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Aveni
Learn how Deazy works with fintechs like Aveni to deliver AI advantage - with best practice engineering that rapidly innovates for growth
Productionising the POC: from low-code MVP to scalable product foundations
From proof of concept (POC) to production: learn how Deazy supports organisations to scale their AI POCs, moving from low-code constraints to market-ready code.
Agentic Marketing Automation
MVP to Production
React, Node.js, JavaScript, MongoDB / DynamoDB, MUI
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From the moment of funding, you’re on a ticking clock to launch your product and beat the runway. Deazy were instrumental in us doing that, providing the technical and AI know-how we needed to hit our deadlines and launch. In less than three months, they helped us move from a basic low-code MVP to a robust and production-ready platform, allowing us to scale rapidly to over 4,000 users (including the FT) and build a solid foundation for everything we want to do next with AI.
Dave Cannell
Cofounder & CEO at Sendr
Key Features
Pace & Capability
- Core product functionality replatformed beyond Bubble in under 3 months
- With no CTO, Deazy’s senior technical support covered a critical infrastructure and DevOps gap
- The robust solution supported both future scalability and deeper customisation
- The production-ready MVP was suitable for both investor conversations and growth, securing flagship client, the FT, immediately following delivery
Hybrid Replatforming Approach
- For flexibility, core product components including the existing Bubble sales table were rebuilt in React and Node.js
- For scalability, data was migrated from Bubble into MongoDB / DynamoDB
- UI components and extensibility were improved using MUI
- Collaboration throughout was product-led ensuring critical fundraising and growth plan milestones were met
AI-Ready Foundations
- The replatformed MVP needed to support planned AI features, not constrain them
- AI ambition was backed by pragmatic delivery with a design that supports future AI capability without the need for rework
- MVP features were enabled for AI-driven lead research, personalised media generation and automated insights and analytics
Quality & Delivery Confidence
- QA was embedded early to reduce regression risk as features expanded
- This enabled the team to move faster with more confidence during a high-pressure phase
- Learnings from the MVP directly shaped future product direction and informed longer-term architecture
Project Details
Project Summary
Problem Statement
Solution
Outcome
Team Structure
Our integrated approach brings together client stakeholders, our Deazy team, and vetted developer teams to deliver outstanding project outcomes.
Deazy On-shore Team
1x Account Manager
Delivery Oversight
Delivery Nearshore Partner Team
2x Full Stack
1x React Engineer
1x Part-Time QA
The Deazy Model Applied
Highlighting project milestones and teamwork, we showcase how the team collaborates effectively, overcoming challenges along the way in our project.
Finding the right talent
Vetting and Assessments
Systemised On-Point Delivery
A customised & flexible team
Ready to go faster?
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