Research checked 2 October 2026. This compares documented offers and an illustrative agency workload; it does not claim a hands-on vendor benchmark.
An agency buying AI-visibility software needs to deliver a report that a client can challenge. The client should be able to open the underlying answer, understand why a source was counted and see who will carry out the next correction.
Peec AI and OtterlyAI both deserve consideration for that workflow. The useful differences include capacity allocation, additional engines, client reporting and access to evidence. The subscription price is only part of the agency’s delivery cost. Analysts still need to select relevant questions, inspect uncertain results and turn findings into work someone owns.
This comparison uses a three-client example to make those differences concrete. Beacon by EVAA offers its own SaaS monitoring and separately scoped catalogue-grounded implementation; compare each actual delivery scope independently.
Start with a client service you can describe
Before selecting a tool, decide what the retainer includes. “AI visibility management” could mean several different services:
| Service | What the client should receive | Work the agency must account for |
|---|---|---|
| Monitoring | A fixed question panel, documented conditions, trends and access to answer evidence | Panel maintenance, result review and handling unavailable data |
| Research | Relevant topics, competitors, source pages and a reason for each proposed action | Reading the sources and testing whether the opportunity fits the business |
| Content or product-fact correction | An approved change with an owner and a record of what was changed | Product expertise, source confirmation, drafting and implementation |
| Catalogue-grounded assistant implementation | A working scoped experience, data connection, failure cases and handover | Engineering, permissions, acceptance testing and maintenance |
A monitoring subscription may support several of these tasks, but the agency’s proposal should name the actual deliverables. If the agency only provides recommendations, say who will execute them. If it provides implementation, make the acceptance test part of the scope.
That service definition also makes the software comparison fair. A client-reporting requirement and a catalogue integration requirement should not be collapsed into a single “best GEO tool” score.
Peec AI’s agency model centres on allocated capacity
Peec’s agency pricing explains credits as capacity allocated to projects. Its documented formula is one prompt, one model and one day per credit, with a 30-day example for monthly capacity. Allocations persist until changed; they are not a pot that resets each month. The page specifies a 900-credit minimum per project and permits reallocating capacity by changing prompts or models. Peec’s agency pricing and credit definitions
This makes the model worth examining when an agency’s clients need different amounts of monitoring. A small local client may need a tight panel. A multi-product client may need more questions or more surfaces. The allocation should reflect the service the agency actually sells to each client.
Peec’s agency page describes separate client projects, team access, agency-branded reporting through Looker Studio and CSV/API or MCP-based reporting workflows. It also describes seven-day pitch projects that can become client projects while retaining their initial history. These are documented offers, not features tested for this article. Confirm the exact project, integration and access entitlements in the selected package. Peec’s agency workflow
For a demonstration, ask the operator to move from one client to another, export an answer-level record and create a client-facing report with the intended permissions. Unlimited seats and a branded dashboard do not by themselves establish the access controls your agency needs. Test the client view, not only the agency administrator’s view.
OtterlyAI’s plan includes engines, then adds others separately
OtterlyAI’s current plan documentation lists daily tracking of Google AI Overviews, ChatGPT, Perplexity and Microsoft Copilot. Google AI Mode, Gemini and Claude are listed as paid add-ons. The same document distinguishes one workspace on Lite from unlimited workspaces on Standard and Premium, with unlimited team members. OtterlyAI’s plan documentation
Its monitoring documentation describes drilling from a prompt into individual responses, citation details and engine-level results. That is the level to inspect before committing to the client-reporting process. Ask for a complete result and an unavailable-result example rather than judge the product from the aggregate chart. OtterlyAI’s prompt monitoring workflow
The pricing page currently displays Standard at US$189 per month for 100 prompts. On Standard, Google AI Mode and Gemini are each listed at US$59 monthly as add-ons. Those two additions would bring that published monthly component total to US$307, excluding tax and any other usage or purchase. Confirm the actual checkout currency and billing term. OtterlyAI’s current pricing
That calculation is useful when a brief names the exact surfaces. “Google AI” is too vague for procurement: AI Overviews, AI Mode and Gemini are different collection targets, and the documented package treats them separately.
Price the same three-client workload
Take a fictional agency with three clients. Each client has 20 agreed buyer questions in one country. The initial brief asks for daily monitoring on three selected surfaces during a 30-day period.
The workload is 60 client questions and 5,400 planned question–model–day observations: 3 clients × 20 questions × 3 models × 30 days. This is planning arithmetic, not a vendor’s observed output or a claim about customer demand.
For Peec’s documented allocation model, that example uses 1,800 credits per client and 5,400 in total. It exceeds the documented minimum per project but fits within the listed 10,000-credit Essential capacity. If every client expands to six selected models, the arithmetic becomes 10,800, above that allowance. Peec’s capacity model
For OtterlyAI, the 60 questions sit below Standard’s listed 100-prompt allowance, subject to the actual configuration and country treatment. The base engine set includes four services, so identify which three the client will use in its contracted report. If the brief expands to include Google AI Mode and Gemini as well, price those add-ons explicitly rather than imply they were already included. Plan allowances and included engines
The example supports a workload comparison, not a cheapest-vendor claim. Obtain a dated Peec quote for the exact allocation and billing term, then place it beside the matching OtterlyAI configuration. The current sources reviewed establish Peec’s credit capacity and rules; they do not provide a sufficiently unambiguous cash quote for this article to calculate a final cross-vendor total.
| Requirement to put in the quote | Peec AI check | OtterlyAI check |
|---|---|---|
| Three clients with 20 questions each | Per-project allocation and total credit capacity | Total prompt capacity and workspace setup |
| Three specified models, daily | Which models and cadence are enabled in each project | Whether every required engine is in the base plan or an add-on |
| A new second country | How the country/prompt configuration changes allocation and reports | Whether another country requires another configured prompt and how it counts |
| Client-facing reporting | Exact dashboard, export, integration and permission entitlement | Exact export/API and client-access arrangement |
| A larger month or validation repeats | How allocation, calendar length and extra checks are handled | How repeat collection, prompt additions and billing changes are handled |
Ask the vendor to configure the example during the demonstration. The output should be a settings summary, an estimated bill and a sample report, all describing the same workload.
