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We just delivered this AI-powered finance app with a clean, data-first UI and smooth user experience.
What we built:
Real-time balance tracking with interactive charts
AI-based financial forecasting and goal planning
Clean dashboard for cash, investments, and insights
Goal-based planning flows like house, education, retirement
Secure, scalable backend with fast performance
Pixel-perfect mobile UI with dark mode optimization
Focus was simple:
Make complex financial data easy to understand
Keep UI minimal but powerful
Ensure fast, lag-free interactions
If you’re building a fintech or AI-driven product, we can take it from idea to production with the same level of polish and speed.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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I've built a new mobile AI assistant that brings chat, text and image generation, voice input and document analysis into one app.
It have Smart Chat, Text Creator, Image Create, Voice Input, plus PDF Scanner, Photo Analyze, Social Content and Prompt Ideas, filtered by category.
Almost everything AI can do, just in one place.
Such an amazing tool! Keep going!
A great app should not just function, It should feel visually distinct
When the market is full of similar-looking products, design becomes part of the product’s well identity
For this finance project, we focused on a sleek UI, intuitive UX, and a visual language that doesn’t feel generic
Both dark and light modes were designed to feel equally intentional.
Which one do you prefer?
10 voted
56%
8 voted
44%
18 votes
Closed
I’d go with Light Mode. 👌 It feels fresh, clean, and the UI elements stand out beautifully against the background. Both are strong, though! 🔥
What if anyone on your team could ask your data a question and get a live dashboard back in under a minute?
That was the brief. Business users were locked out of their own data. Every question waited on someone who could write SQL, data sat across disconnected systems, and security teams refused to send sensitive records to third-party AI tools.
So we flipped the model. Instead of moving enterprise data to an AI product, we moved the AI analytics product into the customer's AWS account.
What we built:
• Natural-language querying that turns plain-English questions into governed dashboards in under 60 seconds
• Federated queries across SQL and NoSQL sources through Trino
• AI query generation on AWS Bedrock Agents, with Bedrock Guardrails keeping model output in bounds
• Dashboards generated with Apache Superset, plus proactive anomaly and trend alerts
• A white-label React widget that embeds in any product
• Role-based access, row-level security and enterprise SSO enforced at every layer
The result:
Zero data egress. The whole platform deploys inside the customer's VPC and is live on AWS Marketplace.
Building AI features for a data-heavy or regulated product? Let's talk about doing it without your data leaving your cloud.
