the cases where minutes matter, such as inventory, order status, and notifications, with messages that survive an outage on either side.
Taking over a job or service that runs but nobody understands, getting it into source control, adding logging, and stabilizing it before changing it.
How We Build an Integration
The code is the smallest part of an integration. Most of the work is agreeing what each field means, which system owns it, and what should happen when the two sides disagree. We settle those questions before we build, then test against your data before anything runs unattended.
- 1Inventory
List every system involved, how each one can be reached (API, database, file drop, or export tool), who owns it, and what it must never receive.
- 2Map
Match fields between systems, name a system of record for each one, and write down the conflict rules, so a customer edited in two places ends up one way and not two.
- 3Build
Write the integration so each run can be repeated safely, logs what it did, retries transient failures, and stops and alerts on anything it does not recognize.
- 4Verify
Run it against copies of your data, reconcile the results on both sides, and put the edge cases your team already knows about through it before it touches production.
- 5Run and watch
Go live with monitoring, a dashboard of recent runs, and a runbook for the people who will get the alerts. Stay on for the issues that only appear with real volume.
Built to Fail Loudly
An integration that fails quietly is worse than none, because people keep trusting the numbers. Every integration we ship has the same safeguards.
What ran, when, how many records it touched, and what it skipped, kept long enough to answer questions weeks later.
A timeout or a brief outage on the other side triggers a retry with backoff. A repeated failure stops the job and raises an alert.
Jobs are built so running the same batch twice produces the same result. Recovering from a failure means rerunning the batch, with no cleanup afterward.
Failures and unrecognized data go to a named person by email, with enough detail to act on, and a record you can review later.
What You End Up With
Systems that agree with each other, and a clear answer when they do not.
- Data entered once and carried to every system that needs it, with no retyping.
- A written field map and conflict rules, so everyone knows which system owns each piece of data.
- Logs, retries, and alerts on every integration, with a runbook for the people who receive them.
- Source code and documentation you own, on .NET and SQL Server platforms your team can support.
- Reports that match, because both sides were updated from the same record.
Technologies
Related Reading
Integration usually arrives with a database question or an inherited system attached.
Database design and development
The SQL Server side of most pipelines: schema, tuning, and reporting structures.
See the service GuideTaking over an undocumented codebase
The same sequence we use to rescue an integration nobody understands.
Read the guide ServiceCustom application development
When the right fix is a new application with the integration designed in.
See the serviceCommon Questions
Almost always. When there is no API we work at the database level, through scheduled file exchange, or by automating the vendor's own export and import tools. We confirm which route is safe for each system during discovery.
Every integration ships with logging, retry logic, and alerting, so a failure reaches a person the same day instead of silently corrupting data. Jobs are built so a rerun after a failure never creates duplicates.
Yes. Taking over an integration nobody fully understands is common work for us. We start by getting the code into source control and adding logging, then map what it does before we change it.
Usually a different one for each kind of data. Customers might belong to the CRM, prices to the ERP, and payments to accounting. We settle that for every field during mapping, so two systems never fight over the same record.
Only when the business needs it. A nightly or hourly job is simpler, cheaper to run, and easier to recover. We reserve event-driven, message-based integration for cases where a delay would cost you, such as inventory or order status.
The integration fails loudly instead of quietly. Version and schema checks catch the change, an alert goes out, and the integration stops rather than writing bad data. Adjusting to the new version is normal maintenance.
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