Preserve how each answer was collected
OtterlyAI says it collects from public web interfaces and notes an exception for Claude, which it tracks through an API. Its documentation also acknowledges that personal results can vary with session, location and account settings. Treat its description as the vendor’s collection method, not a promise that every customer will see the same answer. OtterlyAI’s data collection explanation
Request equivalent details from Peec for each selected engine. At minimum, retain the actual surface, location, language, collection date and whether the answer came from a consumer interface or API. A country setting is useful only when you understand what it controls. Naming Singapore inside a question, querying from Singapore and using an account associated with Singapore can produce different tests.
For an agency, this belongs in the report’s method note. Keep it short enough for a client to read and specific enough for an analyst to reproduce. For example: “These are the same 20 questions, collected daily on the specified surfaces in the documented country setting. Failed collection and answers without an AI result are reported separately.” Add any known limitations rather than silently filling a missing answer with zero.
Preserve a stable core panel when onboarding a new client. Put newly discovered questions in an exploration set. If the agency replaces difficult questions with easier ones each month, a rising visibility chart can become impossible to interpret.
Test reporting and client handover before selling the retainer
Ask the vendor to demonstrate three reporting tasks using safe sample data.
First, export one answer record with the exact question, response, time, engine and sources. Check whether the exported fields preserve what an analyst sees in the interface. A count without its supporting record can be difficult to review after an account handover.
Second, give a client reviewer the intended level of access. Test whether they can open their report, reach the agreed evidence and remain separated from another client’s information. Decide whether the agency is selling access to the platform, a read-only dashboard or a periodic delivered report.
Third, reproduce the monthly numbers outside the presentation. Pick one client and reconcile the attempted questions, collected answers, unavailable results, mentions and eligible citations. If the totals depend on a vendor-specific definition, include that definition in the client-facing explanation.
OtterlyAI documents an API for pulling visibility, prompt and citation data into other reporting systems. It also offers Agent Analytics from Standard upward, using site logs to inspect crawler activity. Those are separate evidence feeds with separate setup and access requirements. OtterlyAI’s API documentation, Agent Analytics
A crawler visit, a source citation and an attributed enquiry should occupy separate rows in the report. Joining them by date can support investigation; it does not prove a single customer journey or causal effect. A generic search-engine referrer also needs more evidence before it becomes an AI-specific conversion.
The reporting workload the subscription does not price for you
Software capacity is only one part of the agency margin. Estimate the time needed for onboarding, prompt selection, disputed results, monthly explanation and implementation coordination.
Use a small actual delivery trial to measure that effort. For the fictional three-client agency, record how long an analyst takes to:
- Review a client’s business, approved claims and product sources
- Freeze the initial panel and label branded versus unbranded questions
- Inspect ambiguous brand matches and source-link roles
- Turn a supported finding into an implementable brief
- Discuss the result with the client and record the next decision
Leave those hours as measured observations. Do not borrow a vendor’s testimonial or assign an invented time saving. After the trial, the agency can decide whether the retainer covers monitoring alone, review and recommendations, or implementation as well.
This also helps define escalation. An incorrect warranty statement may need a product owner. An inaccessible source may need the website operator. An API limit may need the monitoring account owner. Name the person who will handle each issue before it becomes an unexplained delay in a client report.
Where Beacon by EVAA could complement the monitoring tool
Beacon has two separately priced offers. SaaS monitoring covers prompt tracking, share of voice and basic AI visibility reporting, with published monthly plans of $49, $99, $199 and $399. Confirm the exact surfaces, cadence, access and deliverables in a walkthrough. Enterprise and agency interactive assistant or plugin implementation is Custom: a separately scoped service for supported platforms such as ChatGPT and Claude. Availability, connection requirements, permissions, integration work and maintenance are agreed for each project. A monitoring subscription does not include a custom plugin build. Beacon pricing.
Beacon by EVAA’s stated catalogue-grounded assistant implementation and monitoring offer can be evaluated when the agency needs delivery work beyond its chosen research system. Examples include connecting an approved product source to a branded assistant, defining its supported actions or maintaining source-to-answer checks. Each capability needs an actual demonstration and written scope for the client concerned. Beacon by EVAA’s public description
The agency should ask for the data handover, permissions, evidence format, maintenance owner and acceptance tests. It should also decide whether it wants to keep its own monitoring account as an independent view of unconnected discovery.
A catalogue integration can work correctly while a brand remains absent from sampled buying answers. A brand can also earn a mention while the answer gives an incorrect price. Report those outcomes separately so neither the agency nor the client mistakes one for the other.
Run a small purchasing test before expanding
Choose one representative client or an explicitly fictional fixture. Define the exact question set, countries, engines and reporting output. Ask Peec and OtterlyAI to configure that same brief and show a sample export and client report. Obtain the applicable cash quote, billing term and feature entitlements in writing.
Then review one complete monthly-style report with the person who would actually use it. Can they trace the findings? Do they understand the missing data? Can they identify the next correction and its owner? Record the time your team spent producing that result.
Select the package that meets that workflow at a sustainable total delivery cost. Keep any implementation proposal separate enough that the client can see what will be built, what will be monitored and who remains accountable after the first report.