
Enterprise systems still run on decades of undocumented Oracle PL/SQL — packages nobody wants to touch because nobody's sure what they'll break. Generic AI code-review tools skim the surface; they don't reason about PL/SQL's stateful, transaction-heavy idioms. OraLift points at a folder of PL/SQL packages and produces four things: a call-dependency graph, a plain-English spec for every procedure and function, a generated REST scaffold (FastAPI routes + pytest stubs), and — the part most tools skip — a risk report naming exactly what can't be safely auto-migrated: dynamic SQL, autonomous transactions, package-level state, and DBMS_* calls. That risk report isn't an LLM guessing; it's four deterministic rules, so every flag is defensible and traceable to a specific line. We built this to lean directly into what IBM Bob is already best at: legacy and enterprise modernization. Rather than compete with the generic code-review bots this hackathon will be full of, OraLift targets an underserved niche — Oracle PL/SQL — grounded in real backend experience with the language. Bob was used throughout the 48-hour build: Architect Mode to plan each module's interface before writing code, Code Mode to implement extraction, risk-scanning, graphing, spec generation, and scaffolding. Stack: Python + FastAPI, a deliberately regex-based extractor (not a full grammar — a 48-hour tradeoff, not an oversight), networkx + Mermaid for the dependency graph, one Claude API call per unit for specs, Jinja2-generated REST/pytest scaffolds, and a Streamlit UI tying it all together.
27 Sep 2026

Viva voce and thesis defenses are mandatory across universities in South Asia and Europe — but there's no way to actually rehearse one. Flashcards test recall. Viva tests whether you can think under real, unpredictable questioning, out loud, the way a real exam committee does. Viva is a voice agent, not a transcription tool. You speak your answer; AssemblyAI's streaming STT transcribes it in real time; a custom turn-controller decides when you've actually finished (allowing natural pauses instead of cutting you off after your first "um"); an LLM examiner then decides whether to press deeper on a weak spot or move to a new concept — and asks that follow-up out loud. At the end of the session, Viva produces a written verdict: which concepts you clearly defended, and which you couldn't hold up under questioning. Built with: AssemblyAI Universal-Streaming (real-time STT), a browser-based turn-controller for end-of-answer detection, an LLM for adaptive questioning and the final verdict, and Web Speech Synthesis for spoken output — all running on Vercel serverless functions so the AssemblyAI API key never touches the browser. This isn't a chatbot with a microphone bolted on — the entire branching logic only exists because of real-time speech. There's no equivalent product for the millions of students who face a viva every semester with no way to practice one.
30 Sep 2026