Built by ZekaNor.AI, Fraud Copilot AI turns raw transactions into risk scores, explanations, and investigation workflows — powered by AWS Bedrock, DynamoDB, and Streamlit.
Flagship project: Fraud Copilot AI — multilingual fraud analytics, analyst-friendly explanations, and voice summaries using AWS Polly.
Fraud Copilot AI is the flagship, but I also build the data plumbing, analytics, and supporting tools that make a fraud platform actually work in production.
Transaction scoring, anomaly detection, case routing, and dashboards designed for fraud and risk teams.
Clean, reliable event streams and history tables so Fraud Copilot AI has the data it needs.
Consoles and reports that fraud, operations, and finance teams can actually use every day.
Secure deployments of Fraud Copilot-style systems, with monitoring and CI/CD.
2-week to 4-week pilots of Fraud Copilot AI with your data, so you can prove value quickly.
Helping founders, fraud leaders, and data teams shape their fraud roadmap around tools like Fraud Copilot AI.
The patterns and controls behind Fraud Copilot AI transfer well to these domains.
Card fraud, KYC, AML, chargebacks, and risk orchestration.
Identity fraud, credit abuse, and application risk.
Account takeover, promo abuse, refund scams, and bots.
Buyer/seller fraud, fake inventory, collusion patterns.
Suspicious claims, network patterns, anomaly scoring.
Early-stage fraud defenses without building a full team yet.
Step 1
Clarify fraud problems, data sources, and success metrics.
Step 2
Shape the Fraud Copilot AI-style console around your workflows.
Step 3
Implement models, rules, dashboards, and explanations on AWS.
Step 4
Roll out, monitor, and iterate based on analyst feedback.
A real-time fraud detection and investigation console built with AWS Bedrock, DynamoDB, and Streamlit. In tests, it reduced manual review time by around 38% for sample workloads.
Tech stack: AWS Bedrock • Streamlit • DynamoDB • Lambda
We can usually kick off within 3–5 business days after scope sign-off. Initial Fraud Copilot-style pilots run 2–4 weeks depending on data access.
We design with least-privilege access, encryption in transit/at rest, and SOC2-friendly patterns. PHI/PII projects are isolated with strict access controls and logging.
Yes — retained support and fractional data / fraud analytics options with clear SLAs and monthly reporting.
We’re cloud-agnostic with deep AWS experience. Fraud Copilot-style designs can be adapted to your data warehouse, event systems, and BI tools.
Share a bit about your fraud / risk challenges and data. I’ll reply within 24 hours with honest next steps — including if we’re not the right fit.