What is ProtoCall AI – Data?
The quality of your AI solution relies heavily on the quality of the data used to train it. Our team harnesses intelligence, skills, technology, and cultural knowledge to create custom rich datasets and labeled training data for your machine-learning applications, Conversational AI, AI Bots, and Intelligent Platforms.
KomBea has designed and improved organization’s customer phone interactions for more than 20 years. Our technology and expertise are used on millions of phone interactions each year. We provide organizations with rich, labeled training data for their Conversational AI initiatives using their own customer phone interactions. Our high-volume, high-accuracy datasets include Intents, Entities, Utterances and Context. We provide you with:
Full audio with text transcription
Call context and outcome
Utterances with intent tags and slot filling
Metadata tags such as:
Demographics (age, gender, accents)
Sentiment (sarcasm, anger, frustration)
Environment (background noise, latency, volume)
Why Use ProtoCall AI?
Our technology and methodology allow us to deliver organization-specific language models, enabling organizations to effectively train AI models and perform analytics that achieve optimal data-driven autcomes of:
Intent determination and content determination
Voice, scripting, intonation, and cadence for AI Bot utterances
How We Create Tailored Training Data
Our proprietary platform allows us to create high-quality, tailored training data to meet industry needs at scale.
Call Engineering: Using ProtoCall Builder, we custom design each phone conversation (flow, scripting, CRM integration, etc.) and create the user interface that our live AI Operators use for Data Creation. This application also enables continuous A/B testing and experimentation to identify the optimal conversation flow, intent determination, and key message characteristics such as voice, scripting, intonation, and cadence for the Conversational AI Bot.
Data Creation: Our live AI Operators use ProtoCall to handle customer conversations, enabling them to follow the prescribed conversation flow and “speak” using pre-recorded audio. They concurrently create metadata such as demographics, sentiment, call outcome, and much more. When using pre-recorded audio, customer conversations have minimal agent variability, thereby greatly improving data quality.
Data Auditing: Using ProtoCall QA, we audit the data created during these customer conversations. This application allows us to quickly accept, reject, alter, annotate, and append data to each customer utterance at each node of the conversation. This audit process is highly efficient, allowing us to create high-volume, high-accuracy datasets while also providing a feedback loop to live AI Operators and conversation-flow designers.
Data Delivery: Using ProtoCall Data Aggregator, our AI and Analytics specialists format and deliver the data specific to the organization’s requirements in many consumable formats such as CSV files, database records, and annotated audio recordings.
Conversational AI Engine: Data is used to train Conversational AI Bots, Textual AI Bots, Real-Time Agent Prompts, SEO engines, etc.
Data Analytics: We recommend and carry out continuous A/B tests and experiments designed to measure and drive optimal outcomes.