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BANKING · OPERATIONS MANAGEMENT SUITE

ENTITY MANAGEMENT

Automates entity onboarding end to end - ingesting any format, extracting,
deduplicating, tagging and validating every record, with one compliance gate before export.

15× faster per batch ✦ 100% bilingual output ✦ 85% time saved

Why Entity Management exists

Fifteen manual steps. Zero of them needed.

The problem

Manual onboarding doesn't scale

Every new batch of entities restarts the same fifteen-step slog, end to end.

15 stepsfrom inbox to export, every single batch
Constant reworkmissing fields surface only at QA
Not scalablethe whole process repeats per batch

It is done manually

Days per batch. Errors guaranteed.

Translation, tagging and compliance checks are all done separately, by hand.

Re-typeddata copied from PDF into spreadsheets
OutsourcedArabic translation done separately, often costly
Missed oftenduplicates checked against old spreadsheets

With Entity Management

Nine automated steps. It runs itself.

One pipeline ingests, extracts, dedupes, tags, validates and exports every entity.

15×faster per batch
0manual re-entry
100%bilingual output, EN + AR

What it does · three engines

Screen it. Tag it. Extract it.

01Shariah Compliance ScreeningScreen the entity, not just the paperwork

GPT-4o vision checks modesty, alcohol, gambling, religious symbols and banned text
Business rules and completeness checked in the same pass
Every result flagged compliant, non-compliant or pending

02AI Tag GenerationTag every entity, in any language

Domain-based taxonomy — dining, retail, travel and more
Bilingual tag output, EN + AR, cached after first run
Tag confidence scoring per record

03Intelligent Document ExtractionExtract exactly the fields you define

GPT-4 parses PDFs, Excel, CSV or plain text
Auto-detects entity name, offer type and expiry
EN + AR multi-language extraction in one pass

The capability set

Eight things it does, on every entity.

Not three separate tools — one pipeline that ingests, extracts, dedupes, tags, validates and exports, entity by entity.

01AI extractionGPT-4 parses PDFs, Excel, CSV & text

02Smart deduplicationFuzzy match + canonical ID registry

03Bilingual tag generationEN + AR, confidence scored

04Multi-language OSSide-by-side EN/AR, RTL-safe

05Shariah-compliant validationGPT-4o vision review

06Backup & restoreVersioned snapshots, one-click rollback

07S3-ready pipelinePre-signed uploads, CDN backfill

08Production-ready stackFastAPI, React 19, Pandas, AWS S3

The OMP data pipeline

Seven stages. One compliance gate.

01Upload

Ingests raw source files — PDFs, Excel sheets or structured exports — straight into the queue, no manual reformatting.

02Extract

GPT-4o reads every document with high-detail image analysis, pulling entity, offer and location fields with near-zero hallucination.

03Dedupe

Fuzzy matching resolves duplicate entities across batches using name similarity, geolocation and category-weighted signals.

04Tag

AI assigns bilingual taxonomy tags — category, type, amenities, service style and more — in English and Arabic.

05ValidateCompliance gate

Business rules, Shariah-compliance image screening, completeness checks and field-level QA, all in one layer.

06Export

Generates bilingual CSV files formatted exactly to the import schema — ready to upload straight into production.

07Restore

Every run is snapshotted. Restore any previous run, recover deleted records or reprocess a failed batch in one action.

Shariah Compliance Screening

Screen the entity, not just the paperwork.

GPT-4o vision · modesty, alcohol, gambling, symbols, text

1
Three intake modesImages, free text or a PDF — GPT-4o vision reviews each the same way.
2
Type it or paste itNo fixed format — a line of text is enough to screen an entity.
3
Rules you controlEdit the compliance rule set without touching code.
4
Optional auto-approveSkip manual review only for clean passes.

Compliance controls

Turn on autonomy, deliberately.

the Validate stage · business rules + image screening

1
Documents tooUpload a PDF and it's screened the same way as an image or text.
2
One drop zonePDF, up to 10MB, no separate upload flow.
3
Edit the rule setCompliance rules live in one place, editable without a release.
4
Auto-approve, on your termsSkips manual review only when it's switched on.

AI Tag Generation

Tag it once, read it everywhere.

domain-based taxonomy · EN + AR, confidence scored

1
Name, then goEnter the entity name — the model infers the rest.
2
Category-awareTags reflect category, type, amenities and service style.
3
One click, every languageGenerates tags in every language you select, in a single call.
4
Cached after the first runBilingual tags aren't regenerated unless the entity is new.

Bulk tag generation

One entity, or ten thousand.

CSV or Excel in · thousands of records per minute

1
Same tool, bulk modeSwitch from one entity to a full file with a single toggle.
2
Bring your own listUpload a CSV or Excel file of entity names, nothing to reformat.
3
One run, every rowGenerates tags for the whole file in one call.
4
Languages carry overThe same output languages apply to every entity in the file.

Intelligent Document Extraction

Define the fields. It finds them.

GPT-4 extraction · near-zero hallucination

1
You define the schemaName every field you need — legal name, registration number, status.
2
Add as many as you needNo fixed template — extend the schema field by field.
3
Any document inPDF, Excel, CSV or plain text, dropped straight into the tool.
4
Structured JSON outMerchant, offer and location fields, typed and ready for the core system.

In summary

Fifteen steps, automated into nine that run themselves.

One pipeline ingests, extracts, dedupes, tags, validates and exports every entity — 0× faster per batch,
with 0% bilingual output, saving 0% of staff time.

Built for production workloads — enterprise-grade reliability, security and scale.

Try it first on your own data in the playground.

omp-playground.tngrm.ai

Entity Management · Crayon Data

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