Customer calls 2024-06-20
By unverified author. Claim this AI
Revolutionary AI for live, lengthy phone conversations.
Generated by ChatGPT

Elto is a sophisticated live conversation AI capable of making phone calls with authenticity and low latency. It's designed to automate communication in various sectors such as healthcare, construction, logistics, and travel.

The tool performs a range of routine call tasks, learning from a few dozen examples to adapt to new call workflows. Functionality extends to scheduling, navigating Interactive Voice Response (IVR) systems, retrieving knowledge, and executing follow-up tasks.

Elto's language models, trained on diverse phone conversation data, are designed to perform on par with human agents. It utilizes a custom end-to-end pipeline for transcription, reasoning, and speech production, aiming for humanlike conversations with quick response time.

The AI tool integrates into product systems, automating downstream workflows and dispatching thousands of calls with minimal coding. Additional features include transferring calls requiring non-AI expertise to live agents, indexing on knowledge bases during calls, and fine-tuning capabilities using samples.

Post-call, Elto can extract conversation outcomes and trigger subsequent workflows. It also includes a No-Code dashboard for managing operations. Furthermore, the tool offers the functionality of auto-navigating IVRs and the delivery of hundreds of realistic, low-latency voices, with ongoing additions.

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Elto was manually vetted by our editorial team and was first featured on July 9th 2023.
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Pros and Cons

Pros

Parallel dialing feature
Intelligent call routing
Voicemail and pickup detection
Integration with CRM and SEP
Prioritizes engaged prospects
Faster pickup detection
Different plans for different needs
Optimized for multiple industries
Automates routine call tasks
Custom language models
Integration into product systems
Indexing on knowledge bases
Post-call outcome extraction
Auto-navigating IVRs
Variety of realistic voices
Low latency in conversations
End-to-end pipeline for transcription
Realistic, humanlike conversations
Fine-tuning capabilities
Automating downstream workflows
Developer-friendly with minimal coding
REST and GraphQL APIs
Fully managed infrastructure
No-Code dashboard
Ability to handle edge-cases
Adapts to new call workflows
DSL function calls mid-conversation
Hundreds of different task-types training
Capable of lengthy phone conversations
Automates follow-up tasks
Custom voices addition
Human agent-like performance
Dispatches thousands of calls
Conversation outcome extraction
Human intervention option
Flexibility in training
Trained on phone conversation data

Cons

Highly dependent on CRM systems
Complexity of plan options
Potential for dialing lag
Less effective without clear examples
No standalone offline capability
Requires consistent data updates
Lack of voice variety
Qualitative analysis may be subjective
May require technical ability for integration

Q&A

How does Elto optimize cold calling processes?
What is Elto's parallel dialing feature?
How does Elto detect voicemails and pickups?
How does Elto integrate with CRM systems and SEPs?
What are the different pricing plans that Elto offers?
How does Elto assess and hang up on numbers that are not engaged?
What makes Elto's routing speed faster than competing solutions?
How can users prioritize calling and selling without disruption using Elto?
What sectors can Elto be used in for automating communication?
How does Elto adapt to new call workflows?
How does Elto perform in comparison to human agents in phone conversations?
What downstream workflows can Elto automate?
What is the capability of Elto's No-Code dashboard for managing operations?
How does Elto auto-navigate IVRs?
How does Elto deliver realistic, low-latency voices?
Can Elto handle calls requiring non-AI expertise?
How does Elto index on knowledge bases during calls?
How does Elto fine-tune capabilities using samples?
How does Elto extract conversation outcomes post-call?
What special tasks can Elto's language model adapt to?
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