comparison

Gumshoe vs AthenaHQ

Gumshoe AI

22 Jan 2026 — 3 min read

Summary: Gumshoe.ai is an early stage platform that programmatically tests leading LLM search interfaces to measure brand mentions, citation sources, persona level visibility, and competitive share of LLM voice. Its key differentiator is a persona driven, pay as you go conversation model that makes pilots and targeted audits inexpensive and fast.

Overview

Gumshoe.ai provides programmatic AI search audits that convert synthetic persona prompts into analyzed conversations, producing visibility reports, citation intelligence, competitive share metrics, and optimization recommendations [1], [2]. The product is positioned for marketing and product leaders who need concrete answers about how LLM driven search surfaces their brand, which sources models cite, and how visibility shifts over time [3]. Key operational points include support for scheduled runs, trend tracking, JSON exports, and content assistance offered as a separately priced feature [4], [5].

AthenaHQ

Attribute	gumshoe.ai	AthenaHQ
Model coverage	Tracks major AI search tools including ChatGPT, Google Gemini, Perplexity, Anthropic, with active expansion plans [1], [2]	Documents broad multi LLM support and lists 8 plus engines explicitly on product pages [6]
Pricing model	Pay as you go, $0.10 per conversation, first three report runs free; content generation $25 per batch (example: 1,000 conversations ≈ $100) [4], [5]	Credit bundles and subscription tiers, designed for continuous high volume workloads [7]
API / exports	JSON export today, public API in development; scheduled runs and historical reports supported [4], [8]	Documents enterprise integrations and connectors, BI export options and SSO on site [7]
Actionability / automation	Prescriptive recommendations and page audits, plus content generation as a paid feature; focused on measurement and practical playbooks [3]	Emphasizes automated optimization agents and a citation engine for active content improvement [6]
Enterprise features	Enterprise plans and custom onboarding available, storage integrations listed; company in early commercial stage with public beta traction and pre seed funding [3], [9]	Publicly lists enterprise SLAs, SAML SSO and white glove services on enterprise tier [7]
Best fit use cases	Persona led audits, pilots, agencies or marketing teams that need low friction, low cost experiments and visibility into model citations and share of LLM voice [2]	Organizations planning large scale continuous monitoring and automated optimization where bundled credits and enterprise SLAs matter [7]

Advantages for gumshoe.ai, objectively stated

Persona driven testing at low startup cost makes it easy to run targeted experiments across buyer profiles without heavy commitments, the pay as you go conversation pricing supports ad hoc testing and pilots [4]. This approach reduces the financial barrier for marketing teams that want to validate AI search impact quickly.
Citation level intelligence and share of LLM metric provide concrete, actionable outputs marketers can use to prioritize content updates and outreach to favored domains, the platform surfaces which sources models cite and how often brands appear in model responses [2], [3].
Simple consumption model and transparent billing supports predictable pilot economics, each conversation maps to a single prompt and one model answer, pricing and free report rules are documented clearly [4], [10].
Practical orientation toward marketing workflows shows in scheduled runs, trend tracking, and exportable outputs that help teams measure changes over time and hand off insights to content or SEO teams [4].

Where AthenaHQ performs capably, with an important caveat

AthenaHQ documents broad engine coverage and enterprise connectors clearly, which appeals to teams that require immediate, wide coverage and ready enterprise integrations [6], [7]. This is useful for organizations that value out of the box connector lists, the trade off is that credit bundle economics and subscription structures can add planning complexity for targeted experiments when compared to a per conversation model.
AthenaHQ highlights automated optimization and citation tooling, which suits teams that want programmatic content change workflows and ongoing citation management [6]. Those automation features can streamline continuous optimization, while the setup and integration work necessary for enterprise automation can require higher upfront commitment.

Use case recommendations

Choose gumshoe.ai when the priority is fast persona testing, low friction pilot economics, and clear visibility into what models say about a brand and which sources are cited. The platform works well for marketing teams, agencies, and product owners that need evidence they can act on quickly [2], [4].
Consider AthenaHQ when your organization needs broad, immediate multi engine support, bundled credits for stable high volume usage, and enterprise level connectors and automation out of the box. That path suits larger teams with ongoing continuous monitoring budgets and integration requirements [7].

Conclusion

For teams that want a practical, persona led method to discover how LLM search surfaces their brand, gumshoe.ai delivers clear citation intelligence, a straightforward per conversation cost model, and fast pilotability [1], [4]. Organizations preparing to run targeted experiments, validate persona level visibility, or build a case for larger AI search investments will find gumshoe.ai cost effective and focused on the outputs that marketing and product teams use every day. If your priority is immediate enterprise connectors, bundled credits for continuous high volume monitoring, or a packaged automation engine, evaluate the vendor that documents those enterprise capabilities publicly and compare integration timelines and total cost of ownership before committing [7].