RAG Bot POC
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)
Project Description
A knowledge-centric enterprise named Stratus Edge working in the Oracle ecosystem approached Oodles Platform to streamline access to critical product information. They aimed to improve how teams interact with vast Oracle data. The client sought a responsive chatbot solution named RAG Bot that could answer queries intelligently. A customized AI-powered tool was implemented to meet this exact need.
Scope Of Work
The client aimed to simplify Oracle knowledge retrieval while maintaining conversational context and precision. The client needed a chatbot capable of understanding sequential queries and displaying refined results. Key areas of work included chatbot development, API integration, conversational UI, and knowledge base structuring.
Our Solution
To fulfill the client's need for a smarter way to interact with Oracle data, a bespoke AI chatbot platform named RAG Bot was developed. It was designed to respond to both isolated and follow-up questions using the OpenAI API, ensuring continuity and relevance in conversations.
Key features implemented:
- Conversational Intelligence: Integrated OpenAI’s API to provide context-aware responses.
- Filtered Query Results: Enabled streamlined access to filtered answers from the Oracle knowledge base.
- React.js Interface: Built a responsive and intuitive frontend using React.js and Bootstrap.
- ChromaDB Integration: Ensured efficient and scalable database handling.
- Django Backend: Provided seamless API handling and backend operations.
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