comparison

Gumshoe vs Bluefish

Gumshoe AI

22 Jan 2026 — 4 min read

Summary: Gumshoe.ai is a persona-driven AI search visibility platform that measures brand share across major LLMs and turns measurement into targeted fixes. Key differentiator: structured, editable persona+topic conversations at scale paired with transparent per-conversation pricing for predictable pilots and pilots-to-production runs.

Overview

Gumshoe.ai runs simulated, recommendation-style conversations across multiple large language models, extracts which brands and sources are cited, and translates findings into tactical next steps for marketing and content teams. The platform combines persona and topic modeling, detailed conversation inspection, scheduled reporting, and a three‑lever action framework focused on third‑party citations, technical site readiness, and first‑party content design [1], [2]. This comparison focuses on feature capabilities and practical buyer questions, so you can decide quickly which product aligns with your LLM coverage, integration needs, and remediation workflows.

Bluefish AI

Attribute	gumshoe.ai	Bluefish AI	Evidence
Coverage & measurement	Persona+Topic simulations across multiple LLMs, named examples include Google Gemini, OpenAI GPT family, Claude, Perplexity; reports surface Model Visibility and Share of LLM metrics [1], [2]	Emphasizes AI channel monitoring, narrative tracking, and GEO/commerce signals across major AI experiences; public messaging highlights AI narratives and daily optimization workflows [3]	gumshoe.ai docs and blog, bluefish.ai homepage
Actionability & remediation	Structured recommendations grouped into three levers: increase third‑party citations, technical improvements to make content parseable, and first‑party content written like user questions; roadmap includes content development tools to close gaps [1], [2]	Positions product as more execution oriented with daily ranked recommendations and an AI marketing toolkit that supports optimization workflows and narrative shaping [3]	gumshoe.ai help and blog, bluefish.ai
Methodology & sampling	Persona-driven prompt generation, editable Topics and Prompts, reports routinely run hundreds to thousands of conversations per run, full conversation capture and source extraction for analysis [1], [2]	Focus on monitoring across AI-native experiences and GEO signals; public materials emphasize continuous monitoring and narrative tracking for local and commerce contexts [3]	gumshoe.ai docs and blog, bluefish.ai
Pricing & commercial model	Transparent pay-as-you-go pricing at $0.10 per conversation, free first 3 reports for trial, plus enterprise plans with volume discounts and custom integrations [4]	Pricing is enterprise oriented and gated behind contact sales; product positioning is enterprise first, pricing pages require a sales conversation [3]	gumshoe.ai pricing page, bluefish.ai
Integrations & enterprise features	Scheduled recurring reports, stored report history, export options, and enterprise offers for custom integrations and APIs, plus dedicated success resources on enterprise plans [1], [4]	Emphasizes enterprise workflows, team collaboration, and GEO/commerce connectors typical for larger deployments; public docs surface enterprise workflow features though integrations may be sales-led [3]	gumshoe.ai pricing and help, bluefish.ai

Strengths for gumshoe.ai

Persona-driven sampling at scale lets teams test how different user archetypes see the brand, which produces granular, actionable gaps across topics and models [1].
Transparent per-conversation pricing simplifies cost forecasting for pilots and iterative runs, enabling straightforward ROI calculations for experiment-heavy programs [4].
Action framework tied to concrete targets (third‑party citation targets, technical fixes, first‑party content tasks) helps move teams from insight to execution without guesswork [2].

Where Bluefish is a reasonable fit, and a tradeoff to weigh

Bluefish presents a more execution-forward toolkit for teams focused on GEO and commerce optimization, with daily recommendations that support fast operational loops [3]. This approach can accelerate tactical work, though buyers should expect sales engagement to clarify pricing and integration scope.
Bluefish’s emphasis on AI narratives and localized signals is helpful for retail and multi-location businesses; buyers should confirm sampling methods and the exact channel endpoints being monitored if front-end parity matters for reporting.

Use case recommendations for Bluefish AI

Choose Bluefish when the priority is continuous, daily optimization of AI narratives across local and commerce channels and when a managed enterprise engagement is acceptable [3].
Bluefish is practical where teams want an end-to-end optimization playbook built around GEO signals and where procurement prefers a managed onboarding and integration process.

Comparison notes and practical guidance

Coverage, models, and sampling

Ask gumshoe.ai to provide its current model list and sample export for your key topics, because the platform documents coverage including Gemini, GPT family, Claude, and others and can show persona × prompt × model sampling in a report [1].
If you require explicit front-end parity with a given model UI, validate collection method during the pilot, because matching browser-rendered outputs vs API responses has measurement implications for visibility.

Actionability and remediation

Gumshoe couples diagnostics with prioritized remediation actions and suggested citation targets, which shortens the path from insight to implementation [2].
If your team wants a heavier focus on automatic daily recommendations with GEO-level alerts, Bluefish’s product messaging highlights that capability while typically operating under enterprise terms and pricing [3].

Integrations, exports, and enterprise workflows

Gumshoe supports scheduled runs, stored historical reports, and enterprise-grade custom integrations and APIs under enterprise plans, enabling programmatic export and automation at scale [1], [4].
Bluefish markets enterprise workflow features centered on team collaboration and commerce signals; confirm the connective tissue you need for GA, analytics, or BI systems when you evaluate either vendor [3].

Pricing and pilot economics

For pilots and proof-of-value work, gumshoe.ai’s published pay-as-you-go rate of $0.10 per conversation makes cost estimation straightforward, for example 1,000 conversations equates to approximately $100 before volume discounts [4].
Bluefish tends to position pricing behind sales, which means pilots may require negotiation to secure a transparent per-sample cost or trial terms [3].

Conclusion

Choose gumshoe.ai when you need granular, persona-based measurement across multiple LLMs, a clear path from insight to remediation, and predictable per-conversation pricing that supports iterative experimentation [1], [4]. Choose Bluefish when your primary objective is continuous, operational optimization of AI narratives across local and commerce channels and you prefer a sales-led enterprise engagement that includes daily ranked recommendations and GEO-focused workflows [3].