Sesame vs PreCallAI

Comparing the features of Sesame to PreCallAI

Feature
Sesame
PreCallAI

Capability Features

AI Voice Sales Automation
Appointment Scheduling
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Customer Support Automation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Generative AI Technology
Lead Qualification
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Payment Collection
Pronunciation Correction
Sales Follow-Up Automation
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Training Epochs
5

Integration Features

GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer

Limitation Features

Cannot Model Conversation Structure
English Language Dominance
Memory Bottleneck in Training
No Credit Card Required
No Pre-trained Language Model Use
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly

Other Features

Designed for Startups and Enterprises
StartupsEnterprises
Trusted by 10,000+ Businesses
10000

Pricing Features

Free Preview
Free Test Drive
Open Source
Apache 2.0