Project Overview We are seeking an experienced AI Development Agency or Senior AI Engineer/Engineering Team to design, develop, and integrate a comprehensive suite of Agentic AI assistants for our ERP system. The objective is to automate complex administrative workflows, enhance student self-service capabilities, and deliver a next-generation user experience through conversational AI, OCR document verification, and interactive Video Avatars. Scope of Work (The 7 Key Use Cases) The selected vendor will be responsible for building the following Agentic AI components and seamlessly integrating them into the ERP architecture: Use Case 1: Student Profile Update Agent An AI assistant that enables students to instantly update their profile information (mobile number, email, address, profile photo) through a conversational interface. The agent must automatically sync and validate these changes with the backend. Use Case 2: Document Verification & Updation Agent An AI and OCR-powered agent designed to automatically verify the authenticity of student-uploaded identity and supporting documents. It must extract key fields, cross-check them against system data, and detect mismatches or potential fraud. Use Case 3: Service Request Agent A chat-based agent allowing students to submit internal service requests (e.g., certificate issuance, leave applications, section transfers). The AI must intelligently categorize the intent of the request and automatically route it to the appropriate institutional department. Use Case 4: Autonomous "Smart-Loader" Agent Multi-Source Ingestion: The agent must accept Excel (.xlsx), CSV, and unstructured/semi-structured PDFs (e.g., scanned result sheets or fee receipts). Zero-Template Mapping: Instead of requiring a specific file format, the agent should: Analyze & Classify: Read the uploaded file to identify what data it contains (e.g., "This is a list of Semester 3 Exam Marks"). Intelligent Field Mapping: Use semantic reasoning to map source columns (like "Student ID", "UID", or "Roll No") to the correct ERP table fields (e.g., student_master_id). Data Preview & Transformation: Before any insertion, the agent must present a "Staging Grid" showing the user exactly how the data was interpreted, highlighting any rows that failed validation (e.g., missing values or invalid date formats). Final Confirmation: Data is only pushed to the production database after the user clicks "Confirm & Import" on the preview. Use Case 5: Student Self-Information Assistant A secure, logged-in AI chatbot that allows students to query and retrieve their personal academic and financial data instantly (e.g., timetables, enrolled courses, pending fee bills, hall tickets, and exam results). Use Case 6: Website-Based Information Assistant A 24/7 public-facing chatbot embedded on the institution's website. It must handle public queries from prospective students and visitors (e.g., admission processes, course details) while also providing a secure login gateway for current students to ask personalized questions. Use Case 7: Video Avatar Conversational AI A friendly, on-screen, interactive virtual character that interacts with users in real time. It must utilize Speech-to-Text (STT) to understand spoken queries and Text-to-Speech (TTS) alongside realistic facial and hand gestures to deliver spoken answers. Technical Requirements & Expected Skills AI/LLM Frameworks: Strong expertise in Large Language Models (OpenAI, Anthropic, or open-source), LangChain, LlamaIndex, and prompt engineering. Vision & OCR: Experience integrating OCR (Optical Character Recognition) APIs (e.g., Google Cloud Platform (GCP) or Microsoft Azure AI-powered OCR ) for automated document data extraction. Conversational Avatars: Familiarity with generating real-time interactive video avatars (e.g., HeyGen, Synthesia, or custom WebRTC-based avatar rendering) tied to STT/TTS pipelines. Data & File Handling: Ability to build robust data parsing pipelines for Excel/CSV files and implement automated batch processing and rollback features. API & Backend Integration: Proven ability to build middleware and integrate AI agents securely with complex ERP databases via RESTful APIs. Vision-Language Models (VLMs) or Advanced OCR: Ability to extract tabular data from PDFs using tools like LayoutLM, AWS Textract, or Azure Document Intelligence. Semantic Mapping Engine: Experience using LLMs for "Schema Matching"—the ability to find the relationship between two different data structures without manual coding. Validation & Sanitization Layer: A robust Python/Node logic layer to sanitize data (e.g., converting "Jan 12th, 2026" into a standardized YYYY-MM-DD format) before it hits the ERP. Transaction Safety: Implementation of a "Stage-then-Commit" architecture where data is held in a temporary buffer for user review. Requirements for Vendor Quote Submission To be considered for this project, please provide a comprehensive quote that includes: Company/Team Profile: Highlight your previous experience in developing Agentic AI, ERP integrations, and conversational avatars. Please include case studies or a portfolio. Proposed Technology Stack: Detail the specific LLMs, OCR tools, avatar rendering engines, and frameworks you intend to use for these use cases. Estimated Timeline & Milestones: Provide a project timeline breaking down the development, testing, and deployment phases for each of the 7 use cases. Cost Estimate: An itemized pricing structure (fixed bid or time-and-materials) covering development, API integrations, testing, and post-launch support.