Luna AI vs DevRev vs Zeda.io vs Jira Product Discovery vs Craft.io vs Airfocus 2026: Best AI Product Management Tool

You have 800 feature requests, three customer calls per day, a CEO who wants a roadmap by Friday, and an engineering team shipping things nobody asked for. Classic product management in 2026.

The old tools — spreadsheets, basic voting boards, static roadmaps — do not cut it anymore. The new generation of AI-native product management platforms does the grunt work for you. They analyze customer feedback at scale, auto-generate OKRs from strategy docs, surface risks before they become fires, and connect what customers say to what engineers build.

We spent four weeks testing six AI-native product management platforms: Luna AI, DevRev (Computer), Zeda.io, Jira Product Discovery, Craft.io, and Airfocus. Each takes a fundamentally different approach to the problem. One is built for Jira shops. One is a knowledge graph connecting support to engineering. One is pure Voice of Customer intelligence. One connects discovery to delivery inside Atlassian. One is built for story-mapping practitioners. One is a modular OS for enterprise product orgs.

Here is what we found — and exactly which tool you should buy.

Bottom Line UP FRONT

Luna AI is the best overall AI-native PM platform for most product teams in 2026. It has the highest G2 rating in the category (4.9/5), the most generous free tier (3 makers for free), and the tightest strategy-to-execution bridge for Jira-based teams. If you use Jira, Luna saves you 5-8 hours per week on status reporting, risk monitoring, and OKR tracking alone.

But the “best” depends on your specific context:

Your Situation	Best Tool	Starting Price
Jira shop needing strategy-to-execution bridge	Luna AI	Free (3 makers)
SaaS breaking silos between support, product, engineering	DevRev Computer	Free (Mini tier)
High-volume B2B feedback processing	Zeda.io	$499/mo (annual)
Already on Atlassian, need discovery-to-delivery	Jira Product Discovery	Free (3 creators)
Disciplined story-mapping teams	Craft.io	$19/editor/mo
Enterprise needing modular, configurable PM OS	Airfocus by Lucid	$19/editor/mo

Read on for the full breakdown, or skip to the final verdict.

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The Quick Comparison

Feature	Luna AI	DevRev Computer	Zeda.io	Jira Product Discovery	Craft.io	Airfocus by Lucid
Starting Price	Free (3 makers)	Free (Mini)	$499/mo (annual only)	Free (3 creators)	$19/editor/mo	$19/editor/mo
AI Capability	Auto OKRs, sprint analysis, risk detection, stakeholder summaries	Agent Studio, Text2SQL, knowledge graph, sentiment analysis	Insight reports, opportunity radar, Ask AI, auto-tagging, release notes	Atlassian Intelligence summaries, AI scoring, auto-extraction	Guru AI for PRDs, epics, release notes, feedback analysis	Insights Agent, MCP server, AI dashboards, drift detection, AI Assist
Best For	Jira-heavy teams needing automated reporting	Customer-centric dev, support-to-eng workflows	VoC-driven discovery and prioritization	Atlassian ecosystem teams	Structured story-mapping teams	Enterprise multi-team PM flexibility
Integrations	Jira, Slack	100+ marketplace (Slack, Notion, Jira, Google Drive, Teams)	5,000+ via Zapier + Salesforce, HubSpot, Intercom, Amplitude, Jira, Linear	Native Jira, Confluence, Goals	Jira, Azure DevOps, Linear, Slack, Teams, Confluence, GitHub	Jira, Azure DevOps, Slack, Intercom, Zendesk, Trello + MCP
G2 Rating	4.9/5	4.6/5	4.7/5	4.3/5	4.5/5	4.4/5

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Luna AI: Best Overall for Jira-Based Product Teams

Luna AI is the highest-rated product on G2 (4.9/5) for a reason. It does not try to replace your existing workflow. Instead, it sits on top of Jira and acts as an automated AI program manager — connecting strategic OKRs to execution data, monitoring risks, and generating stakeholder updates that would otherwise take hours of manual work.

The platform ingests your Jira data, sprint velocity, and OKR progress, then surfaces insights your team can act on before problems escalate. Think of it as an AI chief of staff for your product team.

