Digraph vs Foglift pricing
| Plan detail | Digraph | Foglift |
|---|---|---|
| Lowest published price | Free for 14 days, then $99/mo | From $49/mo |
| Plan and billing | Standard, billed monthly | AI Visibility monitoring |
| Allowance | 30 prompts, 1 brand | Confirm limits |
| AI coverage | Supported AI models | 5 AI surfaces |
| Next plan | Pro $249/mo: 300 prompts, 3 brands | See Foglift’s pricing page |
Lowest published plan for each vendor; billing terms differ. See which AI systems Digraph checks and how.
Features compared
| Capability | Digraph | Foglift |
|---|---|---|
| Published entry pricing | Standard: $99/month for 30 tracked prompts and 1 brand. | Foglift describes a free Technical Audit and paid AI Visibility monitoring from $49/month; confirm current plan limits and billing terms. |
| AI-system coverage | Standard and Pro list supported AI models. | Paid plans describe ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews; the free plan describes weekly Perplexity monitoring and on-demand checks. |
| Prompt and answer evidence | Inspect full answers, recommendations, competitor mentions, cited URLs, source domains, and changes over time. | Foglift describes prompt-level results, brand mentions, cited sources, sentiment, competitors, and dated history; confirm answer retention and export fields in the selected plan. |
| Technical and AI-readiness audits | Route visibility gaps into AI Audit, Marketing & Technical Analysis, Signal, and agent workflows. | Foglift describes Technical Audits across SEO, AI Readiness, performance, security, and accessibility, with prioritized recommendations. |
| Developer access | Reports and exports are public-plan capabilities; API access is listed for Enterprise. | Foglift describes REST API, CLI, MCP, webhooks, npm packages, and GitHub Action access on paid plans; verify availability and limits by tier. |
| Agency and action workflow | Compare competitors and connect answer evidence to focused content, source, technical, and research work. | Foglift describes white-label PDF reports, client portal, batch scans, content briefs, and recommendations for agency workflows. |
Key differences between Digraph and Foglift
Foglift and Digraph both measure how AI systems mention, recommend, cite, and compare brands. Foglift combines free Technical Audits and AI Readiness checks with paid monitoring across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews, and highlights API, CLI, MCP, content briefs, and recommendations. Digraph emphasizes a defined prompt portfolio, full answer evidence, cited URLs, source domains, competitor context, and connected audit or analysis workflows across supported model APIs. Compare the evidence and operating model, not only the entry price.
Free audit entry versus prompt-centered monitoring
Foglift’s free Technical Audit is designed as a low-friction readiness and visibility check before paid monitoring. Digraph’s public plans begin with tracked prompts, brands, answer evidence, and cross-engine monitoring. A fair evaluation should run the same buyer questions through both products, then separately compare the technical findings and the action workflow.
Normalize engine coverage and measurement units
Foglift describes five paid monitoring engines and weekly free-plan Perplexity coverage. Digraph lists supported AI models on Standard and Pro. Record the exact models or surfaces, prompt count, geography, language, cadence, answer history, and source fields; engine counts are not interchangeable without checking modes and sampling.
Compare the evidence behind a visibility gap
Both products describe mentions, citations, competitors, and recommendations. Use one prompt where a competitor appears and Digraph is absent. Check whether each tool exposes the full response, cited URL, source domain, competitor framing, sentiment, and a clear next action. Do not compare aggregate scores without their denominators and collection conditions.
Developer and agency workflows are meaningful differences
Foglift publicly describes API, CLI, MCP, webhooks, GitHub Action, white-label reports, client portals, and batch scans. Digraph emphasizes an evidence-connected workspace with reports, exports, audits, analysis, Signal, and agents, while API access is listed for Enterprise. Test permissions, export shape, automation limits, client separation, and the effort to re-check a published change.
Run a controlled side-by-side pilot
Use the same brand, competitors, categories, markets, language, buyer questions, active engines, collection window, and reporting format. Record full answers, prompt and model context, brand position, competitor mentions, sentiment, cited URLs, source domains, proposed actions, refresh time, and resource consumed. Compare one recurring report and one verified follow-up action before choosing the operating model.
Need the work done, not another tool?
A tracking tool tells you where you stand in AI answers; it does not write the content, fix the site or earn the mentions that change them. Digraph is an AI marketing agency: we measure on our own platform and do that work for you, starting with a one-off audit.
See our AEO agency servicesHow to evaluate both
This documentation-based comparison was reviewed September 21, 2026; it is not a hands-on benchmark. Foglift publicly describes free Technical Audits, paid five-engine AI Visibility monitoring, prompt-level results, cited pages, competitor trends, recommendations, API, CLI, and MCP access, with monitoring from $49/month. Digraph lists Standard at $99/month for 30 prompts and 1 brand and Pro at $249/month for 300 prompts and 3 brands across supported model APIs. Their measurement units, free entry points, engine coverage, and developer workflows differ. Compare the same prompts, engines, source evidence, competitors, cadence, and export requirements before choosing.
Sources reviewed
Foglift’s capabilities are summarized from the official sources below. This is a documentation-based comparison published by Digraph, not a hands-on benchmark.
Common questions
How does Digraph compare with Foglift?
Foglift and Digraph both measure how AI systems mention, recommend, cite, and compare brands. Foglift combines free Technical Audits and AI Readiness checks with paid monitoring across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews, and highlights API, CLI, MCP, content briefs, and recommendations. Digraph emphasizes a defined prompt portfolio, full answer evidence, cited URLs, source domains, competitor context, and connected audit or analysis workflows across supported model APIs. Compare the evidence and operating model, not only the entry price.
How does Foglift pricing compare with Digraph?
Foglift’s lowest published plan is From $49/mo (AI Visibility monitoring) with confirm limits and 5 AI surfaces. Digraph starts with a 14-day free trial; Standard is then $99/mo billed monthly for 30 prompts, 1 brand across supported model APIs, and Pro is $249/mo for 300 prompts, 3 brands. Billing basis, collection surfaces, and plan units differ, so confirm current terms with both vendors.
Is Digraph a good Foglift alternative?
Digraph is a fit for teams choosing between a free technical-readiness entry point with developer surfaces and a prompt-centered cross-engine evidence and investigation workflow. Run the same buyer prompts in both products and compare the full answers, citations, and next actions before deciding.
Can Digraph complement an existing Foglift workflow?
Yes. Many teams use more than one research or measurement system. Digraph adds an evidence-led view of AI answers, prompts, citations, competitors, and follow-up work alongside the tools SEO, brand, and content teams already use.
How should I run a fair AI visibility evaluation?
Use the same prompt portfolio, competitors, markets, AI systems, and reporting period in each tool. Review the underlying answers and sources, not only aggregate scores, before choosing a workflow.