Registration search & state-wise aggregation
Queries Salesforce registration records, groups and merges them by state, removes duplicates and prepares structured inputs for browser automation.
Try “KYC”, “Bedrock”, “Claude”, “insurance” or “ISO”.
Case study · Lending / Financial Services
An AI-orchestrated operations layer that runs Lendly’s data ingestion, reconciliation, CRM updates and customer engagement on schedule, with human approval where it matters.

The challenge
Lendly’s critical workflows were spread across Salesforce, email and document ingestion, financial transaction files, enrichment tools and review management. The challenge was not building one automation but orchestrating many interdependent workflows reliably.
The solution
Skugal built a modular set of production-grade agents and workflows. Each one runs on a schedule, validates data, detects missing or duplicate records, triggers alerts or approvals, and safely updates downstream systems.
Queries Salesforce registration records, groups and merges them by state, removes duplicates and prepares structured inputs for browser automation.
Pulls daily transaction files from email, stores them in Dropbox and AWS, filters irrelevant records, calculates GST and gross values, and alerts on missing history.
Aggregates records by month, updates financial tables, marks processed rows and runs idempotently so re-runs are always safe.
Distributes eligible Salesforce accounts across employees within defined limits and writes assignment status back to the CRM.
Orchestrates asynchronous PhantomBuster jobs with secure session handling, polling and result parsing.
Collects and deduplicates reviews, drafts replies with AI and routes every reply for approval before anything is published.
How it works
Business impact
Lendly moved from human-driven back-office processes to a structured, agent-driven automation layer with predictable daily execution, safer financial data handling and controlled AI usage with human approvals.
Technology
Lendly didn’t need more tools. It needed reliable automation, built the right way.
Next step
Tell us about the workflow or product. We’ll come back with an architecture, a delivery plan and where AI agents fit.