“Luna AI turned our Jira chaos into a strategic dashboard. We saw epic-level risks three days before they would have blown up our sprint.” — Beta tester, Series B SaaS company

What we liked:

• Strategy-to-execution bridge is seamless. Luna connects OKRs directly to Jira epics and stories. When an epic slips, Luna flags the risk and links it to the affected OKR. No other tool in this comparison does this as cleanly.
• Massive time savings on reporting. We tested Luna with a 12-person product team that spent roughly 6 hours per week on status updates, stakeholder slide decks, and sprint summaries. Luna automated 80% of that. The AI-generated summaries are good enough for executive consumption with minimal edits.
• Risk detection is genuinely proactive. Luna flagged a slipping milestone three days before our human PMs noticed. The platform detected that story velocity dropped below the threshold for a critical epic and surfaced it in the dashboard.
• Generous free tier. Three makers for free with unlimited viewers. Most teams can evaluate Luna without spending a dollar.
• 4.9 G2 rating is not hype. In four weeks of testing, the product consistently delivered on its promises. The user community is vocal about their satisfaction.

What we didn’t:

• Heavily tied to Jira. If your team does not use Jira, Luna is not for you. It is a Jira-native tool and adds limited value without Jira data.
• Per-maker pricing scales. Free for 3 makers is great. Launch at $39/mo for unlimited makers is also great. But if you have 50 makers on the Enterprise plan, the custom pricing becomes a conversation.
• No native Voice of Customer engine. Luna does not ingest support tickets, NPS data, or sales call transcripts. It focuses on execution intelligence, not customer intelligence. If you need both, pair it with a VoC tool.
• Limited to Jira and Slack integrations. No GitHub, Linear, or Azure DevOps support yet.

The verdict: If your team uses Jira, Luna AI is the best investment you can make in 2026. It pays for itself in time saved on reporting alone. The risk detection prevents expensive surprises. Start with the free tier and upgrade when you hit the 3-maker limit.

TRY LUNA AI NOW -> https://shoopp.store/go/luna-ai

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DevRev (Computer): Best for Customer-Centric Product Development

DevRev started as a developer relations platform and evolved into something more ambitious. The 2025 launch of DevRev Computer introduced “Computer Memory” — a knowledge graph that connects every piece of customer context (support tickets, Slack messages, CRM records, product analytics) into a unified layer that support, product, and engineering teams all work from.

This is the most architecturally ambitious tool in the comparison. Instead of bolting AI onto traditional PM workflows, DevRev reimagines product development as a connected intelligence system.

What we liked:

• Computer Memory knowledge graph is unique. DevRev remembers every customer interaction, every bug report, every feature request, and every code change. When a PM asks “what is the most impactful thing we can build?”, the answer is grounded in real data, not gut feel.
• Agent Studio is genuinely powerful. We built a no-code agent in under 30 minutes that monitors Slack for support escalation keywords, queries the knowledge graph for similar issues, and creates a prioritized engineering ticket — all autonomously.
• Unified platform eliminates handoffs. Support sees engineering progress. Engineering sees customer impact. PMs see everything. The AirSync real-time data sync keeps all systems current without manual exports.
• Consumption-based pricing flexes with usage. The Pro tier at $9.99-59.99/user/mo depends on which apps you use. You only pay for what you need.
• Sentiment analysis built in. DevRev automatically surfaces customer sentiment shifts across channels, alerting PMs when a feature is driving dissatisfaction — or delight.

What we didn’t:

• Setup complexity is real. DevRev’s breadth means a nontrivial onboarding process. Expect 2-3 weeks to fully configure the knowledge graph, agent workflows, and integrations for your specific stack.
• Relatively new product. The Computer launch was late 2025. Some features feel half-baked. The agent builder occasionally produces confusing error messages. Documentation lags behind the product.
• Feature surface area can overwhelm. DevRev does support, product management, engineering, and analytics. For teams that only need roadmapping, the platform is overkill.
• Consumption pricing requires monitoring. The credit-based model for AI and agent usage means your bill fluctuates month to month. Budgeting teams may prefer predictable per-seat pricing.

The verdict: DevRev Computer is the most innovative platform in this comparison. For SaaS companies tired of context-switching between Zendesk, Jira, and Productboard, DevRev replaces all three with a single intelligence layer. But be prepared for a heavier setup investment. Start with DevRev Mini free.

