Machine Learning
Identify repetitive tasks, define the exceptions, and keep people in control of consequential actions.
Big Data Development Services
Turn your raw data into valuable business insights with AI App Design Studio’s custom big data solutions, built to improve decision-making and efficiency.
Comprehensive big data Solutions
Big Data Consulting
Bring relevant information together so users can understand performance and act with confidence. Define the decisions first, then build the pipelines and reporting needed to support them.
Big Data Analytics
Identify source systems, owners, validation rules, and the quality issues that affect reporting.
Data Management
Choose measures tied to business decisions and show enough context to interpret changes.
Custom Data Applications
Set permissions, retention expectations, and an audit trail appropriate to the information involved.
Platform Integration
Monitor freshness, failures, and data drift, with named responsibilities for resolving issues.
Cloud Migration
Identify source systems, owners, validation rules, and the quality issues that affect reporting.
Maintenance and Support
Choose measures tied to business decisions and show enough context to interpret changes.
Powerful tools to get the most out of your data
Bring relevant information together so users can understand performance and act with confidence. Define the decisions first, then build the pipelines and reporting needed to support them.
Machine Learning
Identify repetitive tasks, define the exceptions, and keep people in control of consequential actions.
Artificial Intelligence
Connect approved information sources, manage access, and make answers traceable to the material used.
Data Science
Set permissions, retention expectations, and an audit trail appropriate to the information involved.
Business Intelligence
Use detailed analytics to create data-driven strategies.
Data Visualization
Monitor freshness, failures, and data drift, with named responsibilities for resolving issues.
How we Build your big data solution
Bring relevant information together so users can understand performance and act with confidence. Define the decisions first, then build the pipelines and reporting needed to support them.
01
Data Strategy
Identify source systems, owners, validation rules, and the quality issues that affect reporting.
02
Data Collection & Cleaning
Choose measures tied to business decisions and show enough context to interpret changes.
03
Data Analysis
Set permissions, retention expectations, and an audit trail appropriate to the information involved.
04
Solution Development
We design and implement a data solution tailored to your needs.
05
Testing & Deployment
Monitor freshness, failures, and data drift, with named responsibilities for resolving issues.
06
Ongoing Support
Identify source systems, owners, validation rules, and the quality issues that affect reporting.
Industries we serve
Automotive
B2B
Healthcare
Education
Ecommerce
Food
Manufacturing
Fashion
CRM
Logistics
Travel
Legal
Agriculture
Finance
Real Estate
Why AI App Design Studio for big data Development?
Put AI to work where it can reduce manual effort, improve access to information, or support better decisions. Start with a defined use case and measure the result against the current process.
Identify repetitive tasks, define the exceptions, and keep people in control of consequential actions.
Connect approved information sources, manage access, and make answers traceable to the material used.
Test accuracy, latency, operating cost, and failure cases with examples drawn from the intended workflow.
Fit the feature into existing systems with logging, feedback, and a clear route to human review.
Technologies we leverage for big data
Bring relevant information together so users can understand performance and act with confidence. Define the decisions first, then build the pipelines and reporting needed to support them.
iOS
SwiftSwift
UI KitUI Kit
RxSwiftRxSwift
CombineCombine
MVVMMVVM
AlomofireAlomofire
Core DataCore Data
Android
KotlinKotlin
MVVMMVVM
RxJavaRxJava
JavaJava
RetrofitRetrofit
JetpackJetpack
Common Questions about big data Development
Separate discovery, design, implementation, testing, and launch from ongoing hosting and support. List integrations, roles, platforms, and data migration needs. Compare estimates against the same assumptions and include room for uncertainty.
Break the release into reviewable milestones and identify external dependencies such as API access, content, approvals, and store review. Validate the riskiest assumption first, and adjust the plan when evidence changes.
Map data access and consequential actions, then specify authentication, authorization, logging, and retention. Test permission boundaries and recovery procedures. Confirm applicable requirements with the appropriate specialists.
Agree on metric definitions, source ownership, and refresh expectations. Validate completeness and accuracy before presenting trends, and give users enough context to understand uncertainty or missing data.