KIME

Overview

KIME is an AI-search visibility platform for measuring how a brand appears in generative answers and turning those observations into prioritized work. Its public product pages describe prompt tracking, competitor benchmarking, AI perception and sentiment, citation analysis, country and language filters, and an action center. KIME also positions AWX, its agentic execution layer, as a way to carry out selected content, outreach, and technical tasks rather than only reporting a visibility score.

That puts KIME closer to a content-optimization and GEO operations platform than to a passive rank tracker. The distinction matters: a KIME score is a sampled observation of selected prompts and engines, while the optimization and execution layer is a separate workflow whose quality, safety, and outcome still need to be tested by the buyer.

• Best for: Marketing teams, ecommerce brands, and agencies that want transparent entry pricing, prompt-level AI visibility measurement, competitor comparisons, and an optional action/execution layer.
• Not ideal for: Buyers who need a complete census of real user questions, independently audited citation lift, or a mature neutral review consensus for the newer agentic features.
• Current public price: Explorer at €99/month and Core at €399/month; Enterprise is custom-priced. Annual billing is advertised with a 15% discount and quarterly billing with a 5% discount.
• Free access: The official pricing page advertises a 7-day free trial for Explorer and Core. That is a trial offer, not a permanent free plan.
• Primary strength: The published plan matrix makes prompt, engine, response, seat, and agentic-execution allowances easier to compare than many quote-led GEO platforms.
• Primary limitation: Independent product-specific evidence is still sparse, and the sampled nature of AI-answer metrics limits what visibility and share-of-voice numbers can prove.

Quick facts

Fact	Publicly verifiable detail
Main job	Track and interpret AI-search visibility, then prioritize and optionally execute optimization work
Main category	Content optimization and GEO operations
Explorer	€99/month; 50 unique prompts, 2 AI engines, 3,000 AI responses/month, 10 agentic executions/month, 5 seats
Core	€399/month; 200 unique prompts, 3 AI engines, 18,000 AI responses/month, 30 agentic executions/month, 10 seats
Enterprise	Custom prompts, all available models, 40–100 agentic executions/month, 30–50 seats, and expanded support/services
Trial	7 days on Explorer and Core according to the official pricing page
AI surfaces named	ChatGPT, Google AI Mode, Perplexity, Google AI Overviews, Gemini, Microsoft Copilot, Claude, Grok, DeepSeek, and Meta AI; plan access differs
Measurement	Prompt responses, mentions, position, sentiment, cited sources, visibility score, and share of voice are vendor-described metrics
Localization	Unlimited languages and countries are listed in the current plan comparison
Optimization	Action center, custom task management, AWX agentic execution, and Optimus self-optimization are listed; confirm account entitlement and safeguards
Integrations	MCP access and advanced API access are listed across the published plans
Independent signal	Farman Rind’s July 18, 2026 practitioner review evaluates KIME as a useful measurement layer but says the product did not provide much strategy guidance in that review
Review-platform signal	Capterra displayed 0.0 from 0 user reviews when checked on September 16, 2026; this is an evidence-volume boundary, not a quality score
Last reviewed	September 16, 2026

AICiteKit editorial verdict

KIME is a credible candidate for teams that want a dedicated AI-search measurement layer without starting at an enterprise-only price. Explorer’s 50 prompts, two engines, five seats, and 3,000 response allowance provide a bounded way to establish a baseline. Core is materially more expensive, but it increases prompt and response capacity and adds onboarding support rather than merely charging per additional seat.

The most interesting part of the current positioning is the move from measurement to action. KIME says the action center turns visibility gaps into tasks and AWX can execute selected content, outreach, or technical work. That may reduce the handoff between “we are not being cited” and “what should we change?”, but the official material does not independently establish the quality, factual safety, approval controls, or citation impact of those executions. Treat AWX as a workflow capability to evaluate, not as proof of improved visibility.

