Streamline Financial Services Operations with Aisera’s AI Agents on AWS

By Alex Pazik, Sr. Technical Account Manager (ISV) – AWS By Utkarsh Contractor, Field CTO – Aisera

Artificial intelligence (AI) and Large Language Models (LLMs) are driving significant efficiency gains across the financial services and banking industry. Advances in LLMs, including the rise of domain-specific models tailored for particular industries, have opened new possibilities for integrating AI applications in complex workflows. Gartner predicts that by 2027, over 50% of enterprise large language models will be domain-specific, marking a 49% increase from 2023. This shift highlights the growing importance of specialized AI solutions in enterprise environments. Aisera delivers proprietary, domain- and industry-specific LLMs that provide precise, context-aware insights and intelligence. Leveraging Amazon Elastic Compute Cloud (EC2) and powerful P5 instance types with GPU-based instances, Aisera fine-tunes these models efficiently on AWS infrastructure. With Aisera’s AI Agent Platform, powered by AWS, organizations can deploy prebuilt AI agents and Amazon Bedrock Agents to automate and manage complex workflows through multi-agent collaboration.

Evaluating AI Agents

Aisera introduced a new benchmarking framework called CLASSic to evaluate AI agents in real-world enterprise scenarios. This framework assesses agents across five key dimensions: Cost, Latency, Accuracy, Stability, and Security. The evaluation revealed that domain-specific agents outperform general-purpose frontier LLM agents. In complex domains such as IT, FinTech, and HR, Aisera’s agents achieved 76.1% accuracy and a 99.3% success rate in refusing harmful prompts. Additionally, at $0.005 per request, these agents can reduce AI processing costs by up to 80% while maintaining competitive response times and accuracy.

Aisera’s AI Stack

Aisera’s AI architecture combines Large Foundation Models (LFMs), domain-specific LLMs, and task-specific Small Language Models (SLMs) to deliver high accuracy at a fraction of the cost of general-purpose LLMs. LFMs cover a broad range of models trained on diverse data types, while SLMs are optimized for efficiency with lightweight architectures requiring less computational power.

Figure 1: System of AI agents with universal agents, domain agents, and task agents. The AI Agent Platform offers prebuilt agents that automate high-volume, repetitive tasks such as customer inquiries, unauthorized activity detection, and compliance documentation. These agents integrate seamlessly with financial platforms like Zendesk, Genesys, NICE, and SAP, supporting use cases including:

Human-like customer support with real-time personalized chatbots
Account setup and management, including authentication and registration
Payment and deposit tracking with secure transaction verification
Real-time detection of unauthorized and anomalous activities
Automated document processing extracting insights from contracts and regulatory filings

Figure 2: Enterprise AI architecture diagram showing integration of Aisera’s AI Agent Platform with enterprise systems.

Case Study: Dave

Dave

Amazon OpenSearch

“Today’s consumer expects personalized assistance on demand. Partnering with Aisera has enabled us to address our members’ needs in real-time through AI. DaveGPT, powered by Aisera, fundamentally impacts how we scale by automating simple interactions and generating value through efficiency and supporting our members.”