
How Quarterzip and Cora AI compare

What your business needs

What your business needs
What your business needs
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What your business needs
Guidance model

Guidance model
Proactive agents lead the conversation in real time

Proactive agents lead the conversation in real time
Workflow automation that acts on customer signals - no direct user guidance

Workflow automation that acts on customer signals - no direct user guidance
Interface

Interface
Voice and screenshare, multi-modal

Voice and screenshare, multi-modal
CSM-facing dashboards and workflow triggers - not user-facing

CSM-facing dashboards and workflow triggers - not user-facing
AI capabilities

AI capabilities
Native voice agent with computer vision, multi-modal conversation

Native voice agent with computer vision, multi-modal conversation
Agentic automation across CS channels and workflows

Agentic automation across CS channels and workflows
Cross-app support

Cross-app support
Yes, across browser tabs and third-party tools

Yes, across browser tabs and third-party tools
Connects to post-sales stack via integrations - not present in the user's workflow

Connects to post-sales stack via integrations - not present in the user's workflow
Time to live

Time to live
Two weeks, done-for-you

Two weeks, done-for-you
Implementation varies by stack and scope

Implementation varies by stack and scope
What you learn

What you learn
Customer goals, friction points, qualitative reasoning✕Health signals, usage

Customer goals, friction points, qualitative reasoning✕Health signals, usage
Health signals, usage patterns, churn risk - no qualitative session context

Health signals, usage patterns, churn risk - no qualitative session context
Pricing

Pricing
Fixed monthly, unlimited usage

Fixed monthly, unlimited usage
Varies by implementation scope and integrations

Varies by implementation scope and integrations
Why do companies choose Quarterzip over Cora AI?
Both Cora and Quarterzip are working on AI diffusion, but they’re working on it from different ends of the workflow.
Agents that talk to the user
Cora acts on data about the user, what they clicked, what they didn't, where the health score dropped, which playbook should fire. The data is useful and the workflow automation is genuinely capable. What it doesn't include is the actual conversation with the user about what they're trying to do and why they're stuck. Quarterzip is that conversation.
Multi-model agent using voice and screenshare
Guidance personalised to every users goals
Mirrors how humans naturally learn and collaborate

Activates AI features that the data layer can't fix
The activation gap on AI features isn't a workflow problem the CSM can solve with better alerts. The user looking at a new AI capability is trying to work out what it does, whether to trust it, and whether it's worth changing the way they've been doing the job for years. None of that surfaces in a usage signal until after the user has already decided. Quarterzip is in the conversation while the decision is being made.
Guides users through goal-based workflows
Role-specific permissions and visibility
A product expert for every user

Operates at the diffusion layer, not the operational one
Cora's lift comes from making the post-sales team more efficient. Quarterzip's lift comes from making the product more usable to the people it was built for. Both are real, but they're measuring different things. Efficiency is a denominator move. Diffusion is a numerator move, it's the AI capability the company has already shipped actually reaching the users who pay for it.
Reaches users in real time
Activates users directly
Doesn't depend on the post-sales team to scale

No code, live in two weeks
Quarterzip's set up is done for you, meaing no engineering work on your end. Cora integrates into the existing post-sales stack, which depending on scope can take longer to implement and configure across the workflows it's automating.
No engineering work on your end
Live in two weeks, regardless of your existing stack
No integration project, no configuration cycle


Quarterzip is built different, by design.
Trusted by fast growing companies
FAQ
Is Quarterzip a Cora AI alternative?
The two products share a buyer and overlap on outcomes, but they sit at different layers of the post-sales problem. Cora is workflow automation for the post-sales team, signals, playbooks, escalations, orchestration across the customer lifecycle. Quarterzip is the interface layer for users: a voice agent that talks to the user, watches their screen, and walks them through new capability in the moment. Teams sometimes evaluate both, and sometimes both end up deployed, but they're built for different parts of the same problem.
Why does Quarterzip work at the interface and not the workflow?
Diffusion happens in the moment a user encounters new capability and decides what they think of it. Workflow automation can act on signals about what the user has done, but it can't be in the conversation while the decision is being made. AI features especially get accepted or rejected in the user's first few sessions, and the decision is hard to reverse later. Quarterzip is built to be in the room when that decision is forming.
Does Quarterzip replace the CSM team?
No. Quarterzip handles the repeatable conversations that follow a pattern, the activation calls, the feature walkthroughs, the moments where a user needs to be guided through something, which frees CSMs to focus on the strategic relationships, expansion, and the work that needs a human. Apollo runs both: Quarterzip on activation, CSMs on the customer relationships that depend on a human owner.
Does Quarterzip give me analytics like Cora?
Quarterzip captures qualitative and behavioural insight from every call: user goals, friction, sentiment, what users did on screen, and where they got stuck. The Insights Hub surfaces all of it. Cora's analytics are oriented toward post-sales workflow signals, health scores, usage patterns, expansion triggers, across the customer lifecycle. The two produce different shapes of data because they're acting on different parts of the problem.
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