There is also a notable evidence conflict. A July 2026 practitioner review describes KIME primarily as a measurement tool and criticizes the lack of optimization guidance, while the current official site prominently presents AWX and Optimus. The newer official positioning establishes current advertised scope; it does not retroactively validate the reviewer’s assessment of the agentic layer. Buyers should test the current account and document what is included in their plan.

Bottom line: KIME is worth a structured 7-day trial for a team that can define a representative prompt set and wants measurement plus optional execution in one workspace. It is not a substitute for a carefully designed sampling methodology, content review, technical SEO work, or independent proof that AI visibility changes lead to traffic, leads, or revenue.

Who should use KIME?

Best fit

• In-house marketing and SEO teams that need a repeatable baseline across selected AI engines.
• Agencies that want multiple seats, brand workspaces, competitor comparisons, and a client reporting narrative.
• Ecommerce and consumer brands where product/category recommendations in AI answers are strategic concerns.
• Teams that want to connect a visibility gap to a content, outreach, or technical task backlog.
• Buyers who prefer a public monthly price and a bounded trial before discussing Enterprise scope.

Not a strong fit

• Teams expecting a free ongoing monitor rather than a seven-day trial.
• Buyers who need statistically representative real-user query data instead of a configured prompt panel.
• Organizations that require a fully documented model-version, geography, raw-answer-retention, export, or audit trail before procurement.
• Teams looking for traditional Google rank tracking, backlink intelligence, or a complete replacement for an SEO suite.
• Governance-heavy publishers that will not allow agentic content or technical changes without review, rollback, and audit controls.

What does KIME do?

The public workflow can be understood as five connected layers:

1. Define the observation set. Choose prompts, countries, languages, engines, competitors, and the brand entities to monitor. The number of unique prompts and engines is plan-dependent.
2. Collect AI answers. KIME says it runs tracked prompts against selected AI platforms and extracts brand mentions, position, sentiment, and cited sources. The resulting data is a sample, not a census of every answer a user might receive.
3. Compare performance. Visibility, share of voice, sentiment, competitor presence, and citation sources can be analyzed by engine, market, and time period.
4. Prioritize work. The action center is intended to turn gaps—such as a competitor appearing for a prompt where the target brand is absent—into content, technical, or editorial tasks.
5. Execute selectively. AWX is described as an agentic layer that can carry out selected tasks. Buyers should confirm approval gates, human review, publishing permissions, source handling, and rollback before enabling automation.

Core features and practical implications

Prompt and engine monitoring

KIME’s pricing page separates Explorer’s two engines and Core’s three from Enterprise’s broader model access. The homepage and FAQ name ten possible AI surfaces, but the existence of a named surface on the product page does not prove that it is included in every plan. Confirm the exact engine mix, refresh frequency, response quota, and raw-answer access in the trial account.

Competitor benchmarking

The platform compares a brand against selected competitors using the same configured prompts and engines. This is useful for identifying relative gaps inside a defined panel. It should not be reported as total market share: competitor selection, prompt wording, market, model behavior, and sampling cadence all affect the result.

Citation and source analysis

KIME shows which domains or sources are cited when monitored answers mention a brand. This can help a content team build a source portfolio and investigate why a competitor is repeatedly present. Citation frequency still does not prove referral traffic, conversion, authority, or that the cited source caused the answer.

AI perception and sentiment

The official product pages describe sentiment distribution and the words AI systems associate with a brand. Buyers should inspect the underlying answer examples and classification rules during the trial. A positive sentiment percentage is an interpretation of sampled model outputs, not a customer-satisfaction survey.

Action center and AWX

KIME’s current commercial pages list an action center, custom task management, and monthly agentic-execution allowances. The unit is important: Explorer includes 10 executions and Core 30, while the analytics suite is described separately. Before purchase, ask what counts as one execution, whether failed or revised tasks consume allowance, which actions can publish or modify a site, and what approval and audit controls exist.

