Idea
A benchmark platform evaluating LLM agents on complex office workflows to improve productivity tool automation for enterprises and developers
Research Paper
Core Innovation
This paper introduces OdysseyBench, a novel benchmark that tests LLM agents on long-horizon, multi-step office application workflows. It uses HomerAgents, a multi-agent framework that automates task generation and dialogue synthesis, enabling more realistic and comprehensive evaluation than prior benchmarks. This approach advances assessment of LLM capabilities in complex productivity scenarios.
Market Size (TAM)
$2–10B TAM, $1–2B SAM; assumption: growing enterprise adoption of AI-driven office automation and productivity tools.
Potential Customers & Pain Points
- Enterprises Needing Reliable AI Automation in Office Workflows
- AI Developers Lacking Realistic Benchmarks for Productivity Tasks
- Software Vendors Seeking to Integrate Smarter LLM Agents
Business Model
Offer OdysseyBench as a subscription-based SaaS platform for enterprises and AI developers with tiered access to benchmark datasets and evaluation tools.
Competitive Landscape
- Microsoft Office AI
- Google Workspace AI
- OpenAI GPT-4 API
Implementation Challenges
- Complexity of Realistic Workflow Simulation
- Integration with Diverse Office Applications
- Benchmark Adoption by Industry
Validation Strategy
- Pilot with AI developers to refine benchmark tasks
- Partner with enterprises to test LLM agents on real workflows
- Publish benchmark results to build community adoption
Research Paper Overview
OdysseyBench: Evaluating LLM Agents on Long-Horizon Complex Office Application Workflows
Summary
OdysseyBench is a benchmark designed to evaluate large language model agents on complex, long-horizon workflows across office applications like Word, Excel, PDF, Email, and Calendar. It includes two task sets derived from real-world and synthesized scenarios, requiring multi-step reasoning and long-term context understanding. The benchmark is created using HomerAgents, a multi-agent framework automating task generation and dialogue synthesis, providing a more realistic assessment of LLM capabilities in productivity tasks.