AI Search Starter
A focused starting scope for one clear priority and a smaller operating surface.
- AI crawler accessibility
- Answer-ready page structure
- Documented starting roadmap
AI SEO PRICING
Choose a practical starting level for generative engine optimization, answer visibility, and AI-ready content systems.
These prices are published starting points, not automatic quotes. Final scope depends on the site, markets, access, technical condition, content requirements, and delivery responsibilities. We document those assumptions before work begins.
A focused starting scope for one clear priority and a smaller operating surface.
A broader working program for teams that need recurring execution and coordinated improvement.
A custom operating scope for larger sites, markets, catalogs, or stakeholder groups.
Cost changes when the program spans more templates, markets, integrations, approval layers, or production responsibilities. Existing analytics quality and implementation access also affect the work required.
Share goals, constraints, site access, and the commercial priority.
We inspect the operating surface and identify material dependencies.
You receive deliverables, responsibilities, cadence, and assumptions.
Work begins after access, owners, and acceptance criteria are clear.
They are starting points. A written proposal confirms the actual fee after the scope and responsibilities are understood.
No. Search platforms, markets, competitors, and customer behavior are outside any agency’s control. We commit to transparent work, documented decisions, and careful measurement.
Your agreement identifies ownership and access. We structure projects so your team retains the accounts, approved assets, and implementation documentation needed to continue operating.
Yes, through a documented change when new requirements or constraints appear. We explain the effect on cost and timing before additional work proceeds.
Pricing decision guide
Teams whose important pages need to be understood, extracted, cited, or represented accurately in answer engines and AI-assisted discovery.
Scope may include crawler access, answer-ready information architecture, entity clarity, structured data, source quality, citation research, and monitoring of representative prompts.
It does not include guaranteed citations, control over model responses, fabricated authority signals, or publishing unsupported expert claims.
Template count, knowledge depth, subject-matter review, markets, prompt sets, data access, and implementation ownership drive effort.
Before work starts, we need priority topics, representative customer questions, approved factual sources, analytics access, and a named reviewer for high-stakes claims.
Begin with the products, topics, and customer questions where inaccurate or absent AI answers matter. Test rendered access and source quality, then improve a representative page family before expanding prompt monitoring or editorial production.
Subject-matter experts approve factual claims; content owners maintain answers and sources; developers control templates and crawler output; analysts document prompts and limitations.
Published prices are starting points, not invented certainty. The final scope depends on the website, markets, current condition, data quality, release process, dependencies, and which team owns implementation. These pages provide the context needed to compare responsibly.
Review the operational problem, work areas, outputs, and measurement approach before comparing starting prices.
See how access, diagnosis, priorities, owners, dependencies, and acceptance criteria are established.
Use case studies to understand specific project conditions rather than treating another company’s result as a forecast.
Compare the adjacent program when requirements cross channels, platforms, or delivery teams.
Compare the adjacent program when requirements cross channels, platforms, or delivery teams.
Share the website, objective, current baseline, platform, timeline, and implementation ownership for a defensible scope.