This looks really interesting! Generating large amounts of plausible fake data by modeling the reality is still a big issue both for generating custom demos and for maximum load testing of streaming applications. Will definitely give ShadowTraffic a try.
Thanks! I had initially built ShadowTraffic to help with simple demos, but I'm realizing over time that to run a good load test, you need the same kind of statistically accurate data.
Yeah, maybe the word "free" in "Free Open Source
Conversational Infrastructure with Apache 2.0 license" isn't prominent enough. ;)
For Airy Enterprise and Managed Cloud, we usually like to listen to a potential customer's use case first and come up with a custom pricing that makes sense for both sides, usually containing fixed licensing options, volume-based components or even location-based pricing which can make a lot of sense for multi-location enterprises, but rarely works for e-commerce companies.
In general, Airy is mostly targeted at mid market companies and enterprises that deal with a lot of conversations, e.g. we helped a European retail company to launch conversational experiences on Google Search and Google Maps for their central customer support team and their 1,800 local stores (https://businessmessages.google/success-stories/tedi/).
Airy gives you an enterprise-grade communication infrastructure, running in a Kubernetes cluster, for example EKS with several virtual machines when you are running on AWS. Our recommended initial setup consists out of two c5.xlarge EC2 instances. This should be powerful enough to handle several conversational sources and a few hundred thousand conversations per month. We also have a few rather large SMBs among our customers, but the average SMB rarely gets to such amounts of conversational traffic yet.
Installing Airy is rather easy and can be done with our Airy CLI to set up a remote cloud instance from your local machine with a single command e.g. in AWS ("airy create --provider=aws").
According to my understanding, Jovo seems to be a rather light-weigh framework based on Javascript/Typescript to build voice experiences e.g. for Alexa, Google Assistant, etc. I have not tried it out yet, but it seems to be a cool project to build these kinds of experiences primarily around voice.
In comparison, Airy is a much more resource-intense backend service running conversational infrastructure that you couldn't run on comparable hardware. Airy is designed to run in the cloud giving you a Kubernetes cluster with all the components to stream conversational data at enterprise-scale. For now, we primarily focus on text-based communication, but could theoretically also support transcription and processing of voice based messages or live videos.
Thank you for the question, soorajchandran. We appreciate to see more open source tools in this space and believe that Chatwoot is a great choice when you are primarily looking for a cost efficient alternative to Intercom, Zendesk or basic contact center software with a UI for customer support agents.
What you get with Airy is enterprise-scale conversational infrastructure that can power millions of conversations simultaneously by ingesting messaging events in Apache Kafka, running in a dedicated Kubernetes cluster to stream and process conversational data for a variety of use cases, such as integrating with Conversational AI platforms or storing all your conversations in a data lake to run conversational analytics or train machine learning models based on actual conversations.
In that sense what we do is more like "Segment" for conversational data.
In our approach, we would rather like to integrate with for example live chat plugins provided by Intercom instead of replacing them at companies that already chose Intercom to serve their customers with a live chat plugin on their website or in their mobile apps. Airy also comes with a fully customizable open source live chat plugin and an Inbox UI for human agents, but it's not at the core of what we do.
We believe there is much more value to be gained from utilizing conversational data and we therefore like to integrate and play well with other solutions in the space as we believe that companies should have the freedom to choose the tech stack that best suits their requirements and budget restrictions.
Thank you for that question, michaelagustin. You are right: most popular SaaS tools in the conversational space are indeed priced per volume, usually per message or per (active) conversation.
As communication is core to every business, we strongly believe every company should own their conversations and utilize their conversational data in the best possible way, taking the interest and privacy of their customers into consideration.
We believe there is a unique opportunity now in the market to create an open source conversational stack and we would like to contribute to it with something we are good at and have a lot of experience in. Our goal is to create an open standard for the processing and storing of conversational data which is why we went open source.
This situation is perfectly suited from our perspective for an open core pricing model where we will continue to give away our Airy open source core platform for free under an Apache 2.0 license and sell additional enterprise licenses for optional features like advanced routing capabilities, team management, advanced storage and analytics solutions on top to enterprises that have additional requirements and more organizational complexity to deal with. Enterprises can run Airy Core + Airy Enterprise in their own private cloud or even on premise for privacy sensitive industries like banking, insurance or healthcare.
For business teams that want the full power of a conversational platform like Airy, but can't or don't want to dedicate engineering resources on their end, we also offer a fully managed Airy Cloud solution on the side. Because each Airy instance is fully independent, we can even offer this service in any region in case the relevant customer has preferences e.g. to store their conversational data exclusively in the EU or in a specific country or data center.
We love Matrix for their big vision to build an open network for secure, decentralized communication.
Airy has a more centralized approach from the perspective of a single organization. We want to give organizations an easy way to access all conversational data across their entire organization in a structured form and help them to utilize it, e.g. to train smarter machine learning models in the interest of their customers.
This is reflected in our mission of structuring the world's conversational data to power the future of customer experiences.
Hi renrutal, Steffen from Airy here. Thanks for your remark and I couldn't agree more with you which is why we don't pay-wall privacy features. Actually, nothing stops you from turning on encryption also in the open source version of Airy as Pascal pointed out above.
The topic you mentioned above comes from our pricing page for the Airy Enterprise Edition and is about an additional (!) and fully optional conversational data store for archiving conversations and to provide for conversational analytics use cases. We currently only offer this additional streaming option for enterprise customers with large amounts of conversational data by leveraging data lakes on economic cloud storage solutions like AWS S3. We strongly recommend to activate server-side encryption for this storage option.
