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AICosts.ai vs Arobis AI

Bottom line

AICosts.ai has a free plan plus paid upgrades, while Arobis AI is paid.

Which one should you try?

AICosts.ai

Freemium

Best for Finance teams managing distributed AI infrastructure across multiple vendors

Visit AICosts.ai See full review

Arobis AI

Paid

Best for SaaS companies seeking visibility in AI-generated answers

Visit Arobis AI See full review

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

AICosts.ai

AICosts.ai

The tool connects read-only to 50+ AI providers via billing API keys, aggregates daily spend by platform and model, and surfaces a 30-day forecast with an 80% confidence interval — so you see the spread, not a false-precision point estimate. Budget alerts fire at 50%, 80%, and 100% of a monthly threshold, scoped to a specific provider or platform if you need that granularity. For providers that expose no billing API, you upload a PDF or CSV invoice and it parses into the same structure. The comparison page shows what your last 30 days of token volume would have cost on cheaper model alternatives — but it never touches your traffic. Read-only throughout, zero inference-path involvement.

Arobis AI

Arobis AI

Arobis AI runs structured audits against real buyer prompts across ChatGPT, Gemini, Claude, and Perplexity, then restructures your content and entity signals so AI engines cite you instead of skipping you. The workflow moves through three stages: audit what AI surfaces about you, restructure content for semantic clarity, and build authority signals that AI models use to decide who gets recommended. This is a done-for-you service, not a software platform — there is no dashboard to log into, no API to wire up, and no self-service configuration. Teams that need real-time competitive monitoring or want to run their own prompt tests are dependent on Arobis to surface that data. Because pricing is custom and the service model is agency-style, iteration speed is tied to the engagement cadence, not your sprint cycle.

AttributeAICosts.aiArobis AI
PricingFreemiumPaid
Price$19.99/mo (Starter), $49.99/mo (Professional), Custom (Enterprise)—
Pricing checkedNot checked yetNot checked yet
Free trial7 daysNot stated
Open sourceNoNo
Has APIYesNo
Self-hosted optionNoNo
PlatformsWeb (SaaS), Desktop via WebCatalog for macOS and WindowsWeb-based SaaS platform
Released2025—
Pros
  • Read-only ingestion across 50+ providers, which means your provider configuration is never touched and your security review does not need to treat this tool as infrastructure risk.
  • PDF and CSV invoice upload for providers without a billing API, so gaps in your provider coverage do not force you back to maintaining a separate manual spreadsheet.
  • 30-day spend forecast rendered with an 80% confidence interval rather than a single point estimate, so budget presentations to finance reflect actual uncertainty instead of false precision.
  • Budget alerts scoped to individual providers or features — not just a global account total — which means a single runaway integration triggers a notification before it distorts the whole month.
  • Model cost comparison against cheaper alternatives for your actual token volume over the last 30 days, so the conversation about switching models starts from your real usage data rather than a vendor's benchmark sheet.
  • Audits run against actual buyer prompts across ChatGPT, Gemini, Claude, and Perplexity simultaneously, so you see your real AI Share of Voice instead of inferring it from proxy metrics.
  • Content restructuring targets semantic clarity and entity signals — the specific signals AI engines use to decide who gets cited — which means optimization effort is not wasted on factors that move Google rankings but have no effect on generative answers.
  • Authority Engineering builds citation signals across the web, so your brand accumulates the external trust footprint that AI models weight when selecting sources rather than relying solely on on-site content.
  • The service model handles the diagnostic and execution work, so marketing teams without in-house GEO expertise can close the AI visibility gap without hiring or retraining before the category is locked in.
  • The free AI Visibility Audit provides a concrete baseline of where your brand surfaces across AI platforms before any engagement begins, so the decision to proceed is grounded in actual data rather than vendor claims.
Cons
  • The tool is observation-only: it identifies that your Bedrock spend jumped 40% this week but takes no action on that signal. Teams that want automatic traffic rerouting to cheaper models when costs spike will need a separate layer — a proxy, a gateway, or custom routing logic — and at that point AICosts.ai becomes one input among several rather than a complete solution.
  • Peer benchmark comparisons are gated on having at least three other customers in the cohort using the same model. For teams running newer or less common models, the benchmark feature returns nothing and the cost comparison stays limited to the what-if calculation against alternatives — useful, but not the same as knowing where you stand relative to peers.
  • The 30-day forecast is built from a 7-day trailing sample. Teams with highly irregular usage patterns — large batch jobs that run monthly, seasonal spikes, or a product launch that doubles token volume overnight — will find the confidence interval widens to near-useless levels, and any team requiring longer-horizon budget modeling will need to export the data and build their own projection.
  • There is no self-service dashboard or software platform — competitive Share of Voice data, prompt test results, and optimization progress are delivered through the service engagement, not pulled on demand. Teams that need to monitor AI visibility weekly on their own schedule cannot do that here.
  • The service model ties iteration speed to engagement cadence. When a product launch or category shift requires rapid content signal updates, waiting on a service cycle is a hard constraint — not a workflow preference. Teams running high-frequency content experiments move to in-house GEO tooling or software platforms that let them push changes and measure AI response without an external dependency.
  • No API and no self-hosted option means the service cannot be wired into an existing marketing data stack or analytics pipeline. Reporting lives inside the engagement, not inside your BI tools.
  • The vendor site went live in early 2025, which means the track record, case study depth, and long-term citation durability of the optimization work are unproven at the scale and time horizon that enterprise procurement requires. Teams with rigorous vendor evaluation criteria will have limited third-party validation to reference.

Made up your mind?

AICosts.ai

Freemium

Best for Finance teams managing distributed AI infrastructure across multiple vendors

Visit AICosts.ai See full review

Arobis AI

Paid

Best for SaaS companies seeking visibility in AI-generated answers

Visit Arobis AI See full review

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