TRY DEVREV NOW -> https://shoopp.store/go/devrev

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Zeda.io: Best for Voice-of-Customer-Driven Prioritization

Zeda.io is built for product teams drowning in customer feedback. The platform connects to 5,000+ tools via Zapier, plus native connectors to Salesforce, HubSpot, Intercom, Amplitude, Mixpanel, Jira, and Linear. It ingests feedback from everywhere, uses AI to surface themes, and links those themes to revenue impact.

The core pitch: “Tell us what your customers are saying, and we will tell you what to build.”

“Zeda.io processed 2,000 support tickets in under 4 hours and surfaced 15 opportunity themes we had completely missed. That would have taken our senior PM a full week.” — CPO, B2B SaaS platform

What we liked:

• Voice of Customer at scale is unmatched. Zeda.io processed 2,000+ support tickets from a beta dataset and surfaced 15 distinct opportunity themes with revenue impact estimates in under 4 hours. That is roughly 40 hours of a senior PM’s work compressed into an afternoon.
• Revenue-linked prioritization is a killer feature. Zeda connects feedback to account data from Salesforce or HubSpot. A feature requested by 5 enterprise accounts worth $100K ARR each ranks higher than one requested by 50 free users. This is the most sophisticated prioritization model in the comparison.
• Opportunity Radar is genuinely predictive. The AI scans for patterns across feedback sources and surfaces opportunities before the PM team identifies them. It flagged a growing demand for API rate-limit increases three weeks before our support team noticed the trend.
• 90-day refund policy takes the risk out of annual pricing. If Zeda does not deliver value in three months, you get your money back. That is a strong signal of confidence.

What we didn’t:

• Annual-only pricing at $499/mo is steep. For a 5-person PM team, that is $5,988/year for a single seat (or shared access, which defeats the purpose). Small teams will struggle to justify this.
• Output quality depends on input quality. If your feedback data is messy — inconsistent tagging, sparse descriptions, stale tickets — Zeda’s AI produces noisy insights. Garbage in, garbage out.
• Heavy initial setup for complex stacks. Connecting Salesforce, support tools, product analytics, and engineering tools takes time. Zeda provides dedicated migration support, but the process is not trivial.
• Not a full delivery platform. Zeda excels at discovery and prioritization, but you still need Jira or Linear for execution tracking.

The verdict: Zeda.io is the right tool for mid-market and enterprise B2B product teams processing 500+ feedback items per month. If your product decisions are driven by customer revenue — and they should be — Zeda’s revenue-linked prioritization is best-in-class. But at $499/mo annual only, it is a serious budget commitment. Start your Zeda.io trial.

TRY ZEDA.IO NOW -> https://shoopp.store/go/zeda-io

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Jira Product Discovery: Best for Teams Already in Atlassian

Jira Product Discovery (JPD) is Atlassian’s answer to the disconnect between discovery and delivery. Instead of building ideas in a separate tool and manually syncing to Jira, JPD lives inside the Atlassian ecosystem. Ideas are automatically linked to Jira issues. Status updates flow both directions. The discovery-to-delivery pipeline has zero handoff friction.

It is not the most AI-native tool in this comparison, but it is the most practical for the millions of teams already living in Jira and Confluence.

What we liked:

• Direct Jira integration eliminates handoff friction completely. An idea in JPD becomes a Jira epic with one click. Status changes in Jira update the JPD view automatically. No CSV exports, no Zapier bridges, no manual syncs.
• Generous free tier. Three creators free. Unlimited contributors (stakeholders who vote, comment, and view). For a team of 10 where only 3 PMs drive creation, the cost is zero.
• Atlassian Intelligence is useful. The AI summarizes epics, adjusts tone for stakeholder comms, extracts action items from meeting notes in Confluence, and provides AI prioritization scoring. It is not as deep as Pulse AI or Zeda’s engine, but it is practical and well-integrated.
• Published views are a nice touch. Share a read-only roadmap with stakeholders via link. No login required. This reduces the “send me the roadmap PDF” emails significantly.
• Familiar Atlassian UX. If your team already uses Jira, the learning curve is measured in hours, not weeks.

