What services does Dizinee offer?

Dizinee offers a complete suite of digital services including custom web development (Laravel, Next.js, React), mobile app development (iOS, Android, React Native), UI/UX design, search engine optimization (SEO), graphics design & branding, content writing, copywriting, SaaS platform development, and e-commerce solutions.

Where is Dizinee located?

Dizinee is headquartered at 28/A, Kakrail, V.I.P Road, Dhaka 1000, Bangladesh. We serve clients globally across the USA, UK, UAE, Canada, and Australia.

How much does Dizinee charge for web development?

Dizinee offers tiered pricing: Growth plans starting from affordable rates for small businesses, Scale plans for growing companies, and custom Enterprise plans. Contact us for a free consultation and tailored quote at https://dizinee.com/free-consultation.

Does Dizinee work with international clients?

Yes, Dizinee works with clients worldwide including the USA, UK, UAE, Canada, Australia, and Bangladesh. We communicate in English and Bengali, and accept international payments via PayPal, Wise, Stripe, and bank transfer.

How can I get a free consultation from Dizinee?

You can book a free strategy session with Dizinee's technical directors at https://dizinee.com/free-consultation. You can also reach us via WhatsApp at +880-1601-722755 or email at hello@dizinee.com.

What technologies does Dizinee specialize in?

Dizinee specializes in Laravel, Next.js, React.js, Node.js, PHP, MySQL, PostgreSQL, Redis, Docker, AWS, React Native, Flutter, and Figma for design. Our full-stack expertise enables us to build everything from simple landing pages to complex multi-tenant SaaS platforms.

How long does it take Dizinee to build a website?

Project timelines vary by scope. A standard business website takes 2-4 weeks, a custom web application takes 6-12 weeks, and a full SaaS platform typically takes 3-6 months. We provide detailed timelines during the free consultation phase.

Data Science

Inventory Forecasting System with Machine Learning

The retail chain with 100+ stores had $2M in dead stock annually and frequent stockouts of popular items....

Client: Retail ChainIndustry: Retail✦ 40% saving

Back to success stories

Inventory Forecasting System with Machine Learning

✦ 40% saving

4 months

Timeline

Retail

Industry

Retail Chain

Client

The Challenge

The retail chain with 100+ stores had $2M in dead stock annually and frequent stockouts of popular items.

Our Solution

Built a demand forecasting system using LSTM neural networks analyzing sales history, seasonality, weather, and local events to predict demand per store per SKU.

The Results

Overstock reduced by 40% saving $800K annually, stockouts decreased by 65%, inventory turnover ratio improved by 30%.