Productboard
6.3/10Productboard is a product management platform with a built-in AI agent, Spark, that analyzes customer feedback, ranks opportunities, drafts specs, and manages roadmaps for product teams.
Data last updated November 2026 · Our methodology
Overview
Productboard started in 2014 as a place where product teams collect customer feedback, prioritize features, and build roadmaps. It now presents itself as an agentic product system built around Spark, an AI agent that works from the workspace's own data. Spark connects feedback to strategy, OKRs and personas. It produces voice-of-customer reports that cite the source notes, surfaces findings, and ranks opportunities by evidence. Once you connect a GitHub repository, it can draft delivery-ready specs grounded in your codebase. It also writes release notes and status updates, and after launch it compares results with each spec's success metrics, using analytics tools such as Amplitude, Pendo and Hex. Productboard's MCP server can send specs to coding agents such as Claude Code, Codex and Cursor. Native integrations include Slack, Notion, Confluence, Google Drive, Gong, Intercom, GitHub, Linear, Jira and Azure DevOps. Salesforce is Enterprise-only. Pricing is per maker, meaning each person who edits, with a five-maker minimum. Contributors are free: 25 on Business and unlimited on Enterprise. Each plan includes a monthly pool of AI credits, and extra credits are sold in bundles. The current pricing page lists only Business and Enterprise and gives no prices, so you have to get a quote. The product suits mid-size and enterprise product organizations that want AI analysis tied directly to their feedback and roadmap. Its main drawbacks are cost and complexity. Reviewers often mention a steep learning curve, and the per-maker model with credit metering makes costs climb as more people need edit access.
Our Rating
AI Software6.4/10
Project Management6.3/10
Who Productboard is best for
Best software for Product TeamsGood fit
Spark is aimed specifically at product managers, covering feedback analysis, opportunity ranking, specs and roadmaps.
Codebase-grounded specs, the GitHub integration and MCP handoff to coding agents fit software companies that ship continuously.
The Enterprise plan adds SAML SSO, SCIM, audit logs, custom roles, multiple workspaces and on-prem Jira support.
Reviewers describe it as best suited to mid-sized and large companies with dedicated product managers.
Less suited
The five-maker minimum, unpublished pricing and steep learning curve are a poor match for very small teams.
Reviewers repeatedly call it costly for small teams, and it has no current published free tier.
Pros & Cons
Pros
- Spark works from the workspace's own feedback, strategy and OKRs, and its insights link back to the source customer notes.
- Specs can be grounded in a connected GitHub codebase and sent through MCP to coding agents such as Claude Code, Codex and Cursor.
- There are many integrations: Slack, Gong, Intercom, Notion, Confluence, Linear, Jira and Azure DevOps, plus MCP connectors for Amplitude, Pendo and Hex.
- Contributors who only view or add feedback are free (25 on Business, unlimited on Enterprise), so only editors need paid maker seats.
- It holds ISO 27001:2022, SOC 2 Type II and ISO 42001, encrypts data with AES-256 at rest, and supports SAML SSO.
Cons
- The pricing page shows no prices, and both plans need at least five makers, which raises the entry cost.
- Usage-based AI credits come on top of seat costs, and Spark features pause when credits run out until renewal or a top-up.
- Capterra and G2 reviewers often report a steep learning curve and say the data model is hard to master.
- SAML SSO, SCIM, audit logs, Salesforce integration and onboarding services are Enterprise-only.
- Data is hosted only in AWS us-east-1 in the USA, with no private or self-hosted deployment option documented.
Key Features
Not included
- Private Deployment
Productboard Pricing
Business
- 2 product portals
- 25 free contributors
- Prioritized email support
- API access, Google SSO and MFA
- Sold via demo, no public price
- 500 AI credits per maker per month
- Up to 5 Jira and 5 Azure DevOps integrations
- Minimum 5 makers, added any time with prorated billing
- Roadmaps, prioritization, customer insights, feedback forms and automations
- Spark AI chat, feedback summaries, findings, scheduled tasks, MCP, skills and document sources
Enterprise
- Unlimited contributors
- Contact sales for pricing
- AI Themes and objective hierarchy
- Efficiency and allocation reports
- Whitelabeled portal and multiple workspaces
- Salesforce integration and on-prem Jira/Azure DevOps
- Expedited support, onboarding and professional services
- 1,500 base AI credits per month plus 800 per additional maker
- Custom roles, required fields, entity renaming and closed teamspaces
- SAML SSO, SCIM, Google SSO enforcement, IP whitelisting and audit logs
Frequently Asked Questions
As of November 2026, the official pricing page lists only Business and Enterprise and gives no prices. Business is sold via demo and Enterprise via sales. Both require at least five makers, and annual billing saves 21%. Third-party articles from August and September 2026 reported a Business price of $59 per maker per month on annual billing or $75 on monthly billing, but the official page no longer shows it.
Business includes 500 AI credits per maker each month. Enterprise includes 1,500 base credits plus 800 per additional maker. Analyzing 100 feedback items uses about 30 to 50 credits, and a full spec uses 50 to 200. Top-ups cost $5 per 50 credits on monthly plans or $60 per 600 credits on annual plans. When credits run out, Spark features pause but the workspace stays accessible.
No. Spark is included in both plans. Admins of existing workspaces can enable it. Some capabilities, such as evidence-ranked opportunities, MCP push to dev tools and post-launch evaluation, were marked beta in the June 2026 announcement.
Productboard says it meets ISO 27001:2022 and SOC 2 Type II and lists ISO 42001 certification. It encrypts data at rest with AES-256 and hosts on AWS us-east-1 across three availability zones. Its security page does not say whether customer data is used to train AI models.
Yes. REST API v2 supports personal API tokens and OAuth 2.0, including server-to-server JWT. It also offers webhook subscriptions and an MCP server that AI agents and coding tools can connect to.
Makers are the people who create and edit, and they are billed. Contributors don't count toward the maker total: Business includes 25 and Enterprise has no limit. You can add makers at any time, with prorated billing for changes mid-cycle.
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Ranked near Productboard in AI Software
See Productboard in the listProductboard is #201 in AI Software by our score.
