AI case study

Scalable customer support

by
Nubank
Context

Nubank implemented a custom AI-driven enterprise search solution by integrating GPT‑4o and GPT‑4o mini with fine-tuned domain-specific models and Retrieval-Augmented Generation techniques, enabling employees to access FAQs, policies, and internal documents rapidly. They also developed a call center copilot using GPT‑4o that integrates the bank’s knowledge base and chat history to provide real-time conversation summaries, next-reply suggestions, and step-by-step guidance for agents, and launched an AI assistant to handle Tier 1 inquiries. Furthermore, Nubank piloted a fraud quality assurance system using GPT‑4o vision to analyze transactions and visual data, ensuring robust fraud detection according to regulatory requirements.

Results

Reduced chat response times by 70%, resolved 55% of Tier 1 inquiries, achieved 2.3x faster query resolution, with over 5,000 employee users and 2M+ chats monthly.

Results not reported in the source
Industry
Finance
Published
March 7, 2025
Agent type
Employee Agents
AI provider
OpenAI
ICE score
567
The ICE framework in this database provides a quick way to assess the feasibility and potential impact of AI use cases, with higher scores signaling more actionable opportunities.
‍
Impact: Potential benefits to the business.

‍Confidence: Likelihood of achieving expected results.

‍Ease: Simplicity of implementation in terms of resources and time.

‍ICE Score: Calculated by multiplying the component scores.

Note:
Each score is AI-generated based on available data and should be viewed merely as a general guideline for deeper exploration of the use cases.
Impact
9
Confidence
9
Ease
7

77

AI use cases in

Finance

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Deutsche Bank

Finance
Use case
Faster research reports
Context

Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.

Models/tools

Intuit

Finance
Use case
Faster tax form processing
Context

Intuit integrated Google Cloud’s Document AI and Gemini models into its GenOS platform to automate the autofill of ten common U.S. tax forms, including complex 1099 and 1040 forms. The solution extracts and categorizes data from uploaded documents, drastically reducing manual data entry for TurboTax customers. This integration streamlines tax preparation workflows and improves speed and accuracy.

Models/tools

Block

Finance
Use case
Democratized data access
Context

Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.

Explore industries

321

companies using

Employee Agents

See All
Use case
Fast content creation
Context

Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.

Models/tools
...
2
Use case
Reduce report writing burden
Context

Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.

Models/tools
...
2
Use case
Faster retail transformation
Context

TCS partnered with Google Cloud to integrate advanced AI and generative AI capabilities into retail service offerings. They launched the Google Cloud Gemini Experience Center at their Retail Innovation Lab in Chennai, enabling retail clients to ideate, prototype, and co-develop tailored AI solutions that optimize supply chain, warehouse receiving, customer insights, and content creation. This approach automated processes using tools like Vertex AI Vision for warehouse receiving and leveraged Vertex AI with Gemini 1.5 Pro and speech-to-text to transform service centers.

Models/tools
...
4
Explore agents

78

solutions powered by

OpenAI

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Use case
Actionable workspace content
Context

Notion reimagined its platform by deeply integrating OpenAI’s GPT‑4o, GPT‑4o mini, and embeddings across its core features. They prototyped an AI writing assistant during a hackathon and then built internal tools to rapidly evaluate and deploy new models, transforming workflows in search, note-taking, and knowledge management from static content to interactive, actionable insights.

Models/tools
...
2
Use case
Rigid support workflows
Context

Zendesk integrated OpenAI's models to create adaptive AI service agents that autonomously manage customer conversations and execute resolution tasks. They implemented a multi-agent architecture featuring task identification, conversational RAG, procedure compilation, and procedure execution agents integrated with existing support workflows through API calls and natural language procedure definitions, while providing real-time chain-of-thought visibility. This solution transitions from traditional intent-based bots to a hybrid model of scripted and generative reasoning, streamlining customer service processes.

Models/tools
...
2
Use case
Faster finance/legal research
Context

Hebbia built Matrix, a multi-agent AI platform that orchestrates OpenAI models including o3‑mini, o1, and GPT‑4o to automate complex financial and legal research tasks. The platform decomposes intricate queries into structured analytical steps and integrates modules like OCR, hallucination validation, and artifact generation to process complete documents, creating an infinite effective context window. This solution streamlines due diligence, contract review, and market research workflows, drastically reducing manual processing time.

Models/tools
...
3
Explore AI providers

40

AI use cases in

South America

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Use case
Fast registration & safety
Context

704 Apps implemented an AI solution using Vertex AI and Gemini 1.5 Pro to automate and accelerate driver identity verification and safety monitoring. They integrated these AI models into their existing cloud infrastructure built on Firebase and Google Kubernetes Engine, centralizing real-time data for document validation and audio sentiment analysis. The system alerts the central monitoring team when risk-related language is detected, streamlining operational decision-making and enhancing security.

Models/tools
...
2
Use case
Automated digital marketing
Context

Advolve, a B2B SaaS company, uses Claude from Anthropic as the central orchestrator of their AI platform to automate digital marketing across multiple platforms. Claude enables them to manage millions of ads simultaneously, automate workflows, generate creative assets and copywriting, and dynamically allocate budgets for optimal return on ad spend.

Models/tools
...
1
Use case
Scalable, cost-efficient platform
Context

Wited revamped its learning platform by partnering with Google Cloud and Axmos Technologies to migrate from legacy systems to a robust infrastructure using Cloud SQL, Cloud Storage, Compute Engine, and Google Kubernetes Engine, ensuring reliable scalability and stability for high user demand. They then integrated generative AI by deploying Gemini and Vertex AI to power Max AI—a 24/7 virtual assistant that supports students through real-time assistance and educational guidance—thereby streamlining support processes and enabling the team to focus on innovation.

Models/tools
...
2
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Thoughts & ideas