BotScope
Summary
Your brand has a Wikipedia problem you can't see — the models answering your customers' questions have formed opinions about you, and you have no idea what those opinions are or where they're wrong.
BotScope runs a daily query battery against ChatGPT, Claude, Gemini, Google AI Overviews, Microsoft Copilot, and Perplexity, then grades the responses across four layers: whether the model knows your brand exists, how deep that knowledge goes, whether you surface in recommendation queries, and which of your URLs get cited. The four-layer scoring structure gives teams a specific place to push — a citation gap on L4 is a different fix than an L1 recognition failure. The tool is a passive monitoring SaaS with no self-hosting option, so your data lives on their infrastructure. The API and hosted MCP server let you pull visibility scores into your own stack or pipe them into a Claude session directly.
Bottom line: Pick this when your marketing team needs to audit and track AI-generated brand perception across six major models without building the query infrastructure themselves — skip it if you need on-premise data residency or want to run your own prompt design from scratch without a managed layer.
Pricing Plans
Usage-BasedTrial
14-day trial with 200 credits/month, 1 seat, ChatGPT + Google AI Overview, 14-day history
- 200 credits/month
- 1 seat
- 2 model providers
- 14-day history
Starter
1,000 credits/month, unlimited brands, 3 seats, all 5 providers, daily scans, 90-day history, one-off reports, branded PDF, REST API + MCP (read)
- 1,000 credits/month
- Unlimited brands
- 3 seats
- All 5 providers
- 90-day history
Pro
5,000 credits/month, unlimited brands, 10 seats, all 5 providers, daily scans, 1-year history, public reports, sentiment analysis, REST API + MCP (read)
- 5,000 credits/month
- 10 seats
- 1-year history
- Sentiment analysis
Scale
20,000 credits/month, unlimited brands, 25 seats, everything in Pro plus white-label reports, unbranded PDF, REST API + MCP (read & write), priority support
- 20,000 credits/month
- 25 seats
- White-label reports
Agency
75,000 credits/month, unlimited brands, 50 seats, everything in Scale plus volume pricing, quarterly reviews
- 75,000 credits/month
- 50 seats
- Volume pricing
Enterprise
Custom credits, unlimited brands and seats, everything in Agency plus SSO, audit logs, dedicated infrastructure, SLA support
- Custom credits
- SSO + audit logs
- Dedicated infrastructure
View full pricing on botscope.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Daily automated scans across six major AI models, so your team catches a brand representation shift within 24 hours instead of finding out from a customer complaint three weeks later.
- Four-layer scoring that separates entity recognition from citation behavior, which means you know whether to fix your content's discoverability or your brand's factual representation in the models — not just that something is wrong.
- Annotation pinning on visibility charts, so agencies can show clients that a score drop coincided with a model update rather than losing the account over a number that moved without explanation.
- Shareable report links and PDF exports, which means client-facing deliverables don't require your clients to log into another tool or hold a seat.
- REST API and MCP server access, so teams that already have dashboards can pull BotScope scores in without rebuilding their reporting workflow around a new interface.
Cons
Sign in to edit- The query watchlist runs on BotScope's infrastructure with no self-hosting option — teams operating under strict data residency requirements cannot route competitor and brand query results through a third-party SaaS, and that architectural wall does not have a workaround short of building the monitoring in-house.
- The starter query set is auto-generated and editable, but the platform's structure is designed around BotScope's four-layer taxonomy — teams that need to run highly specific or proprietary prompt designs as their primary methodology will find themselves maintaining their own query logic outside the tool while paying for the monitoring layer, which doubles the operational surface.
- The free scan covers only ChatGPT and Google AI Overviews for a one-time report — teams that need to evaluate the tool's signal quality across Claude, Copilot, and Perplexity before committing have to move to a paid tier to test the full model coverage, which compresses the evaluation window.
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About
- Platforms
- Web
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-07-01T08:01:14.093Z
Best For
Who it's for
- Brand and marketing teams
- Agencies managing multiple clients
- SEO and reputation professionals
- Companies tracking AI search results
What it does well
- Track brand perception in AI responses
- Monitor competitors across AI knowledge layers
- Generate reports on AI visibility trends
- Analyze sentiment in model outputs
- Share public AI perception links
Integrations
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Frequently Asked Questions
- Is BotScope free?
- BotScope is a paid tool. A 14-day free trial is available.
- Is BotScope open source?
- No — BotScope is a closed-source tool. Source code is not publicly available.
- Does BotScope have an API?
- Yes. BotScope exposes a developer API. See the official documentation at https://botscope.ai for details.
- What platforms does BotScope support?
- BotScope is available on: Web.
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Curated lists that include this category
Most brands discover AI has been misrepresenting them when a customer mentions it. BotScope is a monitoring SaaS that runs a structured daily watchlist of queries against six AI models — ChatGPT, Claude, Gemini, Google AI Overviews, Microsoft Copilot, and Perplexity — and grades the responses across four scored layers. Layer 1 checks whether a model can identify your brand unprompted. Layer 2 probes how accurately it describes your products, people, and positioning. Layer 3 tests whether you surface when users ask for category recommendations. Layer 4 traces which of your URLs the models actually cite. The workflow is configure, scan, read, fix: you define your brand and competitor watchlist, BotScope generates a starter query set you can edit or replace, and the platform delivers daily scored readouts with timestamped deltas.
The four-layer methodology is the differentiating structural choice here. A single aggregate AI visibility score obscures where the gap actually lives — a brand that AI knows but never recommends has a different content problem than one AI has never indexed. BotScope’s scoring separates those failure modes so teams have a specific layer to address rather than a single opaque number to stare at.
The annotation feature — which pins notes about content changes, prompt edits, or model updates to specific dates on your visibility charts — is the capability that makes this viable for agency work. When a client’s L3 score drops, you can show them that it coincides with a model update, not a content regression. Without that context, score movement is noise. The vendor also describes shareable public report links, which gives agencies a client-facing artifact without requiring a seat.
The read-only REST API and hosted MCP server let teams pull visibility scores into dashboards or query them via Claude directly. The API is a paid-only feature — the free scan tier generates a one-time report for two models with no persistent tracking. Teams that need multi-client monitoring at scale, or want to build custom query sets outside BotScope’s interface, will hit the limits of the managed layer and face a choice between adapting to the platform’s query structure or building alongside it.
