Share Your Requirements
AI.io Incorporated
LANCER
Lancer :
Ideal for quick, focused engagements
Team: ≤ 2 resources
Duration: ≤ 3 weeks
Indicative Budget: ≤ $3,000 USD*
Use Cases: MVPs, prototypes, simple websites, bug-fix sprints
Indicative Pricing: ~$15–$25/hr per resource*
Growth :
Best suited for growing products or structured builds
Team: 2–5 resources
Duration: Up to 4 months
Indicative Budget: Up to $30,000 USD*
Use Cases: Feature-rich web apps, integrations, custom dashboards
Indicative Pricing: ~$15–$35/hr per resource*
Enterprise :
Tailored for high-scale, complex or long-term initiatives
Team: 5+ resources
Duration: More than 4 months
Indicative Budget: Starts from $30,000+ USD*
Use Cases: End-to-end platforms, SaaS products, compliance-heavy systems
Indicative Pricing: ~$25–$50/hr depending on roles*
(Development)
Lancer :
Ideal for quick, focused engagements
Team: ≤ 2 resources
Duration: ≤ 3 weeks
Indicative Budget: ≤ $3,000 USD*
Use Cases: MVPs, prototypes, simple websites, bug-fix sprints
Indicative Pricing: ~$15–$25/hr per resource*
Growth :
Best suited for growing products or structured builds
Team: 2–5 resources
Duration: Up to 4 months
Indicative Budget: Up to $30,000 USD*
Use Cases: Feature-rich web apps, integrations, custom dashboards
Indicative Pricing: ~$15–$35/hr per resource*
Enterprise :
Tailored for high-scale, complex or long-term initiatives
Team: 5+ resources
Duration: More than 4 months
Indicative Budget: Starts from $30,000+ USD*
Use Cases: End-to-end platforms, SaaS products, compliance-heavy systems
Indicative Pricing: ~$25–$50/hr depending on roles*
Technologies Involved:
CLOUD COMPUTING
Area Of Work:
Amazon Cloud
Project Description
AI.io Incorporated approached us to build a cloud-based AI platform that enables businesses to harness machine learning for operational insights and automation. The system needed to support custom model training, seamless integration with enterprise tools, and a user-friendly dashboard for non-technical users. The solution was intended to empower decision-makers with actionable insights via a SaaS-based delivery model.
Scope Of Work
The client needed end-to-end development of a scalable AI SaaS platform that included backend architecture, machine learning pipeline integration, frontend dashboard, user authentication, and cloud deployment. The solution also required robust data ingestion, API-based data access, and multi-tenant support.
Our Solution
Oodles' solutions:
- Built a multi-tenant SaaS platform with AI-driven modules
- Integrated machine learning models for predictive analytics
- Enabled real-time data processing pipelines using Python and Node.js
- Developed intuitive frontend dashboards using React.js
- Secured API access with token-based authentication
- Deployed the solution on AWS with CI/CD pipelines
- Enabled third-party integration via REST APIs and webhooks
- Delivered documentation and training for future enhancements
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