System Integration

Land Your Migration On Time — And Keep the Data Model You Build

Every ERP rollout, platform migration, and system consolidation is a data-mapping problem underneath. Dataplane automates the work of conforming source data to your target system — and turns that effort into a durable asset instead of a spreadsheet you throw away at go-live.

The Challenge

The Data Work Is Always Bigger Than the Plan Said

When you stand up a new system, the demos look clean and the timeline looks reasonable. Then the source inventory comes back. Customer records live in three places that disagree. Product hierarchies were built by different teams in different decades. Critical attributes only exist in someone's spreadsheet. The new platform has its own data model — its own definition of what a customer, a product, or an order is — and nothing you have today fits it cleanly.

Going live means conforming every source to that target model. That conformance work is exactly where transformation timelines slip. It is understated in scoping, owned by a program office that rarely has tooling built for it, and handled the same way it has been for years: analysts and mapping spreadsheets, hand-reconciling thousands of source fields to target requirements, row by row.

The spreadsheet is slow to build, brittle to maintain, and impossible to fully trust. Worse, it is disposable. The moment you cut over, that hard-won mapping logic gets archived — and the next migration, the next acquisition, the next platform change starts the entire exercise over from zero.

The Shift

The Spreadsheet Is a Throwaway. The Data Model Is Durable.

Dataplane is built around an ontology — a semantic data model that maps your raw, messy source data to what your business actually means. It captures the canonical entities you care about (customers, products, sites, orders), how source fields map into them, and what your target system requires expressed as rules. In other words, the same conformance work a migration demands, but built as a maintained model instead of disposable artifacts.

Our AI compiles source-to-target mappings against that model. The work of getting clean, conformed data into the new system is the work of building your ontology. Same effort, fundamentally different outcome: one approach gets thrown away at go-live, the other becomes the standing semantic layer everything connects to — feeding future governance, the next integration, and every downstream system and team that needs trusted data.

The transformation pays for the model. The model outlives the program. Data stops being a constraint on your timeline and becomes a catalyst for everything that comes after it.

The Solution

De-Risk the Phase That Sinks Transformations

Dataplane automates the extract, reconcile, and conform phase that scoping always understates — and composes the data capabilities a migration actually needs into one workflow.

Automated Source-to-Target Mapping

AI compiles mappings from every source into your target model. Inspectable and explainable — not a black box, and not a spreadsheet maintained by hand.

Any Source, Any Format

Legacy ERPs, CRMs, warehouses, exports, and spreadsheets — structured or unstructured. Dataplane reads them all and conforms them to one canonical shape.

One Record per Real-World Thing

Canonical entities are resolved and deduplicated across every source, so the same customer or product from five systems lands as a single, trusted record in the new platform.

Target Requirements as Rules

The new system's mandatory fields, formats, and constraints become enforceable rules. Gating data errors are caught in validation runs that take minutes, not weeks.

Transform to Target Format

Units, codes, hierarchies, and missing attributes are normalized and enriched to exactly what the destination expects — so loads land clean the first time.

Business Teams in the Loop

A natural-language interface lets the people who know the data engage directly — defining and reviewing mappings without waiting on a queue of technical specialists.

How It Fits Together

One Workflow, Built From Capabilities That Last

System integration is not a single feature — it is the place several of Dataplane's core capabilities come together around your migration, all anchored to the same semantic model.

Master data resolves canonical entities and removes duplicates across every system feeding the new platform.
Data quality turns the target system's requirements into rules that block gating errors before cutover.
Enrichment transforms source values into the exact formats, codes, and completeness the destination demands.
The ontology is the model everything connects to — the durable byproduct that survives long after go-live.

Because the pipelines extract cleanly and the model is maintained, the same foundation carries straight into ongoing governance and the next initiative — including grounding the agentic systems your teams build on top of trusted data.

Results

Outcomes Programs Can Take to the Steering Committee

Automating conformance changes the shape of a migration: the risk moves out of the data phase, and the effort leaves behind something you keep.

Validation in Minutes

Conformance checks that used to take weeks of analyst time run in minutes, so issues surface early enough to fix without slipping the date.

A De-Risked Go-Live

The extract, reconcile, and conform phase that programs chronically underestimate is automated and inspectable end to end.

An Asset, Not an Artifact

The mapping work becomes a maintained semantic model that feeds governance and powers the next integration instead of being archived and rebuilt.

Business and IT Aligned

A natural-language interface lets the teams who own the data participate directly, while IT keeps governance and oversight without becoming the bottleneck.

Make Your Next Migration the Last One You Start From Scratch

See how Dataplane automates conformance and leaves you with a data model that outlives the program. Explore the ontology that anchors the platform or talk to our team.