MCP and API access

MCP and advanced API access are listed in the plan comparison. The presence of an access entitlement does not establish rate limits, endpoint scope, retention, export format, authentication controls, or whether all visibility data is available programmatically. Technical teams should request current documentation and test a representative export before treating the integration as production-ready.

AI engine and platform coverage

KIME’s current FAQ names ChatGPT, Google AI Mode, Perplexity, Google AI Overviews, Gemini, Microsoft Copilot, Claude, Grok, DeepSeek, and Meta AI. The pricing table assigns two engines to Explorer, three to Core, and all available models to Enterprise. The official pages do not provide a complete public matrix for model versions, regional availability, answer types, browser/API collection method, or retention period.

That boundary is central to interpreting the product. “Tracks ten AI engines” is a vendor-described maximum, not a guarantee that a buyer’s plan, country, language, or account can run all ten. Ask for a plan-specific coverage matrix and record whether Google AI Mode and Google AI Overviews are sampled through the same workflow or represent different products and data sources.

Plans, pricing, and usage limits

Plan	Published price	Prompt and response allowance	Engine and execution allowance	Practical fit
Explorer	€99/month	50 unique prompts; 3,000 AI responses/month	2 engines; 10 AWX executions/month; 5 seats	A bounded baseline for one marketer or a small pilot
Core	€399/month	200 unique prompts; 18,000 AI responses/month	3 engines; 30 AWX executions/month; 10 seats; onboarding support	A recurring program with a larger prompt panel and team workflow
Enterprise	Custom	Custom prompts and all available models	40–100 AWX executions/month; 30–50 seats; expanded support	Larger organizations needing scope, services, and access negotiation

The official pricing page says plans can be billed monthly, quarterly, or annually, with advertised discounts of 5% for quarterly and 15% for annual billing. It also says there are no per-seat or per-model fees. Buyers should still confirm taxes, currency conversion, response overages, data-retention terms, and what happens when an execution or response allowance is exhausted.

Capterra’s current listing adds a conflicting legacy/provider-data observation: it displayed €127/month for a Lite plan and €339/month for Pro, with 25 and 100 unique prompts respectively. The listing also reported a free trial but no user reviews. Because those figures conflict with the current official pricing page and may represent older provider-supplied metadata, they should not be treated as current list pricing. Ask KIME to reconcile the plan names, allowances, and effective date in the contract or checkout flow.

Strengths

• Public pricing exposes prompt, response, engine, seat, and agentic-execution units.
• A 7-day trial enables a bounded baseline without requiring an Enterprise sales process.
• Competitor and citation views connect AI-answer observations to content research questions.
• Unlimited country and language fields are advertised across the plan comparison.
• The action center and AWX provide a potential bridge from measurement to execution.
• MCP and API access are presented as first-class integration paths.

Tradeoffs and limitations

• The independent evidence base is immature: Capterra showed no user reviews, and the available practitioner review is a single authored assessment rather than a consensus sample.
• Prompt-panel metrics are directional. They depend on query selection, model version, geography, language, timing, and refresh cadence.
• The public pages do not fully document sampling methodology, raw-answer retention, export detail, or plan-specific regional/model constraints.
• Current official positioning includes AWX and Optimus, but the independent review predates or does not evaluate the newer agentic scope.
• Enterprise features, model coverage, and execution capacity require account-level confirmation.
• Visibility, sentiment, citation, and share-of-voice numbers do not prove rankings, traffic, leads, or revenue.
• A seven-day trial may be too short to attribute changes in public AI answers to newly published content or technical changes.

