Challenge
DocLoom
OCR breaks on complexity. (standard OCR breaks on complex layouts, tables, and low-quality scans.)
Multi-engine routing always picks the best fit.
Every tool, a different shape. (output format varies by provider every tool produces different structure.)
Markdown-first normalisation across all providers.
Bad fields slip through. (low-confidence extractions pass through without correction.)
Confidence-aware self-correction on every low-quality field.
Cloud OCR adds up. (cloud OCR at scale adds up - especially for sensitive document types.)
Local LLM option zero marginal cost, zero data egress.
01
Ingest
Upload PDF, jpeg, or png via API, SDK, or portal. Each document is analysed for layout, complexity, and markdown compatibility before routing begins.
02
Extract
The decider engine selects the optimal OCR provider by document type, layout, and cost with a ranked fallback chain prepared if the primary provider fails.
03
Audit
Raw OCR output is normalised to clean Markdown tables, headers, and structure preserved. An LLM maps it to your JSON schema using your custom extraction instructions.
04
Report
Every field is confidence scored. Fields below your threshold trigger automatic re extraction with a higher- capability provider, then merge back into the final output.
Every provider output is normalised into unified Markdown before extraction runs. LLMs process structured Markdown with significantly higher accuracy than raw text fewer hallucinations on complex documents.
Raw OCR text → # Markdown
LLM-ready
Set your confidence threshold. Any field below it triggers automatic re-extraction with a more capable provider only that field, only that page. Corrected values merge back automatically.
Below 0.80 → re-extract automatically
Azure Document Intelligence, AWS Textract, Google Document AI, and DotsOCR routes to the right engine per document - if the primary fails, the next in the ranked chain picks up automatically.
Azure AI → Textract → . Google → DotsOCR
Run extraction inside your own infrastructure with DotsOCR, a locally hosted vision LLM tuned for complex layouts. Built for sensitive and regulated document environments.
Data-agree
Azure Marketplace
Marketplace
Billing
Via Azure
Setup
Instant
Data location
Cloud managed
Direct SaaS
Cloud
Billing
Direct
Setup
Self-serve
Data location
Cloud managed
AWS-native
VPC deploy
Billing
AWS / direct
Setup
Pipeline-fit
Data location
Cloud managed
On-premise. DotsOCR
Private
Billing
Self-hosted
Setup
On your hardware
Data location
Data egress
