Automated financial analysis
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Endex built an AI Analyst platform that leverages OpenAI's reasoning models (GPT‑4o, o1‑mini, o1‑preview, o3‑mini, and o1 vision) to retrieve, analyze, and synthesize complex financial data. The solution integrates internal data, public disclosures, and financial reports to automate processes such as due diligence, earnings analysis, and investment committee memo preparation using reinforcement learning fine-tuning and performance tracking, transforming traditional manual workflows into streamlined AI-driven processes.
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70% preference in blind testing and response latency reduced to one‑third of traditional methods.
71
AI use cases in
Finance
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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.
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Rogo, an AI finance platform, uses OpenAI's GPT-4 to provide real-time financial intelligence to investment professionals, automating tasks like meeting prep, company profiling, and market research. By fine-tuning OpenAI's models and integrating financial datasets like S&P Global, Crunchbase, and FactSet, Rogo helps shift focus from manual work to high-value decision making.
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Deployed Microsoft Copilot integrated with Microsoft Azure and Microsoft 365 to automate drafting, reporting, training material creation, and meeting note taking, enabling employees to focus on higher-value tasks through secure, compliant workflow automation and continuous feedback
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166
companies using
Customer Agents
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Tidio integrated Anthropic’s Claude model to develop their Lyro AI agent, automating customer support interactions across both live chat and email channels. They implemented a network of specialized AI agents for conversation rating, summarization, and a dynamic routing system that selects the optimal API between native Anthropic API and Google Cloud Vertex AI based on performance metrics, streamlining support workflows and enabling personalized product recommendations.
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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.
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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.
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74
solutions powered by
OpenAI
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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.
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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.
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Booking.com integrated OpenAI’s GPT models with its extensive proprietary data on properties, pricing, and availability to develop an AI Trip Planner that converts natural language queries into personalized itineraries. The team rapidly built the solution in 10 weeks by leveraging existing ML infrastructure and fine-tuning the model on both structured and unstructured data, which also powered additional tools like Smart Filters, Property Q&A, and AI Review Summaries. This innovation transformed travel discovery, search, and customer support processes.
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162
AIÂ use cases in
Global
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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.
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Booking.com integrated OpenAI’s GPT models with its extensive proprietary data on properties, pricing, and availability to develop an AI Trip Planner that converts natural language queries into personalized itineraries. The team rapidly built the solution in 10 weeks by leveraging existing ML infrastructure and fine-tuning the model on both structured and unstructured data, which also powered additional tools like Smart Filters, Property Q&A, and AI Review Summaries. This innovation transformed travel discovery, search, and customer support processes.
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Bito implemented AI-powered developer agents by integrating Anthropic's Claude and leveraging Claude 3.7 Sonnet for advanced reasoning into its code review and coding workflows. They utilized Anthropic’s robust API and developer-friendly infrastructure to embed an AI Code Review Agent and Bito Wingman directly within developers’ Git workflows and popular IDEs, enabling automated analysis of pull request diffs and code architecture. This integration streamlined code review, error detection, and code generation processes while upholding security standards.
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