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Recently built and launched Calorie AI: Weight Tracker for a client, an AI-powered nutrition tracking app designed to make calorie tracking smart and simple.
Instead of manually searching for meals and adding calories, users just point their camera at food for instant AI-powered calorie estimates.
I handled full mobile development and added features like:
– AI food recognition
– AI meal tips and daily insights
– Barcode scanner for packaged foods
– Macro tracking (calories, protein, carbs, fats)
– Exercise logging, calorie & weight tracking
– Smart reminders for meals and weight
– Multilingual 17-language support
Now live on Google Playstore: https://play.google.com/store/apps/details?id=com.calai.tracker&pcampaignid=web_share
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Hey everyone, this is my submission for the @Rive HMI Challenge: NEURAL ROBOT CONTROL.
This project explores a system where a human can remotely operate a maintenance robot inside a radioactive reactor core — an environment too dangerous for direct interaction. The robot acts as a physical extension of the operator.
The experience is built as a clear flow:
connection → system sync → diagnostics → navigation → scan → operation
The AR interface serves as the main point of view, overlaying essential information directly onto the environment. It shows navigation guidance, target location, and system feedback while keeping the view minimal and unobstructed.
The robot includes a self-diagnostic HUD for maintenance teams, displaying real-time data such as battery, CPU temperature, mechanical stability, and radiation exposure. It also features a small onboard display that communicates system states like connecting, loading, warnings, errors, and movement direction.
The focus of this project is how motion communicates system behavior. Each transition reflects a state change, helping users understand what the robot is doing at any moment.
Built using State Machine, Data Binding, and Layout in Rive.
so good!! 🔥
⚖️ Legis-Ops: The Autonomous Legal Command Center
The Problem: > Small to medium businesses (SMBs) and startups sign hundreds of contracts (NDAs, SaaS agreements, vendor contracts) but lack dedicated legal teams to track them. Crucial details—like auto-renewal dates, non-standard liability caps, and hidden deliverables—get buried in unstructured legalese. This exposes companies to massive financial risk and missed deadlines.
The Solution: > Most Notion AI agents focus on simple tasks like summarizing meeting notes. Legis-Ops solves a highly complex, high-stakes business problem. It is an autonomous Custom Agent that acts as a 24/7 Legal Operations manager. It doesn't just read text; it parses dense legal jargon and automatically converts it into structured, actionable, relational data.
How It Works (System Architecture):
📥 Automated Risk Intake: Users paste raw, unstructured contract text into the Contracts Intake database.
🧠 Rules-Based Parsing: The Legis-Ops agent cross-references the contract text against a centralized Company Playbook database containing the company's acceptable terms (e.g., "Must be Net-30 payment terms," "Liability must be capped").
🚨 Automated Risk Scoring: The agent autonomously assigns a 1-10 Risk Score based on deviations from the Playbook, writes a summary of the dealbreakers, and flags the contract for manual review if the risk is too high.
⚙️ Relational Output & Task Extraction (The Magic Step): The agent scans the legalese for hidden duties and deliverables. It then automatically generates linked, individual tasks in an Obligation Tracker database, assigning deadlines and connecting them back to the original contract.
The Impact: > Legis-Ops turns hours of tedious, error-prone manual contract review into a 10-second automated workflow. It centralizes risk management, protects the company's bottom line, and ensures no contractual obligation is ever missed again.
Check out the AI Agent I built: https://www.notion.so/agent/33406fe1-4c8c-8041-a1c9-0092910e4d17
#NotionAgent #NotionAI #Buildathon #LegalOps #AIWorkflow #Automation #RelationalDatabases #Productivity #Contra #FutureOfWork
Wow this is great! Can definitely see this being very useful to early stage companies!
I built my first native iOS app this weekend.
The client? My wife. The budget? $0 😅
She's a home pastry chef and needed a kitchen timer. Simple brief. Zero negotiation room.
Spent most of the weekend designing it by hand in Figma - Dieter Rams vibes, minimalist with a touch of skeuomorphic texture that just feels right on a physical device.
Then handed it off to Claude Code to implement in Xcode.
Accuracy? Kind of wild. 99% pixel-perfect from my Figma file. A lot of prompting, but it delivered.
App's live on TestFlight. Client tested it. Client approved it. Client is still not paying.
Next up: multi-step timers - which was actually the feature she asked for in the first place.
Great job! I'm sure she loves it .
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