GoBright
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 Netherlands-based AI solutions provider specializing in market research sought to modernize qualitative interviews using chatbot automation and data analytics. The client needed a mobile-first platform to conduct open-text interviews, sync data in real time, and analyze participant responses at scale. Oodles delivered a smart, cloud-integrated solution tailored for cross-platform accessibility and advanced NLP-driven insights.
Scope Of Work
The client sought Oodles to simplify open-ended user interviews through an AI-powered chatbot that captures qualitative data and syncs it to Google BigQuery. The engagement focused on building a mobile application, integrating chatbot flows, automating backend sync, and visualizing data in Google Data Studio for sentiment and response analysis.
Our Solution
To support large-scale qualitative research through AI, Oodles built a cross-platform application integrated with cloud services and conversational AI.
Key features include:
- NLP-Powered Chatbot Integration: Used Engati to conduct guided, open-ended interviews with participants through an interactive chat interface.
- Real-time Data Capture: Captured structured responses (e.g., age, interests, feedback) during live interactions and synced them to Firebase Firestore.
- Automated Data Sync to BigQuery: Deployed a Python-based Google Cloud Function (sync_chat_bigquery.
- Cross-Platform Mobile Setup: Developed iOS and Android apps with environment-specific Git branches.
- Analytics Dashboard in Google Data Studio
- Secure and Scalable Infrastructure
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