Enterprise AI Agent Deployment — Financial Services

Manual at scale — unsustainable

The client's customer onboarding process required manual review of compliance documents — KYC forms, regulatory filings, identity verification — across hundreds of daily submissions. Analysts spent 60–70% of their time on document extraction and classification tasks that were error-prone and slow.

Key pain points:

• 3–5 business days average onboarding time
• High error rate in manual document classification
• Compliance risk from inconsistent review processes
• Scaling bottleneck with headcount as primary lever

Multi-agent AI system with LLM orchestration

Kryst Digital architected a multi-agent AI system using large language models (LLMs) for document understanding, combined with deterministic rule engines for compliance checks. The system operates as a coordinated pipeline of specialised agents.

• Intake agent for document ingestion and normalisation
• Classification agent using fine-tuned LLM
• Extraction agent for structured data retrieval
• Compliance validation agent with rule-based checks
• Escalation agent routing edge cases to human reviewers
• Full audit trail and explainability layer

73% faster. 99.2% accurate. In 8 weeks.

The system went live in 8 weeks from project kickoff. Within the first month of operation, the results were unambiguous — processing time dropped from days to hours, accuracy improved dramatically, and compliance risk was materially reduced.

• 73% reduction in manual processing time
• 99.2% document classification accuracy
• Onboarding time reduced from 3–5 days to under 4 hours
• Zero compliance incidents post-deployment
• Analyst capacity redirected to high-value advisory work