FinTech

Building a Context-Aware, Compliant LLM Agent for High-Volume Support Deflection

Building a Context-Aware, Compliant LLM Agent for High-Volume Support Deflection

Engineered a stateful conversational AI agent trained strictly on proprietary banking databases to autonomously resolve Tier-1 helpdesk tickets without regulatory breaches.

CoreTech System Thumbnail
CoreTech System Thumbnail
82%

Helpdesk Deflection Rate

82%

Helpdesk Deflection Rate

< 45s

Average Resolution Time

< 45s

Average Resolution Time

0

Compliance Breaches

0

Compliance Breaches

The Operational Friction

CoreTech Systems, a rapidly scaling digital banking platform, experienced an exponential surge in Tier-1 customer support requests regarding account configurations, balance discrepancies, and basic transaction disputes. Their human engineering and customer success queues were severely backed up, causing standard ticket resolution times to spiral past 36 hours. Legacy rule-based chatbots failed completely at comprehending conversational nuances, frustrating premium users and driving up customer churn rates. However, because they operate in FinTech, implementing an off-the-shelf LLM was a massive regulatory risk; a single "hallucinated" piece of financial advice could trigger severe legal penalties.

"We were terrified of customer-facing AI hallucinations that could land us in regulatory hot water or expose financial data. Stackgrid didn't just build a chatbot; they built a deterministic infrastructure. This architecture doesn't guess—it functions exactly within the mathematical guardrails defined, solving user problems instantly while keeping our legal and compliance teams entirely comfortable."