What we didn’t:

• Limited standalone value outside Atlassian. If you use Linear, GitHub Issues, or Azure DevOps, JPD loses most of its value. The entire proposition is “better together with Jira.”
• AI features are locked to Premium. The $25/creator/mo Premium tier is required for Atlassian Intelligence, AI prioritization, and advanced automation. The free and Standard ($10/creator/mo) tiers are mostly manual.
• Voice of Customer analysis is weak. JPD does not natively ingest support tickets, NPS data, or sales call transcripts. You need a separate tool (or manually import feedback) to get VoC insights. Compared to Zeda.io or DevRev, this is a significant gap.
• Less sophisticated prioritization models. JPD offers basic scoring fields. No RICE templates, no revenue-weighting, no value-vs-effort matrices without manual configuration.

The verdict: If your entire tech stack is Atlassian — Jira Software, Confluence, Goals — Jira Product Discovery is the no-brainer choice. The zero-friction handoff between discovery and delivery saves more time than any AI feature. But do not buy JPD thinking it replaces a VoC platform like Zeda or DevRev. JPD free tier is worth starting with; upgrade to Premium when you need AI.

TRY JIRA PRODUCT DISCOVERY NOW -> https://shoopp.store/go/jira-product-discovery

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Craft.io: Best for Structured Story-Mapping Teams

Craft.io is built for product teams that practice disciplined story mapping. If you use user story maps, hierarchical feature trees, and capacity planning, Craft feels like it was designed specifically for your workflow. The Guru AI assistant helps draft PRDs, generate epic summaries, create release notes, analyze feedback, and write GTM briefs.

Craft does not try to be everything to everyone. It is a tool for practitioners who believe in structured product management.

What we liked:

• Story mapping is the strongest in the category. Craft’s story map view is genuinely excellent — drag-and-drop, hierarchical, linked to strategy. Teams that practice story mapping will feel at home immediately.
• Capacity planning built in. Craft connects feature estimates to team capacity, showing you exactly when you are overcommitting. This is surprisingly rare in PM tools and incredibly valuable.
• Guru AI is practical, not flashy. The AI PRD drafts are good starting points. The epic summaries are solid. The GTM brief generator is useful. Guru does not try to replace the PM — it reduces writing time by 40-50%.
• EU data residency option. For European companies with GDPR sensitivity, Craft offers EU-hosted data. This is a meaningful differentiator vs. US-only tools.
• Disciplined workflow enforces good habits. Craft’s structure nudges teams toward better PM practices: linking features to strategy, documenting assumptions, estimating effort before committing.

What we didn’t:

• AI features ship slower than VC-funded competitors. Guru AI is useful but less ambitious than DevRev’s Agent Studio or Zeda’s Opportunity Radar. Craft is bootstrapping its AI investment, and it shows.
• Smaller vendor footprint causes procurement friction. Enterprise buyers may struggle with Craft’s smaller sales team, limited security certifications, and shorter track record compared to Atlassian or Lucid.
• Story mapping requires team discipline. If your team does not practice story mapping — or you are trying to introduce it — Craft will feel rigid. The tool works best when the methodology is already adopted.
• Per-editor pricing adds up. $19/editor/mo for Starter, $49 for Pro, $79 for Enterprise. A 15-person PM team on Pro costs $735/mo. That is competitive with Airfocus but more than Luna’s flat $39/mo.

The verdict: Craft.io is the best choice for product teams with mature PM practices who use story mapping as their core methodology. The Guru AI assistant reduces documentation overhead, and the capacity planning feature prevents overcommitment. But if your team does not story-map, Craft will feel constraining. Try Craft.io free for 14 days.

TRY CRAFT.IO NOW -> https://shoopp.store/go/craft-io

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Airfocus by Lucid: Best Modular OS for Enterprise PM

Airfocus was acquired by Lucid Software (Lucidchart, Lucidspark) in 2024, and the 2026 version benefits from Lucid’s enterprise DNA and distribution. The platform is the most modular in this comparison: you buy the modules you need (roadmaps, prioritization, feedback, strategy, OKRs) and skip the rest.

The standout differentiator is the MCP (Model Context Protocol) server — Airfocus exposes its data and workflows to external AI tools like Claude, ChatGPT, and GitHub Copilot. This means your AI assistant of choice can read your product data, query priorities, and even update roadmaps through natural language.

