Every Q360 shop has a pile of "we need this file in / out" problems.
Bank statements in CSV. Credit card transactions from the corporate card portal. Payroll files in a format the HRMS vendor expects. Monthly rebate reports from a vendor program. Custom expense categorizations from one department. End-of-month journal entries from a sister company's accounting system. None of these are part of Q360's out-of-the-box functionality. All of them are bog-standard data-processing work that someone has to own.
Most shops handle these with a patchwork of Excel macros, Power Automate flows held together by a retired finance manager, and the occasional Python script written by whoever was technical enough. It works until it doesn't — and when it breaks, nobody knows how to fix it.
Every shop we audit has at least half a dozen of these "data glue" processes running in the background. They're rarely documented, often owned by one person, and the business depends on them more than leadership realizes.
Data processing as a service.
Rubi takes ownership of the data-processing layer around Q360. We build reliable pipelines for the formats your business already consumes — bank statements, credit cards, expense exports, payroll files, vendor reports — and we maintain them as part of an ongoing engagement.
The boring data work that every Q360 shop accumulates over a decade. We take it off your plate and make it reliable.
Common use cases.
How we build these pipelines.
- Discovery. We walk through every existing "glue" process — what files come in, where they go, who currently handles them, what breaks, and what happens when it does.
- Prioritize by pain. We start with the most manually-intensive or error-prone pipelines, not the easiest. High-value wins first.
- Build the pipeline. Using our data-transformation toolkit, Q360 Live Data Reports + SQL Report API, CSV/spreadsheet processors, and third-party APIs (expense platforms, payroll, accounting).
- Dry-run + validation. We run the pipeline in "report-only" mode for 2-4 weeks so your team can compare the output against what the manual process would have produced.
- Go live. The pipeline takes over. Outputs flow automatically. We monitor for the first month closely and then drop to ambient monitoring.
- Ongoing ownership. We maintain the pipeline as part of the engagement — vendor format changes, new edge cases, incremental improvements.
Technology stack.
- Q360 API + Live Data Reports + SQL Report API — for reads and writes against the ERP
- CSV + spreadsheet processors — robust parsers that handle weird encoding, missing headers, split files, and other edge cases every real-world file has
- Third-party integration APIs — expense platforms, payroll systems, banks, vendor portals
- Data transformation engine — our internal tool for declarative transformation rules; field renames, value mappings, aggregations, enrichment
- Scheduled execution — typically Azure Functions or a similar cloud scheduler; reliable, observable, alertable
Frequently asked questions.
Yes — that's the recommended path. Pick the single most annoying manual process, let us automate it, see how it feels, and then decide whether to hand us more.
We maintain the pipeline — when a bank changes its CSV format, or a vendor tweaks their report columns, we adjust the transformation rules without charging you for a new project.
No. Power Automate is fine for simple flows but hits walls on volume, reliability, and complex transformations. Our pipelines are code-based (Python / SQL) with proper error handling, retries, and observability. They work at scale and don't break silently.