Looking for a
Dialogflow Alternative?
Say Hello to Something Better

Agara is not just a better Dialogflow alternative. It is the solution to all the limitations of DIY Platforms such as Dialogflow

  • No hardware
  • No coding
  • Plug-n-play and get started in 4 weeks

Why is Agara the best Dialogflow alternative

Do you want to empower your business with an intelligent Virtual Voice Agent
that is easy to use, understand, and deliver seamless customer experience.

Here’s a comparison between two players, Agara and Dialogflow, to help you make better decisions.
Both Agara and Dialogflow are strong contenders as Conversational AI-powered voice agent,
but the differences are quite big. Pay close attention!

Agara vs Dialogflow

Purpose built for voice

Agara is focused entirely on solving for voice — delivering high-quality, natural autonomous conversations over voice.

Our speech recognition engine is a custom engine trained specifically on phone call data from customer support teams from around the world.

Our dialog builder has been built afresh for voice conversations which tend to be long and multi-directional. We have created special modules to correctly identify elements from the customer’s voice to eliminate errors.

Dialogflow belongs to “Chatbot Platforms & Tools” generic machine learning category that is used to build voice and text-based conversational apps.

The speech recognition is supposed to work across all audio inputs but is not optimized for phone audio (which is rather different).

The NLP is suited to short statements rather than long, multiple sentences (which is how we talk). The dialog manager puts all the onus on you instead of bringing the intelligence of actual conversations (which is necessary).

Agara typically has a 3-5% improvement over public ASR engines (Google)

Higher speech accuracy

Agara uses publicly available ASRs combined with its proprietary ASR technology and proprietary Spoken Language Understanding (SLU).

Agara’s custom trained ASR has been trained on several hundred hours of customer support phone call recordings for the most optimal, context-specific speech recognition. SLUs are custom machine learning models designed to operate directly on speech input to identify and extract specific entities. They perform robustly against accents, background noise, and different ambient setups.

Dialogflow uses Google ASR to transcribe generic speech and get the base transcript of the conversation.

While these provide reasonably accurate results and are an excellent way to get started in a project, they will not get the best accuracy than a solution that is optimized for a specific use-case. This is because the machine learning models used by the cloud providers have been trained on generic data rather than domain-specific language.

Agara’s SLUs drive a 20%-30% higher accuracy (relative to ASR) on specific entities

Conversational flexibility and intuitive drag-and-drop flow builder

Agara offers ease of creating complex workflows. The process of creating a workflow is simply a process of putting together Blocks – pre-built units of conversation that connect with each other seamlessly. Users can create and edit workflows within minutes, creating fully-featured, highly engaging conversation flows without any technical assistance.

Dialogflow offer limited flexibility when it comes to building conversation flows. To move and make changes to the flow you create is difficult in the future and forces developers to think well in advance about the hierarchical dialog flow of their conversation.

Agara identifies and handles smallest edge cases and all the different possibilities

Training and feedback

Agara’s ML models are trained on a regular basis looking at areas where improvements are needed. They are also additionally trained to manage the specific needs of clients.

Dialogflow makes it harder than it should be to automate processes and expand the conversational agent’s learning.

Agara has a continuous feedback mechanism to perfect the conversations

Scalable and enterprise-ready

Agara is an easily configurable virtual voice agent that can be deployed in less than 4 weeks’ time for different use cases in your business. It offers unlimited scalability that expands and contracts based on fluctuations in call volumes.

Dialogflow is not built for enterprises looking for scalable, flexible, and ready-to-implement solutions for their business needs. Dialogflow is for developers only.

Agara offers unlimited scalability and ready-to-implement solution

Buy or build?

With Agara, your spend is 60%-80% lower than current manual spends, highly predictable and in direct proportion to the volumes processed. There are no fixed annual charges, no hardware/software based escalations and no limit on number of workflows being used.

All upgrades to the system and increases in accuracy through machine learning investments come at the same predictable price too!

While initial costs can be low, high quality infrastructure and dedicated staff adds up in cost rapidly. These costs also tend to be fixed in nature irrespective of the output or result.

Any upgrades and even routine maintenance require constant investment in machine learning qualified staff, experimental IT infrastructure and long lead times.

Overall, the cost of a production-grade build over a 1+ year timeframe can cost 20%-50% more than buying from Agara.

Transform your customer experience with Agara

Agara helps businesses build truly intelligent and effective conversational AI-powered voice agent
that deliver strong ROI and great consumer experience.