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Shashank Ha@shashankh31
1
Events attended
1
Submissions made
India
3+ years of experience
About me
I’m a software engineer who believes traditional software engineering is evolving faster than most people realize. Technology is accelerating at a pace that is difficult to predict, and the way we build, work, and create value may change completely in the coming years. I’m currently at a turning point—exploring what kind of company I should build, where I can create meaningful impact, and how I can position myself for the future. I may not have every answer yet, but I’m deeply curious, ambitious, and determined to build something valuable in a world being rapidly reshaped by AI.
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🤓 Latest Submissions
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Achyrix: AMD Gemma Restaurant Intelligence
Achyrix is an approval-gated restaurant operations copilot. Restaurant teams make prep, purchasing, and menu-availability decisions using fragmented signals such as recent sales, forecast demand, on-hand inventory, safety stock, reservations, catering orders, supplier delays, open purchase orders, and refunds. A generic chat assistant may overlook these interactions and produce a plausible but unsafe recommendation. Achyrix uses Google Gemma hosted on AMD infrastructure as its primary reasoning layer. It sends a compact, redacted operational snapshot to an OpenAI-compatible Gemma endpoint and requests an evidence-backed, structured recommendation. Before anything reaches the user, the application validates the response deterministically by checking tenant, outlet, item, and date scope; safe prep and stock limits; known-cost bounds; registered tool permissions; and manager-approval requirements. The model cannot silently alter prep, procurement, or menu availability. The project is containerized and includes a controlled fallback path. If the model cannot respond safely within its request budget, Achyrix returns deterministic guidance instead of inventing an answer. We built a 13-scenario evaluation set covering waste, low stock, purchase orders, supplier delays, promotion spikes, catering, refunds, unavailable items, cross-outlet imbalance, conflicting signals, missing data, malformed data, and normal no-action cases. This combines practical AI assistance with the trust and guardrails restaurant operators need.
13 Jul 2026
