DevTune connects AI search data, community discussions, traffic patterns, adoption metrics, and content analysis into a single view so you always know what to work on next.
Every action is backed by correlated evidence from multiple signals, not a single metric in isolation.
The intelligence layer turns your signal data into specific, actionable recommendations.
See what winning content does differently, and exactly how you can improve.
Build-ready briefs combine AI visibility, competitor context, owned content, and downstream signals.
Know what changed, what it means, and what to do about it before you even think to look.
Every signal, action, and evidence chain is accessible to your apps and autonomous workflows.
DevTune is built for founders, marketers, devrel and docs teams at developer tool companies who want to create data-informed content strategy.
You have no idea if ChatGPT recommends you or your competitors. Track your AI search rankings and citations across every major platform.
AI models cite sources you didn't know mattered. See exactly which docs, repos, and pages shape your recommendations.
Too much data, no clear next step. Get prioritized, AI-powered actions ranked by impact on your visibility.
Downloads and stars live in silos, disconnected from your GTM efforts. Connect adoption metrics to what actually drives discovery.
AI bots crawl your docs daily, but you can't see which ones or how often. Measure AI bot visits and referral traffic.
Developer conversations shape your brand and what AI models recommend, but teams can't monitor them. Track mentions, sentiment, and competitive context across Reddit, Hacker News, GitHub, and more.
You shipped a docs update 2 weeks ago. Did it move the needle? See correlations between your actions and growth signals.
When developers ask ChatGPT or Perplexity for a tool recommendation, you have no idea what they see or how they feel about you. DevTune tracks your rankings, citations, sentiment, and visibility across every major AI search platform so you can stop guessing and start optimizing.
Monitor how AI models respond to developer queries across all frontier models
Track your position over time and identify when your product or brand gains or loses visibility
Discover what questions developers ask that your documentation doesn't answer
See how you stack up against your competitors in AI search results
Find every single citation of your owned surfaces along with competitors and third-party sources
Define your own search topics and prompts and track the metrics that matter most
Test AI Search presence across ChatGPT Search, Perplexity, Google AI, xAI (with more platforms coming soon)
Not all search queries are created equal. Understanding the difference between competitive and opportunity-based prompts is key to optimizing your AI search presence.
AI models pull from your docs, GitHub issues, and Stack Overflow to form recommendations. But which sources are they actually using? DevTune traces every citation back to its source so you know exactly what to improve.
See exactly where AI models pull information from: docs, GitHub, StackOverflow, and more
Understand which prompts trigger the most accurate and relevant responses about your SDK, product or brand
Compare citation frequency and prominence between your product/brand and competitors across AI responses
Identify areas where your documentation is missing or needs improvement to boost AI visibility
Understand the quality and authority of sources AI models reference for your product or SDK
Get detailed reports on how different sources contribute to AI model knowledge about your SDK, product or brand
Most teams make content decisions based on intuition, not data about what AI models actually surface. DevTune analyzes your results across multiple signals, identifies the highest-impact opportunities, and tells you exactly what to do next.
Get intelligent analysis of your data with actionable insights powered by advanced AI
Focus on what matters most with automatically prioritized improvements based on impact
Receive specific recommendations to improve documentation, examples, and discoverability
Get notified when competitors make moves that affect your market positioning
Machine learning identifies patterns and suggests optimizations you might have missed
GPTBot, ClaudeBot, and PerplexityBot crawl your docs daily, and AI platforms refer developers to your site. DevTune identifies every AI visitor and referral so you can measure the real impact.
Identify visits from GPTBot, ClaudeBot, PerplexityBot, and other AI crawlers to your documentation
Measure traffic coming from ChatGPT, Claude, Perplexity, and other AI platforms
Visualize AI-driven traffic patterns over time to identify growth opportunities
Connect your AI search visibility with actual traffic and adoption metrics
DevTune connects adoption and star metrics to AI visibility and community signals so you can see how your content efforts are driving growth.
Monitor star counts and growth trends for your repositories and competitor projects
Track weekly download counts from npm, PyPI, crates.io, NuGet, RubyGems, and more
See how changes in AI search visibility correlate with downstream adoption metrics like downloads and GitHub stars
Compare your adoption metrics side-by-side with competing SDKs in your space
Access nightly snapshots of adoption metrics for long-term trend analysis
Track packages across all major registries from a single unified dashboard
What developers say on Reddit, Hacker News, Stack Overflow, Dev.to, and GitHub Issues & Discussions directly shapes your brand perception and what AI models recommend. But most teams have no way to monitor these conversations or connect them to outcomes. DevTune surfaces every relevant thread and shows how community activity tracks with your visibility and growth.
Monitor threads mentioning your brand, competitors, and relevant topics across major developer communities
Track how developer sentiment and discussion volume change over time after product updates or launches
See exactly how developers talk about your tool: pain points, praise, feature requests, and comparisons
Aggregate signals from Reddit, Hacker News, Stack Overflow, Dev.to, GitHub Issues & Discussions, and other developer communities
Content and docs changes take days or weeks to show impact. Without a way to connect actions to outcomes across every signal, teams can't prove ROI. DevTune's timeline overlays your content events with AI visibility, web traffic, adoption, and community changes so you can see what's working (and what's not).
See AI presence rate, community threads, citations, and content changes on a single time-series chart
See how your content actions correlate with visibility changes using realistic lag analysis
Layer community activity, page outcome citations, and content changes alongside AI presence trends
Mark key events - doc updates, launches, competitor moves - and track their downstream impact
DevTune is built API-first, with AI agents as first-class consumers. Integrate visibility data into your agentic workflows and automated monitoring systems through REST API, Webhooks, and MCP.
Programmatic access to DevTune capabilities. Pull AI search rankings, citation data, and visibility metrics for any project or prompt, export analytics data, and retrieve actions and insights. Designed for automation-first teams and agentic pipelines.
Get real-time notifications when tests complete, scores change, or competitors move. Push events directly to your agents, Slack, or any HTTP endpoint.
Expose DevTune as a tool to any AI agent via Model Context Protocol. Your agents can query visibility data, retrieve prioritized actions and ready-to-execute content briefs, and act on them without leaving their workflow.
Track your SDKs across major package registries and development platforms
DevTune connects AI visibility, adoption, community, traffic, and competitive data so you can focus content efforts on the right things.
Plans from $49/mo • Enterprise options available
Find answers to common questions about DevTune