Radarkit vs Riff Analytics in 2026: Four engines with API access versus seven engines with no API
Cheapest API-enabled monitoring, or wider mid-market coverage without programmatic data delivery?
Radarkit includes API access on every paid tier from $29/month. Riff Analytics does not offer API access on any plan. For teams that need programmatic data delivery on a budget, Radarkit is the only answer in this AI visibility tool comparison.
Riff Analytics tracks 7 AI engines: ChatGPT, Perplexity, Claude, Gemini, Grok, DeepSeek, and Llama. Radarkit tracks 4: ChatGPT, Claude, Gemini, and Perplexity. For wider engine coverage, Riff Analytics wins.
Radarkit Lite at $29/month is cheaper than Riff Analytics Starter at $49/month, but Riff Analytics includes broader engine coverage and an AI readiness audit. The deciding factor is API access versus engine count.
Riff Analytics includes citation source tracking and an AI readiness audit on every tier. Radarkit includes citation source identification on Growth ($79/month) and above. Both tools surface which URLs AI models cite.
Neither tool offers crawler log access, AEO content generation, or white-label delivery. Both are monitoring and reporting tools without agency delivery features.
Radarkit is fully self-serve with no sales call. Riff Analytics is self-serve with no sales call required. Both are accessible without procurement friction.
For Generative Engine Optimization (GEO) workflows that need API access on the cheapest plan, Radarkit wins. For GEO workflows that need wider mid-market coverage with citation tracking and an AI readiness audit, Riff Analytics is the right choice.
If you are weighing Radarkit against Riff Analytics, you are really choosing between two different AI visibility tool comparison philosophies. Radarkit tracks 4 engines (ChatGPT, Claude, Gemini, Perplexity) with API access on every paid tier from $29/month, but stops short of wider engine coverage and white-label delivery. Riff Analytics tracks 7 engines (ChatGPT, Perplexity, Claude, Gemini, Grok, DeepSeek, Llama) at $49/month Starter with citation source tracking and an AI readiness audit, but offers no API on any plan and no white-label delivery. The right pick depends on whether API access on a budget plan or wider mid-market coverage with citation tracking matters more to your workflow.
The tools at a glance
Radarkit
AI brand monitoring across ChatGPT, Claude, Gemini, and Perplexity with API access
Radarkit monitors brand mentions and citations across 4 AI engines: ChatGPT, Claude, Gemini, and Perplexity. The platform tracks how often your brand appears in AI-generated answers, which sources the AI models cite, and how your visibility compares to competitors over time. The 4-platform scope is the defining feature: teams that prioritise Claude and Gemini coverage alongside the two biggest first-party AI search engines often shortlist Radarkit.
Where Radarkit stands out is on price and API access. The Lite plan at $29/month is the lowest paid entry point in the AI visibility category for a tool that includes API access across all four paid tiers. The Growth tier at $79/month unlocks competitor benchmarking and citation source analysis, and the Pro tier at $139/month adds unlimited historical data. For developers and analysts building custom reporting stacks, this combination is the deciding factor in this AI visibility tool comparison.
The gaps to plan around are scope and delivery. Radarkit does not currently track Google AI Overviews or Google AI Mode, which matters for SEO teams whose audiences are asking questions in Google search. There is no white-label delivery or branded client view on any tier, so agencies delivering AI visibility reports to clients would need a separate reporting layer. For internal Generative Engine Optimization (GEO) tracking on a tight budget, Radarkit is a credible option.
| Feature | Lite $29/mo | Growth $79/mo | Pro $139/mo | Enterprise Contact |
|---|---|---|---|---|
| AI models tracked | 4 | 4 | 4 | 4 |
| API access | ✓ | ✓ | ✓ | ✓ |
| Competitor benchmarking | ✗ | ✓ | ✓ | ✓ |
| Citation source analysis | ✗ | ✓ | ✓ | ✓ |
| Historical trend data | 30 days | 90 days | Unlimited | Unlimited |
| White label | ✗ | ✗ | ✗ | ✗ |
Riff Analytics
AI brand visibility tracking across 7 LLM engines with citation source analysis, sentiment monitoring, and competitor benchmarking
Riff Analytics monitors brand mentions across a wider set of AI engines than most competitors, including Grok, DeepSeek, and Llama on top of the main 4. The platform monitors not just whether your brand appears in AI answers, but which sources those AI engines are citing when they mention you, which informs where to invest in content and PR to improve AI visibility over time.
The citation source tracking tells you whether AI models are pulling from your blog, your Wikipedia page, review sites like G2 or Capterra, or competitor-adjacent content. Understanding the citation pattern is the starting point for an AEO content strategy, because it reveals which content types and domains carry the most weight with each AI engine. The competitor benchmarking and AI readiness audit round out the workflow.
