1. The Strategic Offering What to offer first: Start with AI & Automation basics (aligned with CBSE/NEP 2020) because they have the lowest barrier to entry and highest demand. Once established, layer in AR/VR as a "learning multiplier" (e.g., virtual field trips, anatomy labs) and later Spacetech (drones, satellite data modules) as a premium differentiator. New & Interesting: Move beyond "coding" to "Industry Problem Solving." Offer projects where students use real-world data (e.g., environmental data or city traffic patterns) to build AI models. This "real-world" focus excites both faculty and students. 2. Targeted Segments Focus on: Tier-1 & Progressive K-12 Schools: Those mandated by NEP 2020 to introduce vocational skills. Engineering Colleges: Look for institutions seeking to improve their "placement metrics" through industry-ready certifications. 3. Positioning as a Partner Do not pitch as a "vendor...
User Story: AI-Powered Automated Welding Quality Inspection ID: TMBS-WELD-01 Title: Real-time Welding Defect Identification Priority: High User Story Statement: As a Quality Control Engineer at TMBS, I want the AI inspection system to automatically analyze live video feeds from the welding stations, So that I can identify and categorize weld defects instantly and ensure only high-quality modules proceed to the next assembly stage. Acceptance Criteria (AC): AC 1: The system must accurately classify the welding output into the following categories: burn_through , crack , porosity , undercut , overlap , or good_weld . AC 2: The system must provide real-time inference during the welding process, triggering an alert if a defect is detected. AC 3: If a defect (0 through 4) is identified, the system must log the specific defect type and timestamp to the central tracking database. AC 4: The inspection UI must clearly highlight the detected defect on the video feed to assist the...