Justblank vs Thinking Orbs: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Justblank and Thinking Orbs — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Justblank
Justblank
Full-cycle AEO platform that turns competitive insights into actionable content to boost brand visibility in AI search.
Key features
- AEO Analytics: Provides free analytics that reveal how AI engines interpret and rank a brand's content, surfacing gaps and opportunities versus competitors.
- AI-Guided Content Creation: Generates and rewrites content tailored to AI search signals, with guidance to align copy with what AI engines prefer for higher visibility.
- Competitive Insights Dashboard: Aggregates competitor content and ranking signals to highlight differences and suggest prioritized actions for content strategy.
- Content Scoring & Measurement: Scores pages and content against AEO criteria and tracks performance changes over time to measure impact of optimizations.
- Actionable Workflows: Converts analysis into step-by-step editorial recommendations and execution plans so teams can turn insights into published content updates.
- Monitoring & Alerts: Tracks brand visibility across AI search endpoints and surfaces changes or opportunities so teams can react quickly to shifts.
- Free AEO analytics to show how AI engines understand and rank content
- Content creation and guidance optimized for AI search
- Automated content rewriting and optimization suggestions
- Measurement and analytics for content performance in AI search
- Competitive insights to identify opportunities and gaps
- Actionable execution tools to turn insights into content changes
Best for
- Optimizing existing website pages to improve how AI search engines surface and summarize brand content, increasing discoverability.
- Running competitive AEO analysis to identify which competitors AI engines prefer and prioritizing content rewrites to close gaps.
- Generating AI-guided rewrites or new content briefs for SEO and editorial teams to align copy with AI search ranking signals.
- Monitoring changes in AI-driven rankings and summaries to validate the impact of content updates and iterate on strategy.
- Equipping marketing and branding teams with prioritized, actionable tasks that translate analytics into publishable content changes.
- Providing agencies with a repeatable workflow to deliver AEO services to multiple clients, combining insights, content creation, and measurement.
- Marketing teams optimizing site content for AI/answer-engine search visibility
- Brand teams monitoring how AI engines rank and interpret competitor content
- Content teams rewriting and optimizing articles to improve AI search placement
- SEO/AEO workflows that convert analytics into prioritized content actions
- Analytics-driven competitive research to inform content strategy
Thinking Orbs
Yogesh
Thinking Orbs is a lightweight React library of animated orb status indicators for AI interfaces such as thinking, searching and compacting.
Key features
- State-Based Orbs: An Orb component with states like reasoning, searching, working, retrying, compacting and waiting to mirror what the agent is doing.
- Zero Dependencies: The React orb needs nothing but React and the plain JS version needs nothing at all, at about 3.8 KB gzipped.
- Customizable Props: Control variant, size, speed, density, dot size, tilt, pause and screen-reader label to fit any interface.
- Opt-in Shapes and Renders: Import extra shapes like cube and renders like halftone separately so only used code is bundled.
- Flexible Installation: Install from npm, pnpm, yarn or bun, or copy the component into a project with shadcn.
- Tintable with CSS: Color orbs with text-* utility classes so they match the host UI theme.
- Interactive Playground: A web playground to preview all states, shapes and renders before integrating.
- llms.txt Support: Publishes an llms.txt so coding assistants can integrate the library correctly.
Best for
- Chat Interface Status: Show a thinking or reasoning animation while an LLM responds.
- Agent Progress Display: Indicate searching, working or background-task states in an agentic coding UI.
- Context Compaction Feedback: Visualize compacting states when conversation history is summarized.
- Retry and Waiting States: Signal retries or waiting-for-input states with distinct orb variants.
- Design System Components: Add a polished AI loading indicator to an in-house React component library.
- Prototype AI Products: Quickly drop a refined status animation into demos and prototypes.