Comparing Dialpad Ai and Level AI? Both are Agent Assist & Copilots and Contact Center & CCaaS tools in the directory, which is why buyers put them on the same shortlist. Below is a side-by-side look at how they price, what they integrate with, and when each is the better fit, so you can pick on the facts rather than either vendor's own sales page.
| Attribute | Dialpad Ai | Level AI |
|---|---|---|
| Pricing | Paid · $15/user/mo | Paid · Custom |
| Founded | 2011 | 2019 |
| Categories | Agent Assist & Copilots Contact Center & CCaaS Voice & Phone AI | Agent Assist & Copilots Contact Center & CCaaS QA & Conversation Analytics |
| Integrations | Salesforce Zendesk Google Workspace Microsoft Teams HubSpot ServiceNow | Genesys NICE CXone Five9 Talkdesk Salesforce Zendesk |
Dialpad's founders have been building phone systems for the internet age longer than almost anyone: CEO Craig Walker previously created the products that became Yahoo Voice and, via GrandCentral, Google Voice. Founded in 2011, Dialpad is a cloud phone system and contact center with AI baked into every call, and its 2018 acquisition of voice AI startup TalkIQ, roughly $50 million, turned out to be the masterstroke. That technology, matured into DialpadGPT and trained on billions of minutes of business conversations, now powers live transcription, sentiment analysis, real-time coaching cards, automatic summaries, and AI scorecards across the platform.
For support teams the draw is having telephony, contact center, and support AI from one vendor. Dialpad Support, the contact-center product, starts around $80 per user per month, while the base Connect phone system starts at $15, and unusually for the industry the core AI features are bundled into standard plans rather than sold as add-ons. Newer agentic AI agents that autonomously handle scheduling, order lookups, and ticket updates are priced per conversation on a quoted basis. Integrations cover Salesforce, Zendesk, HubSpot, ServiceNow, Google Workspace, and Microsoft Teams.
The company was valued at $2.2 billion after an ICONIQ-led round in 2021 and has raised roughly $450 million from investors including Andreessen Horowitz and Google Ventures.
Dialpad fits teams that want to consolidate: if you are buying a business phone system anyway and support runs heavily on calls, getting transcription, coaching, QA, and virtual agents in the same box is genuinely efficient. Voice-AI purists may prefer a specialist like PolyAI; pragmatists consolidating vendors will like Dialpad a lot.
Read the full Dialpad Ai listing → · See Dialpad Ai alternatives →
Level AI is what happens when someone who helped build Amazon's Alexa turns the same technology on the contact center. Founder Ashish Nagar worked on the Alexa Prize conversational AI effort before starting Level AI in 2019, and the product's core bet is that quality assurance should be about meaning, not keywords. Its semantic engine scores every conversation against your rubrics by understanding intent, so an agent who solved the problem politely but never said the magic phrase still scores well, and one who recited the script while losing the customer does not.
Automated QA is the anchor, and around it the platform builds the full intelligence loop: real-time agent assist that surfaces answers from your knowledge sources during live conversations, voice-of-customer analytics that tell leaders what is driving contacts and sentiment, agent screen recording for the full picture, and AI virtual agents for handling routine interactions outright. It integrates with the usual suspects, including Genesys, NICE CXone, Five9, Talkdesk, Salesforce, and Zendesk.
The company, based in Mountain View, has raised about $73 million, most recently a $39.4 million Series C led by Adams Street Partners, and counts Vistaprint, Purple, Extra Space Storage, and Smartsheet among its customers. Pricing is quote-based with nothing public, typical for the category.
Level AI competes most directly with Observe.AI and the QA suites inside bigger platforms, and the honest differentiator is its semantic scoring and analytics depth. Shortlist it if your QA program has outgrown checklists and you want conversation data treated as a source of insight rather than a compliance chore, especially if you run a mid-size to large team on one of the contact-center platforms it plugs into.
Read the full Level AI listing → · See Level AI alternatives →
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