What is the difference between AEO and GEO?

AEO (Answer Engine Optimization) is specifically about getting cited as a source when AI engines answer questions. GEO (Generative Engine Optimization) is broader — optimizing for inclusion in any AI-generated output, including product recommendations, comparisons, lists, and summaries. AEO is a subset of GEO.

Do I still need traditional SEO?

Yes. AEO doesn't replace SEO — it complements it. Traditional Google search still drives the majority of organic traffic for most B2B and ecommerce businesses. AI Overviews appear on roughly 47% of searches, but they often pull from the top SEO results. Strong SEO foundations make AEO 5-10x more effective.

How do you actually track AI citations?

We run a defined prompt set (30-100 queries depending on package) across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews on a weekly cadence. We log whether your brand is mentioned, where you appear in the response, what context, and which competitors are cited alongside or above you.

How long until I see results?

Faster than traditional SEO, slower than paid ads. Schema and structural fixes get reflected by AI engines within 2-4 weeks. Citation increases on existing pages: 4-8 weeks. New AEO content getting indexed and cited: 8-16 weeks. Compounding effects: 4-6 months.

What is the pricing for AEO services?

Three packages. Starter at $2,500/month for SMBs. Growth at $5,500/month for $5M-$25M brands. Enterprise from $12,500/month for $25M+ brands. Quarter-to-quarter contracts with no 12-month lock-ins. INR pricing available for India clients.

Will AI eventually replace traditional search?

For some use cases, yes. For others, no. Research-heavy queries increasingly happen in AI tools. Transactional queries still happen in Google. The right strategy is to optimize for both surfaces — your content engine produces material that ranks in SERPs AND gets cited by AI.

Ruby vs Smith.ai (2026): Virtual Receptionist Compared

Disclosure: some links are partner links — we may earn a commission at no cost to you. Opinions are our own from client work.

Ruby and Smith.ai are the two names small firms compare for virtual receptionist coverage. Both answer your calls with real humans backed by tech; the fit differs by volume, hours and what happens after the call. We reviewed both for client front-desk stacks.

The short answer

Ruby for the most polished caller experience and tight mobile app control — the premium pick for law firms and professional services where every call is a case. Smith.ai for heavier automation: AI-assisted intake, outbound follow-up, and chat included at aggressive prices.

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Where Ruby wins

Caller experience. Consistently rated among the friendliest, most professional live answers in the category — it feels like your own front desk. App control. Flip call handling, statuses and messages live from the mobile app. Bilingual answering included. Full notes: Ruby review and our Ruby vs traditional answering services breakdown.

Where Smith.ai wins

Intake + workflows. CRM logging, conflict checks, appointment booking and outbound callbacks are core, not add-ons. Price per interaction tends to land lower at similar volumes. Web chat staffing bundled if you want one vendor for calls + chat.

Head-to-head

Factor	Ruby	Smith.ai
Best for	Law/professional services, premium feel	Volume + automation-minded firms
Live answer quality	Category-leading	Strong
Intake/CRM workflows	Good	Deepest
Chat coverage	Available	Bundled focus
Control	Excellent mobile app	Dashboard-centric

Verdict

If missed calls are lost cases and brand feel matters, Ruby justifies its premium. If you want maximum automation per dollar, Smith.ai is the value engineer’s pick.

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