How to Write SLA Pages for AI Citations

How to write SLA pages for AI citations: publish an honest service-level agreement, uptime commitment, or service-credit policy page answer engines can extract for residual “does [brand] have an SLA,” “[brand] uptime guarantee,” “what is [brand] SLA,” and “[brand] service credits” questions — freeze commercial prompts first, lead with commitment + measurement window + credits + constraints, keep claims consistent with status and contract facts, and re-probe the same wording. No invented 100% uptime promises or fabricated citation lifts.

SLA pages for AI citations are owned service-level-agreement landings, uptime-commitment hubs, service-credit policy pages, and “what our SLA covers” surfaces that answer residual questions like “does [brand] have an SLA,” “[brand] uptime guarantee,” “what is [brand] SLA,” “[brand] service credits,” “is [brand] 99.9% uptime,” and “does [plan] include an SLA.” Buyers often ask AI for uptime and service-credit facts before they commit — engines may ground those answers in a clear owned SLA page, a status-page footer, a pricing enterprise note, a peer review, a contract template, a trust page claim, or a stale marketing restatement. This guide is the content craft for the SLA / uptime commitment / service-credit surface: which residual prompts to freeze, how to write an SLA page machines and humans can use, and what not to fabricate. It is not a promise that an SLA page guarantees a citation. It is not the same as pure status residual alone (see status pages for AI — live incident and uptime feed), pure trust residual alone (see trust pages for AI), pure security residual alone (see security pages for AI), pure pricing residual alone (see pricing pages for AI), pure FAQ residual alone (see FAQ pages for AI), or pure support-portal residual alone (see support portal pages for AI). Pair with answer-first craft, entity consistency when plan and product names fragment, and schema for AI citations only when visible facts are true.

When an SLA page is the right hypothesis (and when it is not)

If free-check or paid probes never surface SLA / uptime-guarantee residual questions for your domain, do not invent a giant “SLA GEO” program. Measure demand first. Some brands correctly ship one clear extractable SLA page and keep custom enterprise MSAs private — ship an honest public SLA shape, not a forever “100% uptime with unlimited credits on every plan” claim that still answers AI wrong after contract changes.

Freeze the commercial prompts before you write

1. Collect real wording — “does [brand] have an SLA,” “what is [brand] uptime guarantee,” RFP questions about service credits, competitor win/loss that mentions SLA friction, and existing AI probe rows.
2. Group by residual type — uptime residual, credit residual, measurement-window residual, and plan-eligibility residual as separate groups when they appear.
3. Freeze exact strings for baseline and re-probe. Do not rewrite the prompt after you publish to force a prettier sample.
4. Weight by commercial value — SLA questions that sit on enterprise purchase trust and hard-to-win residual — not which keyword is easiest for classic SEO alone (fix prioritization).

An SLA rewrite without a frozen prompt set is a trust project with no measurement contract.

SLA page skeleton answer engines can parse

• What commitment exists and who it covers first — first screen states brand/product/plan names, whether a public SLA exists, and which plans are in scope before a long brand film only.
• Uptime target, measurement window, and credits extractable — percentage when public, monthly/quarterly window, how credits are calculated, and how to claim when public.
• Hard constraints when public — scheduled maintenance, force majeure, customer-caused outages, region differences, and plan exclusions; do not invent “100% uptime forever on every plan with unlimited credits” solely to win a prompt if limits apply.
• Support response and severity shapes when true — severity tiers and response/restore targets when those are part of the public SLA (and only when you can defend them).
• Brand and plan names consistent — company brand, product SKUs, and plan labels match live pricing and contract reality (entity consistency).
• Stable permanent URL — one primary /sla or /service-level-agreement (or equivalent) so extractors and re-probes share the same target.
• Status, trust, security, pricing, support, and legal linked, not invented — live incident residual uses status craft; security residual uses security craft; plan residual uses pricing craft; ticket residual uses support-portal craft.
• Schema only when true — WebPage / FAQPage facts must match visible text; never markup fake uptime percentages, invented credits, or guaranteed citation outcomes (schema for AI citations).

SLA page vs status vs trust vs security vs pricing vs support

Pick one primary public URL per residual group when possible so extractors and buyers do not reconcile three contradictory “what is your SLA” restatements.

Honesty rules (hardcoded safety, not strategy judgment)

• No fabricated 100% uptime, phantom credits, or invented “unlimited SLA on free plans” — do not invent unconditional uptime solely to win a prompt; label exclusions, windows, and plan eligibility as constraints when true.
• No contradiction with status history, enterprise contracts, pricing footnotes, or legal MSA terms — if marketing says 99.99% while the SLA PDF says 99.5% with heavy exclusions, extractors and buyers lose trust; pick one primary public truth and align.
• Label plan, region, and channel differences clearly — free vs paid, enterprise vs self-serve, multi-region, and dedicated vs multi-tenant when they differ; do not leave conflicting SLA answers live as the only public explanation.
• One primary SLA URL when possible — avoid three thin keyword clones fighting for the same “[brand] SLA” question.
• Legal and finance claims stay reviewed — service credits, liability caps, and regulated availability claims need the same review path as any public claim; SLA GEO does not bypass legal or finance review or override signed MSAs.

Ship → re-probe loop (no invented lifts)

1. Baseline — freeze SLA / uptime-guarantee / service-credits residual prompts; log presence, position notes, and cited-instead domains on each engine you care about.
2. Publish one SLA page hypothesis — one primary public SLA page for the highest-weight residual group.
3. Wait for crawl reality, then re-probe the same wording — label moved / unchanged / mixed / not yet. Never invent lifts (citation-lift standards).
4. If unchanged — inspect cited-instead: do engines still prefer peer SLA roundups, status footers, pricing footnotes, or contract blogs? Improve extractable commitment + window + credits — do not thrash every “always on” slogan weekly for “GEO.”
5. Cadence — after plan packaging changes, SLA percentage flips, credit policy changes, rebrand, or multi-region launches, re-check those residual prompts on purpose (re-probe cadence).

What product / legal / CX teams should not do

• Ship a pretty SLA shell with no extractable commitment, window, credits, or brand/plan name in HTML.
• Add schema with fake uptime percentages, credits, or awards that are not visible.
• Rewrite free-check prompts until one ChatGPT sample recites your SLA URL.
• Claim multi-engine wins from a single friendly chat screenshot.
• Leave contradictory 100% vs limited uptime claims live as the only public explanation of a still-asked residual.
• Treat schema or llms.txt alone as the SLA strategy (llms.txt is mechanism, not a switch).

How jujuGEO supports SLA-page GEO

jujuGEO discovers buyer- and customer-style questions (including SLA, uptime-guarantee, service-credits, and 99.9% residual shapes when they appear for your domain), probes live engines, shows who is cited instead, drafts gap-specific answer-ready fixes, and re-probes after publish. Start with a free AI visibility check to see whether SLA residual gaps exist, then freeze the real commercial questions before rewriting every “always on” slogan. Related: answer-first content for AI, status pages for AI, trust pages for AI, security pages for AI, SaaS AI visibility, cited-instead content roadmap, and what is AI visibility.