REZINX
Transparent AI Solutions
Data Workflows & Document AI
We build custom, low-latency AI integrations for financial institutions and fintech startups, from automated auditing and transaction analysis to fraud detection and document search. Built with LangChain, LangGraph, and private vector nodes.
Capabilities
Every system is designed to secure transactional privacy and speed up regulatory processing.
Real-time evaluation of transaction records, ledger activity, and customer files against standard financial regulations. Flags compliance deviations automatically with precise audit paths.
Extraction of financial statements, balance sheets, and management notes from SEC filings (10-K, 10-Q) directly into structured databases. Power fast analysis loops without manual copying.
LangGraph agents that trace transaction flows, flag anomalous activity, and alert fraud teams with structured reasoning logs. Reduces false-positive indicators on payment paths.
Automated data aggregation from bank accounts, credit scores, and statements to generate risk summaries for underwriters. Speeds up loan approval turnaround periods.
LLM-powered summarization of market news, earnings calls, and asset performance data for wealth managers. Returns key signals in customizable formats.
High-performance streaming data pipelines that connect AI services with active ledger databases without delaying transaction execution times.
Enterprise Security
We build single-tenant vector database environments that encrypt transaction logs and private ledger columns before processing them through LLM endpoints.
Our finance AI stack connects LangChain pipelines with secure database connectors, executing risk validation models locally without cloud parameter leakage.
Designed around local bank protocols, data privacy mandates, and SECP/SBP guidelines.
Optimized endpoints built on FastAPI for millisecond-level inference and decision checks.
Every credit qualification or fraud flag includes clear step-by-step reasoning logs.
Tight logical separations ensure customer files and values never cross access controls.
We deploy database vector nodes within secure virtual networks (VPCs) with strict IAM rules and row-level encryption. Your core financial logs are scrubbed of personal identifiers prior to any indexing or model parsing.
Yes. Our extraction pipelines use advanced OCR and table structures recognition models to parse balance sheets and earnings tables without losing their spatial context or alignment.
The LangGraph agent creates a structured reasoning trace detailing why the transaction was flagged, which rules were violated, and the corresponding similarity score of anomalous activities.
Yes. For institutions requiring high levels of security, we can deploy open-source LLMs (like Llama-3-70B) directly on your physical local servers, removing any dependencies on outside networks.
A custom financial auditing or compliance system takes between 6 to 10 weeks, depending on database size, regulatory checks, and downstream alert systems integrations.
Ready to build secure financial auditing, RAG search, and automated transaction pipelines? Book a free consultation with our fintech AI architects.
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