User reviews and market feedback

Evidence snapshot

Source	Public signal	What it supports	Confidence and bias
KIME official pricing	Explorer €99/month and Core €399/month; plan allowances and 7-day trial are displayed	Current commercial packaging, prompt/response/engine/seat/execution boundaries	High for displayed vendor terms; vendor-controlled
KIME official product page	Current product scope includes prompt monitoring, competitor analysis, citations, action center, AWX, and MCP	Advertised workflow and feature direction	Medium-high for current positioning; does not prove efficacy
Farman Rind practitioner review	July 18, 2026 review describes clean measurement, citation tracking, and competitor benchmarking; it also calls the data directional and says strategy guidance was limited	Practical workflow observations and important sampling caveats	Medium-low; one practitioner review with author-affiliated consulting context
Capterra KIME listing	0.0 from 0 user reviews when checked September 16, 2026; provider-data pricing differs from the current official page	Evidence scarcity and a dated/conflicting commercial observation	High for the observed listing state; not a quality rating or customer consensus
KIME customer statements	Named testimonials from Saxo, THEMAGIC5, Superb, and VR Travel	Vendor-selected customer claims about perceived clarity and usefulness	Low-medium; vendor-selected, not independently audited

Recurring positive themes

The accessible practitioner review emphasizes a focused dashboard, multi-platform coverage, citation-frequency tracking, competitive share-of-voice views, and trend reporting. The official testimonials similarly describe clearer visibility into how brands perform across AI platforms. These are useful directional signals about the intended workflow, but they are not a statistically recurring theme across a large independent sample.

Recurring concerns and tradeoffs

The strongest documented concern is methodological rather than a complaint about interface quality: a configured prompt set cannot represent every real user query, and a citation-rate percentage can overstate precision if presented as absolute market share. The practitioner review also described KIME as a measurement layer that required a separate strategy layer; the current official AWX positioning may address part of that gap, but the newer execution workflow lacks comparable independent evaluation.

How much should buyers trust the evidence?

Official evidence is strong for the current displayed plans and advertised feature direction. Independent evidence is much thinner. Capterra’s zero-review state means there is no public product-specific review consensus to summarize; it should not be converted into a 0.0 quality judgment. The practitioner review is valuable for explaining sampling limits and workflow fit, but it is one dated perspective. Vendor testimonials are useful context about claimed use cases and should not be treated as neutral proof of citations, traffic, or revenue.

AICiteKit interpretation

KIME has enough current official evidence to justify a bounded trial, but not enough independent evidence to support a confident claim about the quality or outcomes of its newer agentic layer. Use it as an instrument for a defined experiment: document the prompt panel, compare repeated answers, inspect cited sources, and keep human approval over any AWX action.

What to verify during a trial

1. Export the same prompt set before and after a controlled content or technical change; record engine, country, language, date, and model context.
2. Confirm whether the selected Explorer/Core engines match the plan table and whether Google AI Mode and AI Overviews are available in the target market.
3. Inspect raw answer examples behind visibility, sentiment, position, and share-of-voice metrics rather than relying only on aggregate scores.
4. Test citation-source exports and determine whether URLs, answer snapshots, timestamps, and model metadata are retained.
5. Run one low-risk AWX task in a staging or draft workflow. Verify approval gates, source citations, factual review, permissions, rollback, and execution-unit consumption.
6. Compare the current official plan with any checkout or proposal and reconcile the Capterra legacy pricing observation before subscribing.

Review evidence sources

• KIME pricing — official plan matrix, allowances, trial, discounts, and customer-selected statements checked September 16, 2026.
• KIME homepage — official current positioning, named engines, workflow, AWX, MCP, and FAQ claims checked September 16, 2026.
• Kime AI review by Farman Rind — independent practitioner review dated July 18, 2026; used for workflow observations and sampling limitations, not as proof of outcomes.
• Capterra KIME profile — provider directory and review-platform listing checked September 16, 2026; used to document zero product reviews and conflicting dated pricing metadata.

KIME compared with alternatives

Tool	Best fit	Key difference from KIME
Peec AI	Teams focused on prompt-level AI visibility monitoring and competitive gaps	Compare monitoring depth, engine access, reporting, and whether an execution layer is required
Profound	Enterprise teams seeking deeper consumer-panel and AI-search intelligence	Typically a higher-touch enterprise evaluation with different data and pricing assumptions
Scrunch AI	Brands and agencies wanting AI visibility tracking and reporting	Compare plan coverage, evidence methodology, and operational workflows
Surfer SEO GEO	Teams combining content optimization with an established SEO/content workflow	Compare content guidance and SEO integration against KIME’s prompt analytics and AWX direction

The comparison is about buying fit, not a universal ranking. A tool that samples more prompts is not automatically more accurate, and an agentic action layer is not automatically safer or more effective than a human-led workflow.

