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Structured entity extraction and outcome classification on materials science experiment descriptions. Extracted fields include experiment ID, materials, quantities, equipment, process conditions, characterization methods, and outcomes, tagged directly on the source text. Overall experiment outcome (success/partial/failed) classified from the full passage context. This demonstrates our approach to domain specific text annotation where accurate labeling requires understanding technical terminology and process sequences. Every batch reviewed by our QA lead before delivery
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Most people set a budget once and forget it exists until it's too late.
This dashboard was designed to fix that. Weekly spending at $24,200, up 12.5% from last month. Monthly budget at $38,543 with 75% already allocated. Budget goals tracked by category salary, investments, freelance, and others each with a completion percentage and a dollar target that makes progress visible before the month ends.
The group contribution panel takes it further. Four members. One shared budget of $5,000. Taylor completed. Morgan at 70%. Quinn at 45%. Jamie cancelled. A collaborative finance tool that makes shared budgeting feel as clean as personal budgeting should.
Upcoming bills electricity, internet, grocery listed before they hit. A spending breakdown table that shows exactly what was budgeted, what was spent, and how much is left in every category.
This is what budget management looks like when the design treats users like they actually want to be in control of their money.
Does this feel like a dashboard that would change how a team manages their finances together? 👇
Designed by Orbix Studio
Tools: Figma
#DashboardDesign #FintechUI #BudgetApp #UIDesign #WebDesign #ContraFreelance #ProductDesign #SaaSUI
This caught my attention immediately. Great use of contrast and visual hierarchy.
"Businesses lose time and money to invoice errors that go unnoticed until it's too late. I built an automated pipeline that extracts invoice data, cross-checks it against vendor history, and flags anomalies with clear AI-generated reasoning — all visualized in a real-time dashboard. Stack: LangChain, Groq, n8n, FastAPI, Next.js."
AI-powered financial analytics platform built with FastAPI, Pandas, DuckDB, and Gemini API for data analysis, REST APIs, natural-language-to-SQL queries, and automated business insights.
