Bland AI vs Sesame

Comparing the features of Bland AI to Sesame

Feature
Bland AI
Sesame

Capability Features

API Access
Concurrent Calls Limit
1000000
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Pathways
Conversational Speech Generation
Custom Conversational Guardrails
Custom Deployment Engineers
Custom Model Training
Data Encryption
Dataset Size
1 million hours
Dedicated Customer Data
Dedicated Infrastructure
Emotional Intelligence
Enterprise Integrations
CRMERP
Evaluation Suite
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multi-Regional Data Support
Multilingual Support
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Omni-Channel Communication
CallsSMSChat
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sentiment Analysis
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Supports Any Industry
Text and Audio Input
TextAudio
Text to Speech
Training Epochs
5
Use Case Flexibility
Voice Selection

Integration Features

GitHub Release
HubSpot Integration
LLama Architecture Backbone
Memory Integration
Mimi Split-RVQ Tokenizer
Slack Integration

Limitation Features

Cannot Model Conversation Structure
English Language Dominance
Memory Bottleneck in Training
No Free Trial
No OpenAI Integration
No Pre-trained Language Model Use
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly

Pricing Features

Free Preview
Free Tier
Open Source
Apache 2.0