NM Signals vs Propane: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of NM Signals and Propane — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

NM Signals

Nyman Media

Freemium

Audits whether AI crawlers and assistants can actually read your website, then tracks how often they mention your brand.

AI Readiness Audit: Scores a public URL across 106 checks in six categories — crawlability, structured data, entity clarity, content structure, answerability and trust signals — for a readiness score out of 100.
Served-vs-Rendered Comparison: Measures how much of the browser-rendered page survives a fetch-only request, flagging JavaScript-dependent content that non-rendering AI crawlers never see.
AI Crawler Access Checks: Reports robots.txt, canonicals, redirects and status codes specifically for AI crawlers such as OAI-SearchBot, not just traditional search bots.
UX Review with Developer Brief: Runs a separate usability pass with visual layout analysis on paid plans and produces a copyable brief a developer can work straight from.
Saved Action Plans: Keeps an audit as a private baseline, lets you rank findings by priority, and records implementation progress against it.
Generated Fixes and Verification: Premium plans generate implementation guidance for a selected finding and verify the change against a fresh audit rather than trusting a checkbox.
AI Answer Snapshots: Asks the same five core questions weekly with three samples each, deciding by majority whether the brand is named, and charts the trend against tracked competitors.
Programmable Surface: A public REST API, CLI and MCP server let audits run inside CI/CD pipelines or be called directly by AI agents.

AI Search Readiness: Find out why an AI assistant summarizes a competitor's page instead of yours and fix the specific access or rendering issue behind it.
Pre-Launch QA: Audit a new marketing site before launch to catch blocked crawlers, missing markup and unreadable server-rendered content.
CI/CD Regression Guards: Call the REST API or CLI on every deploy so a rendering change that hides content from crawlers fails the build.
Brand Monitoring: Track weekly whether AI assistants name your brand in answers to the questions your buyers actually ask.
Agency Reporting: Produce white-label PDF audits and score comparisons for client sites on the Partner plan.
Content Restructuring: Use heading/body agreement and attribution checks to rewrite pages into retrievable, quotable sections.

Paid

A product-management system that connects all your customer data into shared context for product teams and their AI agents.

Customer Data Connection: Connect every tool, interaction and competitor into one place so your whole team and agents see the same context.
Context in Minutes: Link your stack and surface your first customer context within minutes of setup.
Signal Extraction: Turn each data point into a real, actionable signal teams can build from rather than raw noise.
Collaborative Canvases: Prioritize, sketch and shape roadmaps together in shared spaces with full context.
Agent Hand-off: Hand the full context to AI agents so they work with more accuracy, higher quality and faster shipping.
Stack Integrations: Unlimited integrations with HubSpot, Intercom, Slack and other product tools.

Roadmap Prioritization: Decide what to build next using connected customer signals instead of guesswork.
Customer Intelligence: Centralize fragmented customer and competitor data into one queryable context.
Agent-Assisted Building: Give AI agents full product context so they ship higher-quality work faster.
Cross-Team Collaboration: Let the whole product team work from a single shared source of truth.
Competitor Tracking: Keep an indexed, up-to-date view of competitor activity for product decisions.