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Pricing Plans
Cost of Software Development
The price for developing a piece of software is determined by a variety of things. Before producing an estimate of costs, a development agency would need to go over the project requirements with the clients.
If you’re constructing a basic app with dozens of different screens, the cost may be comparable to those of more intricate apps. Software development costs are not solely dependent on the size and complexity of the app.
Software Cost Factors
App Type and Complexity
Platforms
Complexity of UX/UI Designs
Back-End infrastructure and Connected APIs
Hiring Model
Starting Price
The determining factors for software development costs encompass the amount of human resources dedicated to the project and the technological framework employed. Drawing from our extensive expertise, we have observed that the estimated cost range for software development typically falls within the range of $50,000 to $200,000.
Startup Business
Package
5 Logo Concepts
10 Banner Designs
Hybrid Mobile App (Swift / Flutter)
Website
Admin Panel Web Application
6 Months Free Updates and Maintenance
Multi-Vendor
Package
5 Logo Concepts
10 Banner Designs
Hybrid Mobile App (Swift / Flutter) OR Native
Dynamic Website
Admin Panel Web Application
6 Months Free Updates and Maintenance
Enterprice
Package
5 Logo Concepts
10 Banner Designs
Hybrid Mobile App (Swift / Flutter) OR Native Apps + Many Roles
Website
Database Management
Admin Panel Web Applications
6 Months Free Updates and Maintenance
Custom Software
Development
Enterprise Applications
Development
Machine Learning
Development
Chatbots
Development
Generative AI
Development
MVP Development Plan and Road Map
A service for designing an MVP software development strategy tailor-made for minimum viable products. This plan assists organizations in analyzing and prioritizing their requirements effectively
Tools
JIRA
ASANA
TRELLO
Machine Learning
Project that includes an end-to-end Machine Learning model capable of predicting your target variable. utilization of over 50 different ML algorithms, deployment of the model in webapp/APIs, data preprocessing and cleaning, model fitting and selection, hyperparameter optimization, ensemble modeling, forecasting of desired KPIs, performance measurement, and the ability to save/load the model for future data application.
Deliverables
- End-to-end Machine Learning Model
- Google Colab Notebook with Interactive Pipeline
- Documentation of Theory and Graphs
- Replicability and Scalability
- Utilization of 50+ ML Algorithms
- Deployment in Webapp/APIs
- Data Preprocessing and Cleaning
- Model Fitting and Selection
- Hyperparameter Optimization
- Ensemble Modeling
- Forecasting of KPIs
- Performance Measurement
- Save/Load Model for Future Data Applicatio