Ingestion agent
Initialises a case, validates bank, account and loan metadata, stores documents securely and starts the pipeline.
Try “KYC”, “Bedrock”, “Claude”, “insurance” or “ISO”.
Case study · FinTech / Lending / Financial Analysis
An agent-orchestrated document platform that turns PDF bank statements from 25+ Indian banks into structured, decision-ready insight for lenders and auditors.

Results at a glance
The challenge
Bank statement reconciliation is critical but manual. Every bank uses different formats, layouts and transaction semantics, which makes automation hard at scale.
The solution
Skugal built a case-based dashboard on top of OCR and NLP pipelines, with autonomous agents coordinating ingestion, parsing, validation, merging and analytics asynchronously.
Initialises a case, validates bank, account and loan metadata, stores documents securely and starts the pipeline.
Extracts transactions from diverse formats with OCR and NLP, adapting to layout variations.
Classifies credits, debits, EMIs, charges and balances, flags anomalies and applies bank- and loan-specific rules.
Merges statements into one view, computes EOD balance, inflows, outflows and liabilities, and generates JSON and Excel outputs.
Balance trends, income vs expense, EMI tracking, debit/credit breakdowns and anomaly indicators per case.
How it works
Business impact
Nexensus launched a production-grade platform that converts raw bank statements into clean, decision-ready insight for lending, audit and compliance, with minimal manual effort.
Technology
Automate. Analyse. Scale.
Next step
Tell us about the workflow or product. We’ll come back with an architecture, a delivery plan and where AI agents fit.