How Yojji Built an AI Solution That Cuts Feature Delivery Time by 96%

Speed is a costly resource in the tech market. Companies race to launch new features, but even small updates often rely on busy developers. Every minor (or not) change becomes another task in the backlog. It slows down product growth, right?

Our Yojji team once asked: What if we could build production-ready features in just a few minutes?

Sounds impossible? No! We tried and developed a decision → an AI-assisted web-coding solution. Now, we want to share it with you.

TL;DR: Key info

Yojji built an AI-assisted web-coding solution that lets teams create and deploy production-ready features in just 10–15 minutes. It cuts delivery time by up to 96%. Initially developed for a client’s QR code automation, it became a universal AI tool adaptable to any tech product or industry. The system allows teams to prototype, test, and launch faster without overloading developers or compromising quality.

A Client Request or How It All Began

It all started with a practical challenge from one of our clients. Their operations team needed a simple way to generate QR codes for industrial equipment and connect those codes to specific data stored in their backend system. By scanning a QR code, staff should instantly see the equipment ID, service history, and related technical details in real time. On paper, it sounded easy. In reality, it was a process tangled with inefficiencies. Each new feature request required developer involvement, manual coding, and deployment cycles that took days or even weeks. The client’s non-technical staff couldn’t make even minor changes without waiting for engineering support. They needed to create these small, data-connected tools independently, without interrupting the main product roadmap or overloading the dev team. Then, our Yojji co-founder, Timofey Lebedev, saw a bigger opportunity:

What if we could build an AI-assisted web-coding solution? A system where users describe what they need in plain language, and AI automatically generates a functional, production-ready interface connected to real backend data?

Great idea! But ↓

Challenges We Encountered

When we started developing this solution, we discovered that existing AI web environments were not built for production-grade use. No flexibility, structure, or automation.

Limited AI Studio capabilities

The browser-based tool allowed only one-way GitHub commits and no folder hierarchy. Our developers had to upload or paste code line by line manually.

Performance issues

Large backend models caused heavy lags and sometimes freezing for several minutes.

Deployment automation

Since the AI studio had no CI/CD support, we built a custom deployment pipeline that automatically pushed updates to GitHub and published them as isolated production-ready micro-apps.

By the way, if you face tech issues with your product and need expert tips, our Yojji team welcomes you to an IT consultation. We’re ready to make your problem not a problem at all!

So, how did these challenges open our new door?

Our AI Solution

To solve our client’s challenge, our dev created an AI-assisted web-coding system that connects directly to a company’s backend. It allows users to describe what they need in a few words. For example, “generate QR codes for all machines in the database”, and instantly receive a functional feature.

Learn more about this AI web-coding solution in our case study. And then come back to see the step-by-step route of the process ↓

How This Solution Works (Step-by-Step)

1. Start in the AI web-coding studio.

A user (PM/QA/ops/dev) opens the browser-based studio that runs a lightweight code runner and sandbox. The project is initialized with our base template. It means you open a workspace that already knows how to communicate with your product’s backend.

2. Authenticate against your backend.

You sign in like a regular user, but only to test data, so it’s safe.

3. Describe the feature with a prompt.

The user types a natural-language instruction. For example, “Create a page that lists equipment with last service date and generate QR codes for each item.” The AI parses intent, maps entities to known endpoints (via our backend interface spec), and drafts UI + logic. In plain terms, you tell the system what you need, and it figures out which APIs to call and builds the page.

4. Bind to data via a backend interface spec.

We maintain a lightweight contract, and the AI uses this spec to generate fetchers, pagination, and basic error handling. The AI got a map of your APIs, so it calls them correctly without bulky libraries.

5. Generate the UI and logic.

The AI produces a minimal HTML page (or small helper modules) with tables, filters, a QR generator, and action buttons. It auto-wires state, render cycles, and formatting utilities. We explicitly avoid heavy frameworks to keep the studio responsive. In plain terms, it builds a clean page that loads fast and does exactly what you asked.

6. Optimize for performance.

If the draft tries to import large libraries or 50+ models, guards trigger. Our dev replaced them with lightweight HTML/JS snippets, lazy-loaded optional pieces, and capped payload sizes. This prevents the editor from freezing. So, we keep the code small so the tool stays snappy.

7. Save artifacts to GitHub (one-way commit).

Due to studio limits, we commit forward-only to a dedicated GitHub repo/branch. The commit contains the generated page, assets, and a small manifest. It means that your new mini-feature is saved to version control like any other code change.

8. One-click deploy via CI/CD

A GitHub Action (or similar) detects the commit, builds static assets, and deploys to an isolated sub-application. We don’t touch the core monolith repo. In plain terms, when you press deploy, it goes live under your product, separate from the main app.

9. Wire entry points from the main app

A button in your product opens the new page already filtered to the right data.

10. Reuse with templates

We store prompt + code templates (QR lists, analytics tables, reports). Cloning a template inserts the right fetchers and UI blocks. Only endpoint names/columns change.

So, when you need a similar page, just duplicate, tweak a prompt, and you’re done.

This approach reduced feature delivery time from 40 hours to just 10–15 minutes. It frees devs from repetitive work and allows business teams to move faster. That’s the result our dedicated developers can also help you achieve.

Now, let’s take a look at how it works from the user side ↓

P.S. It’s so simple.

