LLM Optimizer
** - AI brand visibility tool (like SEO for LLMs, or GEO). Measures how ChatGPT, Claude, Gemini, and Perplexity cite and recommend your brand with composite AI Visibility Scores, per-dimension analysis, and prioritized optimization recommendations.
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What is LLM Optimizer?
LLM Optimizer (LLMOpt) is an AI visibility intelligence platform that analyzes how large language models and AI search engines discover, cite, and recommend brands and domains. The tool evaluates a domain’s presence across multiple AI sources (LLMs, AI search engines, social platforms, and video) and produces visibility scores, diagnostics, and prioritized recommendations to improve how an organization is represented in AI outputs. Key features include domain-level visibility scoring, per-entity breakdowns, channel-specific authority metrics (search, Reddit, video, LLMs), and an API for programmatic access and integration. The product is aimed at marketers, SEO and content teams, brand managers, and product owners who need to measure and improve their brand’s discoverability within modern AI-driven answer systems and to prioritize content or PR actions that increase citation and representation by LLMs. It can be used both as a hosted SaaS and via self-hosting or API-driven workflows for teams that want deeper automation or integration with analytics stacks.
LLM Optimizer pricing
Pricing model: Freemium
The website offers a hosted version and an option to self-host; there is a free tier or free-to-install open-source option for developers and early evaluation, while sustained hosted usage and higher-volume API access are available under paid subscription plans. Paid plans include expanded domain queries, higher-rate API access, and support for private API key integration for connectors and automation. Exact plan names, limits, and monthly pricing are provided on the site’s pricing page or during sign-up.
LLM Optimizer pros
- Domain-level AI visibility scoring across multiple LLMs and AI search engines
- Channel-specific authority metrics for search, Reddit, and video
- Per-entity diagnostics that highlight which brand mentions drive visibility
- Prioritized recommendations to improve LLM citations and representation
- Programmatic REST API for integrating visibility data into workflows
- Hosted SaaS option for quick setup alongside self-hosting possibilities
- Supports analysis of transcripts and video content for AI discoverability
- Aggregates signals from traditional search and AI-specific sources
- Able to surface differences between Google search and LLM citation coverage
- Open-source components and an MIT-licensed repo for self-hosting
- Lightweight site tooling (llms.txt helpers) to summarize docs for LLMs
- Tracks freshness and recency signals that affect AI citations
- Provides measurable visibility KPIs marketers can report on
- Designed specifically for modern AI/LLM discovery use cases rather than generic SEO
- Can analyze third-party mentions and earned media impact on AI outputs
- Reddit authority measurement tailored to how LLMs source social citations
LLM Optimizer cons
- Relies on available crawled/indexed data which may lag behind real-time LLM behavior
- Hosted features require a subscription for sustained usage
- Self-hosting and API use need developer setup and API keys
- May not cover every LLM or proprietary model out of the box
- Visibility scores can be sensitive to query selection and sampling choices
- Actionable recommendations sometimes require cross-team execution (PR, engineering, content)
- Smaller brands with low web presence may get sparse diagnostics
- Some advanced diagnostics require programmatic access or paid plan
Frequently asked questions about LLM Optimizer
What does LLM Optimizer measure for my domain?
LLM Optimizer measures domain-level visibility across multiple AI sources by computing visibility scores and channel authority (search, Reddit, video, and LLM outputs). It aggregates citations and mentions, breaks down which entities and pages drive visibility, and surfaces gaps and prioritized actions to improve representation in AI answers and recommendations.
Can I access LLM Optimizer data programmatically?
Yes — LLM Optimizer provides a REST API that exposes domain analysis, visibility scores, search visibility, Reddit authority, video authority, and other metrics so teams can integrate results into dashboards, automation, or reporting pipelines.
Is there a free tier or open-source option?
There is a free/open-source option for developers and evaluators: components of the project are available under an MIT license for self-hosting or local evaluation, while the hosted SaaS offers free-tier access with limited queries and paid tiers for higher-volume use.
Which AI models and sources are analyzed?
The platform focuses on major AI search engines and LLM-driven answer sources alongside traditional search, Reddit, and video signals; coverage varies over time and some proprietary models may not be fully supported without additional connectors or API access.
How does LLM Optimizer handle video and transcripts?
LLM Optimizer analyzes video transcripts and associated metadata to assess video authority and extract quoteable or indexable passages that increase a brand’s chance of being cited by LLMs, and includes those signals in its visibility scoring.
Can I self-host LLM Optimizer for privacy or customization?
Yes — parts of the project are available for self-hosting under permissive licensing, allowing teams to run analyses in their own environment and use private API keys or custom connectors as needed.
How should I act on the recommendations?
Recommendations typically focus on increasing consistent third-party mentions, adding quotable facts and transcripts, improving documentation discoverability, and targeted PR or content placements; execution often requires coordination across content, SEO, and PR teams to change external signals that LLMs use.
How up-to-date is the visibility data?
Data freshness depends on the platform’s crawlers and integrated sources; the tool emphasizes recency as a factor but exact update cadence varies by source and plan level, with paid tiers offering more frequent or higher-volume updates.
Will LLM Optimizer improve my rankings in traditional search?
LLM Optimizer is focused on AI discoverability and LLM citation signals rather than directly changing traditional search rankings, though many signals (third-party mentions, transcripts, structured content) can positively impact both AI visibility and conventional SEO.
What support and onboarding are available?
Hosted subscribers receive documentation, API docs, and onboarding guidance; self-hosting users can rely on the open-source repo and docs, while higher-tier plans or paid subscriptions include additional support options and implementation help.