Query Exactly What You Need, Resolved Across Two Schemas
GraphQL lets you ask for exactly the fields you need in one query, but that only works cleanly when the schema on the other side actually matches yours, which it almost never does exactly. We build GraphQL integrations with AI resolving fields between mismatched schemas, so a query against an external service maps correctly into your ERP's own structure.
50+ ERP and software projects. Zero failed projects since 2021.
Two schemas rarely describe the same thing the same way
GraphQL's flexibility on the client side does not remove the mismatch between what two systems call the same piece of data.
One schema's field becomes another's, correctly
A field called deliveryWindow on one side might be split across two fields on the other, or simply not exist. AI resolution works out the correct correspondence where one exists, and reports clearly where it does not, instead of returning an empty or default value silently.
- Field correspondence resolved across mismatched schemas.
- Unresolvable fields reported clearly, not defaulted.
- Nested and renamed structures handled without a rigid map.
A schema change should not mean a broken integration
External GraphQL APIs evolve their schemas over time, adding, renaming or deprecating fields. The integration detects these changes and updates its resolution logic, so a routine schema update on the other side does not turn into an emergency fix on yours.
- Schema changes on either side detected automatically.
- Resolution logic updated rather than breaking outright.
- Deprecated fields flagged before they cause a failure.
What a resolved query looks like
A query written against one schema, resolved field by field into your ERP's own structure.
From two schemas to one resolved query layer
What a GraphQL integration typically covers
Any external service exposing a GraphQL schema that your ERP needs to query or supply.
Cross-schema queries
Queries against an external schema resolved into your ERP's own field structure.
Schema change detection
Ongoing monitoring for changes in either schema, with resolution logic updated.
GraphQL layer over your ERP
A flexible GraphQL interface exposed over your existing ERP data where useful.
Unresolved field flagging
Fields with no clear correspondence reported clearly instead of defaulted.
Query logging
A record of queries run and their resolution outcomes, for debugging and audit.
Mutation support
Writing data back through GraphQL mutations where the external service supports it.
What a resolved GraphQL integration changes
Why teams choose TCB Infotech for GraphQL integration
GraphQL API AI integration questions
What is GraphQL API AI integration?
How is this different from REST API integration?
Can you build a GraphQL layer over our own ERP?
What happens when a field cannot be resolved?
Do you handle schema changes over time?
How long does a first integration take?
Flexible queries still need an honest translation underneath
GraphQL solves the problem of asking for exactly what you need in one request. It does not solve the separate problem of two systems describing the same thing with different names, structures and assumptions.
Resolving that translation with AI, and reporting clearly when a field genuinely cannot be resolved, is what makes a GraphQL integration something your ERP can actually rely on, not just query against.
Connect Your ERP to a GraphQL Service, Correctly
Book a free consultation. Share the schema you need to connect to, and we will scope what resolution would involve.
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What Is Inside the GraphQL API AI Integration
Resolving two schemas that were never designed to match takes more than a lookup table. Here is how the comparison, resolution and change detection work together.
From two independent schemas to one reliable resolution
Understanding both sides before resolving anything
Before any query runs, the two schemas are compared field by field, type by type, to build an initial map of what corresponds to what. This upfront comparison is what makes later resolution fast and accurate rather than guessed at query time.
- Both schemas compared field by field upfront.
- Types and structures reconciled before live queries run.
- An explicit map maintained, not resolved from scratch each time.
Each field resolved on its own terms
A field might need a straight rename, a currency conversion, a unit conversion, or a calculation combining two source fields. Each field's resolution logic is built individually for what it actually needs, rather than forcing every field through the same generic transformation.
- Resolution logic tailored to each field's specific need.
- Calculations and conversions handled where required.
- No forced generic transformation across all fields.
Watching both schemas so nothing breaks quietly
The integration periodically checks both schemas for changes, such as a new field, a renamed one or a deprecation notice, and flags anything that affects the existing resolution map before it causes a failed query in production.
- Both schemas monitored for changes over time.
- Affected resolutions flagged proactively.
- Deprecations caught before they cause a failure.
Everything the GraphQL integration includes
Mutation support
Writing data back through GraphQL mutations, with the same field resolution applied.
Query and resolution logs
A record of every query run and how each field was resolved, for debugging.
GraphQL layer over your ERP
A flexible query interface exposed over your own ERP data where useful.
Resolution confidence flags
Each resolved field marked by confidence, so uncertain ones can be reviewed.
Schema diff reports
A clear summary of what changed between schema versions and its impact.
Model-agnostic build
Built so the underlying resolution approach can be upgraded without a rebuild.