How Yojji’s AI Solution Adapts to Any Business

Any company that works with backend data (no matter if it’s healthcare, education, fashion, or finance) can benefit from this approach. You can prepare simple text prompts and get fully functional web tools. Our system allows non-technical teams to build dashboards, automate tasks, and visualize data in minutes instead of weeks. Let’s discover some examples.

Healthcare

In hospitals and clinics, maintenance teams can track the condition and service history of medical devices. With our AI solution, they can instantly generate a micro-app with QR codes for each piece of equipment. When staff scan a code, they see the device’s ID, last maintenance date, and upcoming service schedule.

How else you can use it in the medical and healthcare space:

• Compliance reporting. Create exportable reports for equipment maintenance or patient safety audits on demand.
• Medical inventory tracker. Generate a live dashboard showing available medicine, supply levels, and expiration dates.
• Patient intake dashboard. With a single prompt like “create a form for new patient registration connected to our EMR API,” the system can build a secure intake interface in minutes.
• Shift management portal. Allow nurses or technicians to view and swap shifts automatically based on current schedules stored in the HR database.
• Lab result viewer. Quickly generate pages that visualize lab data from diagnostic systems for staff and patients.

The results you can expect:

• 70–90% faster reporting and task automation cycles.
• Reduced downtime of critical equipment through real-time monitoring.
• Zero developer dependency for simple dashboards and reports.
• Full compliance with healthcare data standards by operating on test and authorized production data only.

Our team helps healthcare organizations improve patient care and compliance in one step with our development services. Discover how we build healthcare innovation.

EdTech

Modern education platforms produce vast amounts of student data. But turning it into actionable insights often requires custom reports and developer time. Our AI-driven approach helps methodologists or academic coordinators simply prompt a request like, “show students with activity below 60%,” and receive a color-coded analytics dashboard showing attendance, engagement, and performance in seconds.

Other ways to use it in EdTech:

• Teacher performance metrics. Instantly visualize class attendance, engagement, and feedback ratings.
• Course progress dashboard. Generate detailed reports on completion rates and success metrics per course.
• Parent communication portal. Build pages showing real-time student updates and grades for guardians.
• Dynamic quiz generator. Create personalized quizzes or exercises directly from existing course materials.
• Certification tracker. Produce exportable reports showing completed certifications and upcoming deadlines.

The results you can expect:

• Instant access to insights that previously took days to collect.
• 80% fewer developer requests for analytics or reports.
• Faster interventions for underperforming students.
• Improved decision-making with real-time engagement data.

Explore how we build EdTech solutions and help educational teams make data accessible, visual, and actionable.

FashionTech

In fashion and retail, speed defines success because brands must react quickly to changing trends. Our AI solution allows marketing teams to generate a ready-to-publish dashboard that displays trending colors, fabrics, and product categories in several minutes. Automatically process the data from CRM sales.

More ways to use it in fashion and retail:

• Product launch tracker. Visualize campaign performance, SKUs in stock, and conversion rates.
• Customer behavior insights. Identify top-selling items and seasonal buying patterns.
• Supplier coordination panel. Create a micro-app where vendors can update delivery or quality statuses.
• Return analytics. Monitor return rates by product category and reason.
• Store performance map. View real-time sales data across different locations on an interactive map.

The results you can expect:

• 50% faster trend updates and marketing decisions.
• Increased agility in campaign management and product launches.
• Real-time visibility into sales and customer behavior.
• Reduced dependency on BI teams and data analysts.

Why Our AI Solution Works for Any Industry

Our AI-assisted web-coding solution is adaptable and isn’t limited to one tech stack, product type, or business model. It works anywhere teams rely on backend data, APIs, and repeatable workflows.

Unlike traditional tools that require developer input at every step, our approach bridges the gap between engineering and operations. It lets product managers, QAs, and even marketers create production-grade tools without disrupting existing architecture or security protocols.

Why it scales seamlessly across industries:

• Backend-agnostic architecture that works with any API.
• Security-first setup because it uses authorized test or production data without storing user credentials.
• Flexible deployment as it supports CI/CD, Git-based version control, and easy rollback.
• Human-AI collaboration.

Also, check our cases to see how we implement other modern approaches in various industries to support clients’ business goals.

Results: 96% Faster Delivery, Lower Costs, and Greater Flexibility

What began as a small automation task now enables teams to deploy production-ready features faster (it reduces delivery cycles from weeks to minutes).

Our solution removes the dependency on core developers for micro-features, so companies free up engineering capacity for strategic work. And this allows non-technical specialists to create, test, and publish their own tools safely.

Key results:

• 96% faster feature delivery compared to traditional development cycles.
• 40–60% reduction in engineering costs through automated feature generation and deployment.
• Higher flexibility because teams can experiment, iterate, and deploy updates instantly.
• Better collaboration because business and tech teams co-create tools using one shared workflow.
• Security maintained because all features integrate with existing backend systems and production-grade authentication.

This AI-driven workflow proves that automation can speed up software delivery without sacrificing quality, stability, or control. It’s a smarter way to scale where every team member can contribute to innovation.

Want to achieve the same results for your product with this or other solutions? Our software development services are exactly what you need to help your product get there.

Create Your Business Value

We believe the future of software belongs to teams that build and think boldly, and use AI intelligently. This project proved that with the right approach, companies can turn complex development cycles into agile, scalable workflows that drive business growth.

If you’re ready to accelerate delivery, cut costs, and bring AI-driven efficiency to your product → contact us, and let’s build your breakthrough.