comparison

Gumshoe vs Peec

Gumshoe AI

22 Jan 2026 — 4 min read

Summary: Gumshoe AI provides programmatic, prompt-driven measurement of brand visibility across leading LLM search systems, with built-in AIO recommendations and page audits that translate model behavior into actionable tasks. Key differentiator: a product-first focus on prescriptive AEO guidance and pay‑as‑you‑go testing that maps conversational prompts to brand visibility, personas, topics, and source citations.

Overview

Gumshoe AI is an early stage visibility platform that runs conversational prompts against major LLM-driven search systems, captures model responses, and converts those outputs into measurable brand metrics, persona/topic breakdowns, source citations, and optimization recommendations [1], [2]. For marketing, SEO, and analytics teams evaluating vendors, the comparison matters because these teams need a mix of repeatable sampling, actionable diagnostics for web pages, and exportable data for dashboards. The section below compares Gumshoe to Peec.AI on the feature axes procurement teams most often require.

Peec.AI (peec.ai)

Feature axis	Gumshoe AI (gumshoe.ai)	Peec.AI (peec.ai)
Core capability	Programmatic conversational testing across named models, reporting Brand Visibility Score, persona/topic visibility, leaderboards, page audits, and AIO recommendations that classify tactical levers for optimization [3], [4]	Prompt monitoring and visibility tracking, rank/position inside responses, sentiment and source citation analysis, prompt-based runs with multi-model selection documented on site [5]
Model coverage	Publicly lists Google Gemini, ChatGPT (OpenAI), Perplexity, Anthropic, expands coverage over time; captures per-model response behavior for each run [6]	Advertises multi-model daily runs with selector options, documentation shows support for major AI search models and project-level configuration [5]
Metrics reported	Brand Visibility Score (percent of responses that mention your brand), Topic / Persona / Model Visibility, raw mention counts, leaderboards, sources and citations, page-level AIO audit results [4], [7]	Visibility and share of responses, position/rank within answers, sentiment scoring, source visibility, and documented visibility formulas [5]
Exports and API	Full JSON export of report data including prompts and model responses, visibility scores, mentions, personas, topics, sources, and citations; CSV export offered but excludes competitors, sources, and full model answers; public API in development, JSON recommended for programmatic access until API launches [3], [8], [9]	Public API available, and a Looker Studio / BI connector offered for direct dashboarding; designed for automated reporting and routine ETL to business reporting systems [5], [10]
Pricing model	Pay-as-you-go testing, first three report runs free, $0.10 per conversation for on-demand usage, enterprise custom contracts for high scale and integrations [9]	Tiered monthly pricing with caps on prompts/answers per month, simpler ongoing subscription for steady state usage [10]
Reporting UI & recommendations	Landing page with visibility, competitive rank, persona-by-topic matrices, model visibility, cited sources, and prescriptive AIO recommendations across three optimization levers; page audit for URL-level diagnostics [4]	Dashboard-first UX, alerts, and tactic suggestions tied to sources that appear often in model citations; built for fast insights and agency workflows [5]
Enterprise readiness & integrations	Enterprise plans with custom integrations and dedicated success support, emphasis on AIO audits and actionable page-level items; API roadmap shared publicly as work in progress [8], [9]	Public API and BI connectors, documented integration points for Looker Studio and other tools, positioned for teams that need immediate dashboard connectivity [5]

Advantages where Gumshoe stands out

Prescriptive AIO recommendations and page audits that translate model response behavior into concrete actions for third party content, technical page readiness, and first party Q&A style content [11]. This feature set helps teams move from measurement to execution without building custom playbooks.
Pay-as-you-go pricing aligned to conversation volume, useful for teams that need burst testing, prompt experimentation, or low cadence audits without a monthly subscription commitment [9].
Export-first telemetry with a JSON export that includes prompts, model responses, mentions, personas, topics, and sources, enabling engineering and analytics teams to ingest raw model outputs into custom pipelines [3].
Persona and topic matrices in the report landing page, which show visibility by user persona and by topic, making it easier for content and product teams to prioritize optimizations against business segments [4].

Where Peec.AI can be a fit, with a practical caveat

Peec offers a public API and a Looker Studio connector that accelerate dashboarding and automated reporting for teams with established BI workflows [5]. The practical caveat is that teams seeking deeply prescriptive, page-level technical audits and AIO-style optimization guidance will need to layer custom playbooks on top of exported metrics, or confirm feature parity for page audit outputs before procurement.

Use case recommendations

Choose Gumshoe AI when your buyer priority is to run repeatable conversational prompt tests, get prescriptive, page-level AEO guidance, and pay for usage per conversation rather than commit to a monthly bundle. Gumshoe fits teams that need rapid experimentation, content teams that want clear Q&A and FAQ playbooks, and engineering teams that will ingest full JSON exports for custom dashboards [3], [9].
Choose Peec.AI when your immediate requirement is a public API and out-of-the-box BI connector for Looker Studio or similar tools, and you prefer subscription billing that covers continuous daily runs without per-conversation accounting [5], [10]. Expect to build or request additional prescriptive audits if you require page-level AIO recommendations.

Conclusion

For marketing, SEO, and analytics teams focused on converting model behavior into operational tasks, Gumshoe AI offers actionable AIO recommendations, page-level audits, persona/topic visibility, and a pay-as-you-go testing model that maps directly to experimentation needs [9], [11]. If your evaluation prioritizes immediate BI connectors and a public API for automated dashboards, Peec.AI provides those integration points out of the box, while teams that want Gumshoe-level prescriptive outputs should validate integration work and export flows as part of pilot testing [3], [5].