Reducing document processing time by 97% with AI on AWS
A production-grade, AWS-native IDP platform processing 10,000+ documents a day at 99%+ accuracy in under 45 seconds — eliminating manual data entry across invoices, KYC packets, and loan applications.
- Industry
- Financial Services · Insurance · Healthcare
- Region
- Singapore (ap-southeast-1) · ASEAN
- Platform
- Amazon Textract + Bedrock Claude 4.5
- Compliance
- PDPA · MAS TRM · HIPAA
97%
Reduction in processing time (15 min → 45 sec)
30–75×
ROI vs. manual cost (USD 2–5 → 0.03–0.08 per doc)
99%+
Field extraction accuracy with HIL review
MAS TRM & PDPA compliant — KMS CMK per client
10 document types — invoices, KYC, contracts, and more
14 FTEs redeployed to higher-value analytical work
Large enterprises across financial services, insurance, healthcare, and government process millions of documents a year through manual workflows — slow, error-prone, and linearly expensive. A leading Singapore financial services group set out to eliminate manual data entry from its accounts payable, KYC onboarding, and loan processing operations.
With 15–20 FTEs re-keying data from invoices, contracts, and identity documents into SAP and Salesforce every day, the client needed a solution that could handle 10,000+ documents daily at 99%+ accuracy — while staying fully compliant with Singapore's PDPA and MAS TRM requirements. Legacy OCR had already failed them. A new approach built natively on AWS was the answer.
Document processing at scale surfaces a consistent set of failures that manual workflows and legacy OCR cannot solve:
- Manual entry introduced 1–3% field error rates, causing downstream reconciliation failures and payment disputes.
- Invoice approval cycles of 14–30 days delayed supplier payments and attracted penalty interest.
- Doubling document volume required doubling headcount — costs scaled linearly with no automation leverage.
- Legacy OCR (ABBYY, Kofax) broke on new supplier layouts and lacked semantic understanding of content.
- Documents arrived in English, Mandarin, Bahasa Malaysia, and Tamil with no unified multilingual pipeline.
- No immutable audit trail existed to satisfy MAS TRM and PDPA regulatory requirements.
- Valuable data locked inside unstructured documents stayed inaccessible to analytics and reporting.
Algorims deployed its Intelligent Document Processing platform inside the client's AWS account — a cloud-native system that converts unstructured documents into structured, validated, searchable data at above 99% accuracy and below USD 0.08 per document.
Cost-optimised 5-tier pipeline
Each document is routed to the cheapest AI tier that meets its accuracy requirement — from Textract-only at USD 0.015/page for structured forms, up to full Bedrock + Human-in-the-Loop at USD 0.073/page for critical regulated documents. Bedrock Claude 4.5 classifies every document type, extracts fields with semantic understanding, and applies configurable business-rule validation — all within 45 seconds end-to-end.
Confidence-gated human review
A Human-in-the-Loop layer powered by Amazon A2I routes only genuinely ambiguous fields to reviewers, with a side-by-side bounding-box interface that cuts review time from 15 minutes to under 3 per document. Every correction feeds back into the extraction model, driving HIL routing from 18% at launch to under 4% within 90 days — a system that gets more accurate the longer it runs.
Straight-through enterprise integration
Pre-built connectors deliver structured JSON directly into the client's SAP (RFC/BAPI), Salesforce (REST), and ServiceNow systems — with HMAC-signed payloads, retry logic, and a full immutable audit trail. All processing runs within the client's own account in ap-southeast-1, ensuring data sovereignty and regulatory compliance from day one.
Built entirely on AWS managed services — no proprietary models, no vendor lock-in, no data leaving the client's account:
Amazon Textract
OCR, forms, and table extraction across 10 document types.
Amazon Bedrock (Claude 4.5)
Classification, semantic field extraction, and summarisation.
Amazon A2I
Managed Human-in-the-Loop review with confidence-gated routing.
AWS Step Functions (Express)
End-to-end workflow orchestration with parallel fan-out.
AWS Lambda (Graviton3)
Serverless workers — 20% more cost-efficient than x86.
Amazon SQS + DLQ
Ingestion queuing, parallel page processing, zero message loss.
Amazon DynamoDB
Job metadata, extraction results, and 7-year audit trail.
Amazon OpenSearch
Full-text search across millions of records in under 2 seconds.
Comprehend + Translate
Entity extraction and multilingual processing across four languages.
Amazon S3 + KMS
Encrypted storage with lifecycle policies and per-client CMK.
API Gateway + CloudFront
REST API delivery and web-portal CDN.
WAF · Shield · VPC · CloudTrail
Security, network isolation, and audit logging.
Does the platform work with documents in languages other than English?
Yes — English, Mandarin (Simplified and Traditional), Bahasa Malaysia, and Tamil via Amazon Translate and Comprehend, making it purpose-built for ASEAN operations.
Does client data leave their AWS account during processing?
No. All AI inference, storage, and processing run entirely within the client's own AWS account and region. Data never transits Algorims infrastructure.
How does it handle new document formats from new suppliers?
New layouts are mapped automatically to the existing extraction schema without template updates. New document types are configured within 5–10 business days.
What compliance certifications does the platform support?
Designed for PDPA (Singapore), MAS TRM, HIPAA, Privacy Act 1988 (Australia), and GDPR — with controls implemented at the AWS architecture level, not applied as an overlay.
How long does implementation take?
Standard implementation runs 16 weeks across four phases: Foundation → AI Pipeline → Portal & Integrations → Hardening & Launch.
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