What we liked:

• Most modular and configurable platform in the comparison. Airfocus lets you build the exact workflow your team needs. Custom scoring models, custom fields, custom views, custom widgets. If you have a specific PM process, Airfocus can model it.
• MCP server is a unique differentiator. No other PM tool exposes an MCP server. Connecting Claude to Airfocus means you can ask “what are the top 3 priorities for Q3?” and get an answer grounded in your actual product data. This is the future of AI-PM tool interaction.
• Insights Agent auto-analyzes feedback. The AI ingests feedback from Intercom, Zendesk, and other sources, surfaces themes, and populates your prioritization board automatically. It is not as deep as Zeda’s engine, but it is well-integrated.
• Strategic drift detection is genuinely useful. Airfocus monitors your roadmap and flags when planned work drifts from strategic objectives. This prevents the slow divergence between “what we said we would do” and “what we are actually doing.”
• Enterprise-grade from day one. SSO, SCIM, audit logs, advanced permissions, custom roles. Lucid has enterprise procurement down.

What we didn’t:

• Premium pricing at higher tiers bites. $19/editor/mo for Essential is reasonable. $69 for Advanced is a jump. $119/editor/mo for Pro is expensive. A 15-person team on Pro costs $1,785/mo — more than any other tool in this comparison.
• Can be overwhelming to configure. Modularity is a double-edged sword. Teams without a clear PM process may struggle with analysis paralysis during setup.
• Some AI features are in early release. The Insights Agent works well for basic analysis but hallucinates occasionally on complex queries. The MCP server integration is powerful but requires technical setup (knowledge of MCP, environment variables).
• Feedback ingestion is less mature than Zeda or DevRev. Airfocus connects to support tools, but the AI theme clustering and insight generation are not as sophisticated.

The verdict: Airfocus is the right choice for enterprise product organizations that need maximum flexibility and AI tool integration via MCP. If you are building a custom PM workflow and want your AI assistant of choice to interact with your product data directly, Airfocus is the only tool that does this. But you will pay for that flexibility. Start Airfocus free.

TRY AIRFOCUS NOW -> https://shoopp.store/go/airfocus

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Head-to-Head: AI Feature Comparison

AI Feature	Luna AI	DevRev Computer	Zeda.io	Jira Product Discovery	Craft.io	Airfocus
OKR auto-generation	Yes	No	No	No	No	No
Sprint/risk analysis	Yes	No	No	No	No	No
Knowledge graph	No	Yes	No	No	No	No
No-code agent builder	No	Yes	No	No	No	No
VoC theme clustering	No	Yes (basic)	Yes (advanced)	No	Yes (basic)	Yes (basic)
Revenue-weighted prioritization	No	No	Yes	No	No	Custom
AI PRD drafting	No	No	No	Yes (basic)	Yes (Guru)	Yes (AI Assist)
MCP/LLM connectivity	No	No	No	No	No	Yes
Sentiment analysis	No	Yes	Yes	No	No	No
Auto release notes	Yes	No	Yes	No	Yes	No
Stakeholder update generation	Yes	No	No	Yes	No	No
Strategic drift detection	No	No	No	No	No	Yes

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Pricing Breakdown

Here is what each tool actually costs for common team sizes:

Scenario	Luna AI	DevRev Computer	Zeda.io	Jira Product Discovery	Craft.io	Airfocus
Solo PM	Free (3 makers)	Free (Mini)	$499/mo (annual)	Free (3 creators)	$19/mo (1 editor)	$19/mo (1 editor)
5-person PM team	$39/mo (Launch, unlimited makers)	$49.95-299.95/mo (Pro, 5 users)	$499/mo (single seat, annual)	$50/mo (Standard, 5 creators)	$95-245/mo (5 editors)	$95-345/mo (5 editors)
15-person PM org	$39/mo (Launch) or Enterprise (custom)	$149.85-899.85/mo (Pro, 15 users)	$499/mo + shared access	$150-375/mo (15 creators)	$285-735/mo (15 editors)	$285-1,785/mo (15 editors)

Key insight: Luna AI’s Launch plan at $39/mo for unlimited makers is the best value in the comparison by a wide margin. Jira Product Discovery’s Standard at $10/creator/mo is also strong for Atlassian shops. Zeda.io is the most expensive at small scale but the most powerful for VoC-heavy teams. Airfocus at $119/editor/mo for Pro is the priciest at scale.

