Share Your Requirements
Mark Garcia: Traki
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 global customer support firm specializing in AI-powered automation sought a unified chatbot solution to streamline conversations across platforms. Facing inefficiencies in managing high-volume queries, the client needed an intuitive, multilingual system. Oodles delivered a scalable, voice-enabled chatbot that accelerated response times and simplified user engagement across channels.
Scope Of Work
The client sought Oodles to centralize support interactions while reducing dependency on manual assistance. They required a conversational interface that could operate seamlessly across web and mobile platforms. The project involved areas such as chatbot development, NLP integration, voice recognition, and third-party messaging app connectivity to automate and enrich user interactions.
Our Solution
To address the client’s complex support needs, a dynamic, AI-powered chatbot was developed using a hybrid of Dialogflow and AWS Lex for maximum flexibility and multilingual capability. The system was built to handle text and voice inputs, providing contextual responses in real time.
Key Features Delivered:
- Multi-platform Integration: Enabled connectivity across WhatsApp, Telegram, Facebook Messenger, and web portals.
- Voice Recognition: Leveraged Amazon Lex and Google Dialogflow to support speech-based queries for accessibility and ease.
- Intent-Based Routing: Trained using BERT and custom NLP models to classify and direct queries with high accuracy.
- Dynamic Content Flow: Created flowcharts and rules-based logic for guided conversations, covering over 100+ intents.
- Sentiment Analysis: Integrated third-party APIs to evaluate user sentiment and adapt bot behavior accordingly.
