Built for · By team shape

Built for the seats the category leaders underserve

Most AI marketing tools are shaped for either a single solo founder or a fifty-seat enterprise team. The middle — agencies running five to twenty client brands, SaaS teams under $5M ARR, in-house marketers running every channel alone — gets squeezed in both directions. Sivon HQ is shaped for that middle, and the rest of this page explains how the same Brand Blueprint, diagnosis layer, and engines look different sized to each seat.

How to choose · A quick decision framework

The system underneath is the same on every tier — Brand Blueprint, diagnosis, seven engines. What changes is the shape of the container. These three filters point you to the right one without reading three landing pages back to back.

1 · How many brands do you actually run?

The first filter is the count of distinct brand contexts you hold. A solo in-house marketer at one SMB holds one. A SaaS team running a single product holds one — sometimes two if a second product or a major sub-surface counts. An agency running client work holds five to twenty.

The number maps to the workspace cap, which maps to the tier. One brand fits Starter ($29/mo) or Pro ($59/mo). Two to seven fits Pro. Five to twenty fits the Agency tier ($149/mo). Beyond twenty we cut a custom plan — talk to us. The cost stays predictable as the book of context grows; you don't pay per output, per seat, or per client.

2 · Where is the work bottlenecked — judgement or production?

The second filter sorts by which half of the marketing job is broken. Some teams know exactly what to ship and only need faster execution; others can produce drafts in their sleep but lose hours every week deciding what's worth producing.

The diagnosis layer is shaped for the second case — solo in-house marketers and SaaS teams with split marketing seats feel the lift fastest, because the missing system is precisely the ranked-priority system a director would have provided. Agency teams get value from diagnosis differently — it's the kickoff deliverable they ship to clients, not the input that triages their own week. Either way, the diagnosis ranks before generation, and that ordering is the entire premise.

3 · How much of your buyer research now happens inside an LLM?

The third filter is exposure to the AI citation surface — the share of your buyer's research that now begins in ChatGPT, Perplexity, Claude, or Google's AI Overviews. For most SaaS teams in 2026 this share is substantial and rising. For regional agencies serving local clients it's smaller. For in-house SMB marketers it varies with category.

Sivon HQ ships AI Visibility as a first-class engine on every tier above Free, and the value of that engine scales directly with your exposure. SaaS teams typically get the most leverage here. Agencies get leverage when they specialise in category-driven, technical, or B2B clients where the buyer is LLM-native. In-house marketers benefit when the SMB sells into a category where buyers research before they reach out — most consideration-driven categories qualify.

Pick your shape

Three landing pages, one underlying system

A different shape entirely? See the honest comparisons against Jasper, Copy.ai, Anyword, Writesonic, and ChatGPT — or tell us which seat you sit in. We're building the lineup our buyers actually shortlist.