Spark is the evolution of Pulse and Productboard AI
Productboard Spark includes (almost) everything Productboard Pulse and Productboard AI offered, plus the organizational intelligence and spec generation that make it the natural next step for your team.
Also, Spark is already included in Productboard! You just need to activate it in your workspace.
In this article:
- Context
- Feature comparison
- Why teams are moving to Productboard Spark
- How to move to Productboard Spark
- See also
Context
Productboard AI was our first step into natural language processing and assistance. It helped teams connect the feedback they collected to the features they were building, and it did that well.
Productboard Pulse pushed that further. It added conversational AI for feedback analysis, generated insight reports on demand, and (for the first time) worked as a standalone tool without requiring the full Productboard platform.
Productboard Spark is where that work leads. Spark doesn't just summarize your feedback or generate a report when you ask. It continuously watches your connected data (feedback, competitive signals, your codebase, your existing Productboard workspace) and surfaces the opportunities worth your attention before you go looking for them. When you're ready to act on one, Spark drafts a delivery-ready spec grounded in your product's actual codebase and strategy, not a generic first draft you still have to fix.
The result is less time spent triaging feedback and reading through hundreds of tickets, and more time spent on the decisions only you can make.
Feature comparison
Here's how the three compare, not including elements of the core Productboard platform:
Note: AI search for relevant insights and insights auto-linking require a product hierarchy to function. Since product hierarchies are part of the core Productboard platform, the standalone version of Productboard Pulse can't make use of these capabilities.
Why teams are moving to Productboard Spark
Productboard AI and Productboard Pulse both asked you to bring the question. Spark brings you the answer before you knew to ask.
A few ways that shows up day to day:
- Connect a feedback source (Zendesk, Gong, or Intercom, for example) and Spark reads, classifies, and synthesizes it into a prioritized set of opportunities. Teams have gone from 500 unread feedback items to one clear signal in a single session.
- Open a new spec and Spark already knows your strategy, your target customers, and what your customers have been asking for. The first draft is grounded in your actual codebase, not a generic template.
- Every insight Spark surfaces traces back to the customer conversation, ticket, or usage signal behind it. You can drill into the evidence before you act on it.
- Specs live as shared, real-time documents. Your PM, designer, and engineer work in the same doc instead of passing files back and forth.
- The longer your team uses Spark, the more it knows. Institutional knowledge compounds at the team level instead of living in one person's chat history, so it survives reorgs, onboarding, and attrition.
Productboard AI and Productboard Pulse helped you process what you already knew to look for. Spark does that work continuously, and grounds it in your product's own reality.
How to move to Productboard Spark
If you're currently on Productboard AI or Productboard Pulse and want to move to Productboard Spark, contact your account team to learn more about the future of those products.
As for Spark, it's already in your workspace. You just need to activate it.