Spark, AI built for product managers

Frequently Asked Questions

In simple terms, what is Productboard Spark?

Spark is a specialized product management agent that accelerates some of the most time-consuming aspects of taking an initial idea to a well-defined specification.

Product managers and other collaborators can interact with Spark through a conversational interface to explore product ideas, inquire into customer needs (based on actual customer requests and feedback), and generate documents like product briefs, product requirement documents (PRDs), user research reports, competitive intelligence, product launch materials, and more.

As an AI agent, Spark can create new documents and edit existing documents. These documents can then be collaborated over with colleagues and further refined with help from AI. Moving forward, they can then be used as context in future AI prompts. For example, you could prompt Spark to generate a product specification based on context drawn from your Product strategy doc, User personas doc, and PRD template.

How does Spark differ from other AI tools?

Unlike generic AI tools:

• Spark provides more relevant responses based on knowledge of your product, customers, and business. It can tap into a wealth of information your organization has captured in documents (product strategy docs, product briefs, user personas, competitive intelligence, company objectives, and more…) in addition to collected customer feedback.
• The collection of documents that Spark employs as context is not confined to a specific chat/session or even a given initiative. It persists from one initiative to the next and can be collaboratively refined by you and your colleagues (with help from Spark!). Anyone in the organization can then tap into this shared knowledge as context when submitting future AI prompts.
• As an agent, Spark does not just respond to queries. It can create new documents and revise existing ones. Revisions are displayed as tracked changes that users can accept/reject.
• You can use customizable document templates to guide Spark as it generates certain types of content — for example, to ensure Spark includes the right types of information when generating a product requirements doc.

What are Jobs?

Jobs are guided, step-by-step workflows in Spark that help you complete complex PM tasks with expert guidance. Instead of starting with a blank prompt, Jobs lead you through proven methodologies - asking the right questions at each stage to produce high-quality, strategy-aligned deliverables.

Examples of jobs available within Spark:

• Product Brief: Draft concise, delivery-ready product briefs with structured guidance
• Competitive Analysis: Research and analyze competitive solutions to inform your strategy
• Feedback Analysis: Synthesize customer feedback into actionable insights

Two key benefits:

1. PM best practices built in: Jobs codify expert PM methodologies into agentic workflows, so you get senior-level outputs without needing years of experience
2. No prompt engineering required: Jobs are optimized to generate high-quality results automatically, so you don't need to be an AI expert to get professional deliverables

Each Job walks you through multiple steps, connects to your product context and customer feedback, and creates polished documents you can share with stakeholders immediately.

Can I connect Spark to other tools I use?

Spark connects to external tools in two ways:

Integrations let you sync data from platforms like Confluence, Google Drive, and Notion directly into Productboard for analysis.

Connectors (powered by the Model Context Protocol) let you interact with tools like Amplitude, Hex, Pendo, and Linear directly within Spark chats - querying data, searching docs, or creating tasks without switching apps. You can also set up custom connectors for other tools.

Spark respects your existing permissions in connected platforms and only accesses what your account is authorized for.

Click here for more information on how to connect your tools to Spark.

What AI is used to power Spark?

Spark is powered by large language models by Anthropic and OpenAI. If you choose to use Productboard’s AI capabilities, you agree to Anthropic, OpenAI, and Amazon Bedrock being subprocessors of your data. For more information, please review Productboard’s list of subprocessors.

What data does Spark use?

Spark can access any documents you provide in your workspace in addition to customer feedback notes and associated data. In the near future, Spark will be able to access additional product data in your workspace to carry out more actions and provide more responses.

Spark follows Productboard's standard security and privacy practices. Your data remains within your workspace and is not used to train external AI models.

For more information, see Productboard's AI Terms.

Have additional questions? Send us an email to hello@productboard.com