Intervo

Intervo runs the two channels most businesses actually use. A chat widget handles text conversations on your website, while voice agents take and place calls. The company notes that voice agents and chatbots behave differently, since one talks and the other types, and says it covers both so you aren't stitching together two vendors. For a support desk, that means a customer can start in a chat window and later call the same line without you rebuilding the knowledge base.

The core is open source, and the site points to a Git repository you can clone, customize and deploy yourself. That is the part that separates Intervo from most voice-agent SaaS tools, which keep everything on their own servers. Self-hosting appeals to teams with data rules or a preference for owning their stack. The site is upfront about the tradeoff: running it yourself means setup, hosting and scaling fall to your own technical staff.

The build flow is short and written for non-developers. You define the agent's purpose with a prompt that generates a workflow, add knowledge by uploading documents, pick a voice and publish. The company bills this as no-code, and the four steps map to how a small team would actually get an agent live without a project manager. Templates and orchestration frameworks are there if you want a faster start than building from scratch.

Voice quality is where a voice agent lives or dies. Intervo draws on established providers rather than build its own. You choose from a range of voices powered by ElevenLabs or Azure, then hear how the agent sounds before it faces a customer. Since the voice is the most audible part of every call, the ability to audition and change it without touching code is a practical detail, not a footnote.

A connected phone number turns an agent from a website helper into something anyone can dial. Intervo uses a Twilio integration to manage calls and engage customers in real time, so a support line or a sales callback number can run on the same agent that answers your chat. For businesses whose customers prefer the phone, this is often the feature that decides whether the product fits at all.

Two features push past basic Q&A. Real-time translation lets the agent understand, translate and respond across languages. That helps global teams avoid hiring bilingual staff for every market. On the sales side, the agent scores each interaction against custom criteria like budget, project needs and timeline. It then adapts its questions to pull out the details that matter. Both are the kind of capability that shows up once an agent has real conversations to learn from.