Implemented a conversational AI system:
- Utilized advanced voice recognition and text-to-speech synthesis.
- Enabled bots to understand and respond naturally to customer queries.
- Integrated neural call models for improved conversational accuracy and customer engagement.

Intelligent Call Bots with Advanced NLP

Established a central hub for managing interactions:
- Coordinated multiple call bot instances for simultaneous customer interactions.
- Facilitated seamless integration between backend services, voice recognition, and synthesis modules.
- Enabled dynamic allocation and monitoring of call bot performance.

Centralized Call Bot Hub

Developed a scalable backend infrastructure:
- Managed comprehensive business logic, data validation, and secure API communications.
- Implemented a high-performance database capable of storing millions of call records with optimized data retrieval.
- Ensured data security with encryption and regulatory compliance (GDPR).


Robust Backend and Database Management

Delivered an intuitive and responsive user interface:
- Provided comprehensive user management capabilities.
- Included detailed statistics, real-time graphs, and customizable reports.
- Offered monitoring tools for call bot activities, dialogue scripting, and performance metrics.

Advanced Frontend Dashboard

Enhanced conversational accuracy through AI:
- Analyzed speech patterns and contexts using advanced NLP techniques.
- Generated highly relevant, personalized responses in real-time.
- Continuously optimized models through machine learning and iterative improvements.

Neural Call Model Service

This type of research-based project needs a longer time for full calibration, but even the current results show high accuracy in voice recognition and conversational responses.

High accuracy in voice recognition

Early analytics indicate significant improvement in customer engagement and streamlined communications.

Improved customer engagement 

Call centers are heavily based on human work. A properly trained bot can maintain a consistently high standard of its output compared to humans. This project completely changed the job humans are doing - they analyze the conversations and fine-tune the responses of bots.

Cost savings

One of the crucial aspects of preprocessing was the ability to distinguish signal from background noise.

Maintaining high accuracy of speech-to-text conversion

For real-time communication, low latency is an absolute must. But the speed had to be achieved with limited hw resources as costs for on-the-fly computing can go skyrocket.

Ensuring low latency

AI-Powered Call Bot Solution

GrownApps

This project was tough in terms of requiring a lot of deep research and trial-and-error work that had to be delivered under a reasonable budget.

Team Lead/Tech Lead @ GrownApps

GrownApps is a close-knit team. We've home-grown most of our team members from junior positions, as educating is in our DNA since the beginning. We love to see young talent growing and flourishing. Although we're remote-first, our devs, designers, and sales enjoy our office days, internal tech talks, and beer talks. All of us are humans in the first place, and we approach our clients the same way. 

GrownApps

About

Challenge, approach, and impact

Maintaining high accuracy of speech-to-text conversion

Ensuring low latency

How we built

Testimonials

Team structure

Client team

Peter

Agency team

2 x AI/ML engineer

1 x Backend dev

1 x Fullstack developer

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