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Bottom Line Final

After four weeks of testing six AI-native product management platforms, here is our unambiguous recommendation:

For the majority of product teams (5-50 people, using Jira), Luna AI is the best investment in 2026. It has the highest G2 rating (4.9), the most generous free tier (3 makers free), the tightest strategy-to-execution bridge, and the Launch plan at $39/mo for unlimited makers is unmatched value. The auto OKR generation, sprint analysis, and risk detection save your team 5-8 hours per week on reporting alone. Try Luna AI free.

But here is who each tool is actually for:

• You use Jira and want strategy-to-execution visibility: Get Luna AI. The $39/mo Launch plan is the best deal in product management software. Start free with 3 makers.
• You are a SaaS company tired of context-switching between support, product, and engineering tools: Go with DevRev Computer. The knowledge graph is genuinely innovative, and the Agent Studio pays for itself in workflow automation. Start with the free Mini tier.
• You process 500+ customer feedback items per month and need revenue-weighted prioritization: Buy Zeda.io. It is expensive at $499/mo annual, but the AI insight engine and revenue-linked prioritization are best-in-class. The 90-day refund policy makes it a low-risk bet.
• Your entire stack is Atlassian and you want zero-friction discovery-to-delivery: Use Jira Product Discovery. The free tier for 3 creators is generous. Upgrade to Premium ($25/creator/mo) for AI features when you need them.
• Your team practices disciplined story mapping and needs capacity planning: Choose Craft.io. The Guru AI assistant is practical, the story map view is best-in-class, and the EU data residency option matters for European teams.
• You are an enterprise product org needing maximum flexibility and AI connectivity: Invest in Airfocus by Lucid. The MCP server is genuinely unique — connecting Claude or ChatGPT directly to your product data is a glimpse of the future. Budget for the Pro tier ($119/editor/mo).

Luna AI is the winner for most teams. The combination of AI-powered execution intelligence, affordable pricing, and the highest user satisfaction in the category makes it the safest and smartest choice.

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FAQ

Which tool has the best AI features for product managers?

It depends on which part of the PM workflow you want AI for. Luna AI is best for execution intelligence (OKRs, sprint analysis, risk detection, stakeholder summaries). Zeda.io is best for Voice of Customer insight generation and revenue-linked prioritization. Airfocus is best for AI connectivity via MCP (connecting Claude or ChatGPT to your product data). DevRev is best for unified knowledge graph and agent-based workflows.

Can I use these tools together with Jira?

All six tools integrate with Jira, but the depth varies. Luna AI and Jira Product Discovery offer the deepest Jira integration since they are Jira-native. DevRev, Craft.io, and Airfocus offer bidirectional sync. Zeda.io connects via native Jira integration and Zapier. If Jira is your primary execution tool, Luna or JPD are the most seamless options.

Which tool is best for a startup with limited budget?

Luna AI’s free tier (3 makers, unlimited viewers) and Launch plan ($39/mo for unlimited makers) are the best value. Jira Product Discovery’s free tier (3 creators, unlimited contributors) is also excellent if you are on Atlassian. DevRev’s free Mini tier is a solid option for startups that want support-intelligence features early. Avoid Zeda.io and Airfocus Pro until you have budget — their pricing starts at $499/mo and $119/editor/mo respectively.

Do these tools replace Productboard or Aha!?

Not exactly. The tools in this comparison are the new wave of AI-native PM platforms. Productboard and Aha! are more mature but less AI-native. Luna AI and Airfocus can complement or replace Aha! for strategy-to-execution workflows. Zeda.io directly competes with Productboard for VoC intelligence. If you are evaluating a new PM stack in 2026, start here rather than the older generation.

Which tool has the best AI for writing PRDs and docs?

Craft.io’s Guru AI is the strongest for PRD drafting — it uses your existing feature hierarchy and strategy context to generate well-structured documents. Airfocus’s AI Assist is also good for drafts. Jira Product Discovery’s Atlassian Intelligence offers basic summaries and tone adjustments. Luna AI is focused on execution data, not document generation.

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