We present the PIO system for the FinEval 2026 / FinNLP Multilingual Financial Language Understanding Challenge. Our submission follows the API-based agent/workflow track: all model calls go through OpenRouter and use meta-llama/llama-3.3-70b-instruct (≈70.6B parameters). We address all three subtasks with task-specific pipelines that combine LLM prompting with high-precision rules and schema constraints. On the public leaderboard our scores are entity micro-F1 0.9748 (Greek NER), accuracy 0.9333 (Japanese ICR), and ROUGE-1 1.0000 (PolyFiQA). We describe the design choices behind each subtask, the failure modes we observed, and simple post-corrections that yielded large gains on Subtask 1.

Equitable access to quality education remains a critical challenge in Nigeria, where millions of students prepare annually for standardized examinations (WAEC, NECO, JAMB) with limited access to personalized tutoring (Badei et.al, 2024). This research presents EduNaija AI Tutor, a multi-agent Retrieval-Augmented Generation (RAG) system designed to democratize educational support through AI-powered tutoring aligned with Nigerian curricula. The system integrates conversational AI with document-based question answering, automated assessment generation, and multilingual support for English, Yoruba, Hausa, and Igbo. Using LangChain for agent orchestration, OpenAI GPT models for natural language processing, and FAISS for vector retrieval, the system enables students to interact with educational content through natural language queries while maintaining cultural relevance through Nigerian-contextualized examples and conventions (Chukwuma et.al, 2024). The multi-agent architecture comprises five specialized components: a main orchestrator, explanation agent, quiz generation agent, web search agent, and RAG agent for processing uploaded educational materials. Preliminary evaluation demonstrates the system’s capability to provide curriculum-aligned explanations, generate practice assessments, and answer questions from uploaded textbooks and study materials. This work contributes a culturally-aware educational AI framework addressing linguistic diversity and curriculum alignment challenges in African educational contexts, while leveraging open-source tools for reproducibility and accessibility (Shoukat et.al, 2025).