aitext.chat or Predibase? A Comprehensive Review

Import data from multiple formats

Supports website data crawling

Advanced analytics with chat logs

Supports chatbot and iframe embedding

Different pricing tiers options

Tool for information dissemination

Use of the latest GPT models

Data-focused training

User-centric security settings

Conversations history is available

Low-code platform

Fast ML model training

Efficient deployment

Minimal configuration code needed

Large language models support

Audio classification support

Bot detection capability

Fraud detection feature

Suitable for customer sentiment analysis

Topic classification functionality

Limited number of assistants

Inactivity leads to deletion

Data-training requires multiple formats

Limited credits on lower tiers

Clunky website crawling import

Preferences reset in inactivity

Cumbersome customization process

Limited advanced analytics

High initial learning curve

Complex configuration code required

Limited to certain ML models

Built on specific open-source technologies

Requires granular-level model adjustments

Private model hosting not default

Deployment requires specific infrastructure knowledge

Excessively developer-focused

less for non-tech

Requires historical data for use

Proven scalability not explicitly stated