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Transformar dados em decisões estratégicas não é mais diferencial, é necessidade e quando a análise comercial se une à automação inteligente, o resultado é uma operação mais ágil, previsível e orientada por performance real.
No projeto apresentado, desenvolvi uma solução completa de Análise de Performance Comercial com Automação de Relatórios, capaz de elevar a maturidade analítica e acelerar a tomada de decisão em toda a operação.
Principais pilares do projeto:
Análise de Dados: insights acionáveis que impulsionam crescimento e aumentam previsibilidade comercial.
Automação de Relatórios: eliminação de retrabalho e padronização total do fluxo de atualização.
Otimização de Processos: integração de rotinas, ganho de velocidade e consistência operacional.
Impacto gerado:
95% de redução no tempo de atualização (de horas para minutos)
8x mais agilidade na geração de relatórios
100% de padronização e rastreabilidade do fluxo
+30% de ganho estimado em produtividade analítica
Resultados comerciais analisados:
Faturamento: R$ 12,45M (+18,6%)
Meta atingida: 112,4%
Pedidos: 8.732 (+9,3%)
Ticket médio: R$ 1.427 (+7,8%)
Este projeto demonstra como a combinação de dados, automação e inteligência analítica transforma a operação comercial, reduzindo esforço manual, aumentando velocidade e elevando a qualidade das decisões estratégicas.
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Crypto Portfolio Dashboard
Blue means one thing here: the range you are looking at.
The value chart is a row of thin gray bars, and only the selected date range fills in blue. You read the period that matters and keep the months around it as context.
The phone carries the same chart above the holdings list. Each coin gets its own small bar chart between the name and the amount, so you can scan the whole portfolio for movement without opening a single coin.
Trading screens get busy fast. This one stays light and calm, so the numbers lead: total value, realized and unrealized P&L and open positions, all on one screen.
Designed by the Hue & Machine team.
#Crypto #Fintech #DashboardDesign #TradingPlatform #DataVisualization #UIDesign #ProductDesign #WebApp #MobileDesign #FigmaDesign
Nice Ui Dmytro
Clients often start with the same request: "Let's build an AI agent."
My counter-question is always: which manual process actually costs you time, errors, or money right now?
My selection rule: remove it first. If it can't be removed, simplify it. If it's still needed, automate it with a plain script. Only then add an integration or an agent. Often the best result is the process that no longer exists.
Safe automation means real scenarios, error handling, and alerts. Without alerts, a workflow can silently lose data for weeks. I always define what stays with a human and what goes to the system.
Question for you: which process would you automate first, and why is it still manual?
Service for audit and implementation: https://contra.com/s/BmWLbgFU-ai-automation-from-your-dream-to-working-implementation?r=auto_booster
Your Logistics Team Shouldn't Have to Chase Every Shipment Manually. 🚢
A shipment is delayed. Your customer wants an update. Your operations team is checking carrier portals, copying tracking numbers into spreadsheets, and sending the same status emails repeatedly.
By the time everyone has the right information, the next shipment needs attention.
The problem isn't a lack of effort. It's disconnected logistics operations.
Common challenges:
Shipment updates scattered across multiple carrier systems.
Delayed shipments discovered too late.
Manual customer status emails.
Tracking spreadsheets that quickly become outdated.
Repetitive follow-ups between operations and customer service.
Limited visibility into shipment exceptions.
The solution: An automated logistics operations workflow built with n8n.
I can design an automation that connects carrier tracking APIs, your shipment database, and customer communication channels.
Instead of manually checking every shipment, your team receives structured updates when something actually needs attention.
What the automation handles:
📦 Shipment Tracking — Retrieve updates from supported carrier APIs.
🚨 Exception Detection — Identify delays, customs holds, and missed milestones.
🤖 AI-Assisted Updates — Convert complex tracking events into clear, customer-friendly messages.
📧 Customer Notifications — Send relevant shipment updates automatically.
📊 Operations Visibility — Maintain synchronized shipment records and exception histories.
🔁 Escalation Management — Notify the responsible team when an exception requires action.
The goal: Less repetitive tracking work, faster exception awareness, and more consistent customer communication.
Two ways we can work together:
Option 1: Already have carrier APIs, a TMS, or a defined tracking workflow? Share your requirements, and I'll help design the integration.
Option 2: Not sure which logistics tasks should be automated? We can map your shipment lifecycle and identify the highest-value starting point.
Make your logistics operations easier to manage as shipment volume grows.
Workflow architecture
Scheduled Trigger → Carrier API Request → Normalize Tracking Events → Match Shipment Records → Detect Status Changes → Route Exceptions → AI Summary → Customer Email / Operations Alert → Database Update
Implementation: Authenticate carrier integrations, normalize differing event codes, compare timestamps and event IDs, prevent duplicate alerts, route exceptions by severity, and log delivery failures for retry.
Benefits: Reduced manual tracking, clearer exception ownership, more timely customer updates, and an auditable shipment history.
Result: A centralized shipment monitoring workflow that allows operations teams to focus on resolving exceptions instead of repeatedly checking tracking portals.
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The customs-hold exception is the one I'd find hardest to route, since it needs a different owner than a plain delay. Do you map each exception type to its own team in the escalation step, or is it one shared alert queue?