Recommended workflow

1. Start with a documented baseline: 30–50 prompts grouped by customer journey, product category, competitor comparison, and factual brand questions.
2. Run the baseline across the smallest plan that covers the target engines and market; save answer examples and cited domains, not only summary scores.
3. Separate measurement from intervention. Select one content or technical change and keep other major variables stable where practical.
4. Use KIME’s action center to prioritize a small task set, but require human review and staging for any generated content, outreach, or technical change.
5. Re-run the same prompt set on a defined cadence and annotate model, market, date, and content changes.
6. Report visibility and citation movement as sampled leading indicators. Connect them to Search Console, analytics, and conversion data separately rather than claiming that a KIME score caused revenue.

FAQ

Is KIME a free GEO tool?

No. The current official pricing page lists paid Explorer and Core plans, plus custom Enterprise pricing. Explorer and Core include a 7-day free trial, which is not the same as a permanent free tier.

How much does KIME cost?

The current official page lists Explorer at €99/month and Core at €399/month. Enterprise is custom-priced. Quarterly and annual discounts are advertised, and the page says there are no per-seat or per-model fees. Capterra displays older or conflicting provider data, so confirm the current plan and billing basis at checkout.

Does KIME monitor all major AI engines on every plan?

No. The official comparison assigns two engines to Explorer and three to Core; Enterprise is described as having all available models. The homepage names a broader maximum set, but buyers should confirm the exact engine, market, and model entitlement for their plan.

Does KIME improve AI visibility automatically?

KIME’s current site advertises an action center, AWX agentic execution, and Optimus. Those features indicate an execution capability, not guaranteed improvement. Test the generated work, approval controls, factual accuracy, publishing permissions, and before/after measurement during the trial.

Are KIME’s visibility and share-of-voice scores absolute market share?

No. They are based on the selected prompts and the AI engines KIME samples. Treat them as directional measurements for a defined panel, and document prompt design, geography, language, model, cadence, and answer variability.

Does KIME replace traditional SEO tools?

No. KIME focuses on AI-generated answers, citations, perception, and related actions. Traditional SEO tools still cover areas such as crawling, keyword rankings, backlinks, and search traffic that KIME does not replace.

Final verdict

KIME fills a useful middle ground between a basic AI-answer monitor and an enterprise GEO program: it publishes understandable plan limits, offers a short trial, and connects visibility observations to an action and agentic-execution concept. The product is most defensible as a measurement and workflow platform for a defined prompt panel.

The evidence boundary is equally important. Independent product feedback is sparse, Capterra currently shows no user reviews, and the available practitioner review predates or does not evaluate the full AWX positioning. Buyers should therefore treat KIME as a testable operating layer—not as independent proof of citations, rankings, traffic, leads, or revenue. A successful trial should leave the team with reproducible prompt evidence, a documented cost per measurement/execution unit, and a clear decision about which actions remain human-approved.

Sources and verification

• KIME official homepage — product scope, AI engines, workflow, AWX, MCP, and FAQ checked September 16, 2026.
• KIME official pricing — current Explorer/Core/Enterprise pricing, quotas, discounts, trial, and support terms checked September 16, 2026.
• Farman Rind’s KIME review — independent practitioner review published July 18, 2026; used with disclosed author and evidence limitations.
• Capterra KIME profile — review count, provider-data pricing, product description, and listing metadata checked September 16, 2026.

Last reviewed: September 16, 2026

Data confidence: Medium. Official pricing and advertised scope are directly documented; independent customer evidence for KIME and the current agentic layer remains limited.