Capabilities
Capabilities
The technical capabilities behind the data factory, from document understanding to integration.
Capabilities are not presented as isolated tools. Each one has a defined role in the production line and a measurable output. A capability enters production only after it is configured for the project and measured against its Golden Standard.
DESIGNED FORCapabilities are designed into the platform and enter production only after they are configured and measured against the project's Golden Standard.
Capability map
Capabilities
Document Intelligence
Read and understand many document types without depending entirely on fixed forms.
Complex PDF Decomposition
Automatically split merged files, identify the components of a record, and regroup them in the right context.
OCR + Handwriting
Combine recognition of printed, typewritten, and handwritten text under real data conditions.
Multimodal Understanding
Read text, images, maps, and visual documents when the problem requires it.
Data Extraction
Extract fields, tables, entities, and relationships into the target schema.
Reconciliation
Compare multiple sources to resolve conflicts and determine the priority value.
Deduplication
Detect duplicate documents and records, and consolidate history by entity.
Current-State Resolution
Separate history from the current state when the business requires it.
Rules Engine
Apply domain rules, logic checks, and cross-field validation.
Human-in-the-Loop
Route hard exceptions to a human reviewer instead of forcing the AI to answer.
Golden Standard
Lock the correct standard before scaling into production.
Industrial Scaling
Measure capability by standard-passing output and replicate by production unit.
Data Provenance
Trace results back to the document, page, version, and processing step.
On-Premise / Private Deployment
Deploy on controlled infrastructure for sensitive data.
Integration
Export to the target schema, API, data warehouse, or existing business systems.
Why it matters
The harder the legacy data, the more valuable the production layer becomes.
How to start
Start with one representative dataset
Choose a representative dataset, then lock the output schema, business rules, key fields, handling of missing or conflicting values, and acceptance criteria. Measure the result against those criteria before scaling production.
Related