The platform is positioned as a self-serve in-house tool. There is no API on any plan, no white-label delivery, and no client portal, so it is not designed for agencies managing multiple brands. The Starter plan at $49/month is accessible for small teams, though the jump to $199/month Pro is steep for what is publicly documented as the next tier. For internal Generative Engine Optimization (GEO) tracking with broader engine coverage and no API requirements, Riff Analytics is functional.
| Feature | Starter $49/mo | Pro $199/mo |
|---|---|---|
| AI models tracked | 7 | 7 |
| Citation source tracking | ✓ | ✓ |
| Competitor benchmarking | ✓ | ✓ |
| AI readiness audit | ✓ | ✓ |
| API access | ✗ | ✗ |
| White-label delivery | ✗ | ✗ |
| Looker Studio connector | ✗ | ✗ |
Head-to-head feature comparison
| Feature | ||
|---|---|---|
| AI engines tracked | ChatGPT, Claude, Gemini, Perplexity | ChatGPT, Perplexity, Claude, Gemini, Grok, DeepSeek, Llama |
| Competitive share-of-voice | Yes (Growth and up) | Yes |
| Prompt-level citation data | Yes | Yes |
| Answer / content gap analysis | No | Yes (AI readiness audit) |
| Category intelligence | No | No |
| AEO content generation | No | No |
| Crawler / AI bot log access | No | No |
| Page content audits | No | No |
| API access | Yes, all paid plans | No |
| Looker Studio / BI connector | No | No |
| White-label delivery | No | No |
| Pay-per-prompt pricing | No | No |
| Agency multi-brand support | No | No |
| Starting price | $29/mo | $49/mo |
Need white-label AI visibility reports alongside Radarkit and Riff Analytics?

Neither Radarkit nor Riff Analytics includes white-label delivery on any tier, and Riff Analytics has no API access on any plan. AI Peekaboo is the best AI visibility tool for agencies with white-label client reports, guest access links, and read and write API on every plan from $50/month Starter. For SEO and marketing agencies managing multiple client brands, AI Peekaboo adds a Looker Studio connector and multi-brand support that both tools leave out of standard pricing.
Read the AI Peekaboo review →Which should you choose?
Radarkit and Riff Analytics serve different audiences at similar price points. Radarkit wins on API access at the entry tier and lowest price; Riff Analytics wins on engine count and an AI readiness audit. The trade-off is API access and price versus wider mid-market coverage with audit features.
Bottom line
Radarkit answers how a developer or analyst can pull AI visibility data into a custom reporting stack at $29/month with API access on every paid tier. Riff Analytics answers how an in-house brand manager can monitor 7 AI engines with citation source tracking and an AI readiness audit at $49/month. If API access on a budget plan is the deciding factor, Radarkit. If broader mid-market coverage with an audit is the deciding factor, Riff Analytics.
Frequently asked questions
How does Radarkit compare to Riff Analytics on API access?
Radarkit includes API access on every paid tier from $29/month. Riff Analytics does not offer API access on any plan. For teams that need programmatic data delivery on a budget plan, Radarkit is the practical answer in this AI visibility tool comparison.
Which tool tracks more AI engines, Radarkit or Riff Analytics?
Riff Analytics tracks 7 AI engines: ChatGPT, Perplexity, Claude, Gemini, Grok, DeepSeek, and Llama. Radarkit tracks 4: ChatGPT, Claude, Gemini, and Perplexity. For wider engine coverage, Riff Analytics wins.
Is Riff Analytics worth the cost compared to Radarkit for in-house teams?
For in-house teams that want broader engine coverage with citation source tracking and an AI readiness audit, Riff Analytics is worth the cost at $49/month. Radarkit at $29/month delivers API access and the 4 core engines. The deciding factor is whether API access on Radarkit or engine breadth on Riff Analytics matters more.
Which is best for Generative Engine Optimization (GEO) workflows, Radarkit or Riff Analytics?
For GEO workflows that need API access on the cheapest plan, Radarkit is the right choice. For GEO workflows that prioritise wider engine coverage, citation source tracking, and an AI readiness audit, Riff Analytics is the right choice. Neither tool offers crawler log access or white-label delivery.
How much does Radarkit cost compared to Riff Analytics?
Radarkit Lite is $29/month with API access; Growth is $79/month adding competitor benchmarking and citation source analysis; Pro is $139/month with unlimited historical data; Enterprise is contact-based. Riff Analytics Starter is $49/month with the full 7-engine list; Pro is $199/month. Radarkit is cheaper at entry; Riff Analytics delivers wider engine coverage on Starter.
Can I use Radarkit or Riff Analytics for agency client reporting?
Neither tool is designed for agency multi-client workflows. Neither offers white-label delivery, guest client access, or an API on Riff Analytics. For agencies delivering AI visibility reports to clients, look at platforms built around agency workflows.

