17 questions, answered directly, one by one

Because every company's bottleneck in AI is different. Some are blocked by a CDN or WAF stopping crawlers; some lack authoritative external sources that can be cited; some have their own product data contradicting itself in several places; and some have confused entity identifiers that lead AI to mix them up with another company. These four kinds of problem have very different solutions and very different investment profiles.

The audit takes 10–15 business days to establish a baseline and map the citation structure of your main competitors, and delivers a 90-day roadmap, keeping a company from spending a whole year's budget in the wrong direction. Upgrade to an annual engagement within 30 days and the audit fee is credited against it.

The core effort is concentrated at the start: basic company materials (business license details, qualification certificates, a list of products and services, your pricing basis, organizational structure); one or two business interviews (to confirm the fact entries and how your core strengths are worded); and one internal reviewer as the point of contact.

As a rule of thumb: about 8–12 hours in the first month and 1–2 hours a month thereafter. Once things are running, the client side only needs to review the report monthly and confirm the facts in new content.

We use an “AI for efficiency + human sign-off” process. AI handles material parsing, structured rewriting, version derivation and video production at scale; people handle fact checking, the accuracy of industry terminology, the expression of viewpoints and the final sign-off. Everything published externally has to be fact-confirmed by the client before it goes out.

The reason is plain: when generative engines assess a source they also prefer content that is clearly written and backed by specific detail and data, and purely machine-written copy is at a disadvantage on that dimension.

That is precisely our most persuasive material, and the reason we never hide the number. The 42/100 came from Sinnet Cloud's own diagnosis in Q2 2026, with six-dimension scores of content authority 35, information structuring 48, technical accessibility 55, entity knowledge building 28, authoritative source coverage 52, and cross-platform consistency 38.

It shows two things: first, AI invisibility is a widespread problem that catches even technology and compute companies; second, this diagnostic method works — if it can honestly point out our own weak spots, it can point out yours just as well.

We do offer one-off engagements, corresponding to an information audit (10–15 business days) or optimization of a single in-depth piece of content. But we will be straightforward: a one-off engagement solves “knowing where you stand and what needs changing”; it does not solve “being cited continuously”.

The reason is that the source landscape of generative engines keeps changing — competitors are building, platform retrieval strategies are being adjusted, and a company's own products and qualifications are being updated too. The reason annual engagements include quarterly content updates and continuous monitoring is precisely to keep citation positions stable. Whether to choose an annual engagement depends on how urgent the client's window of opportunity is.

The engagement length is up to you: you can take a one-off engagement (AI information audit, delivered in 10–15 business days, covering up to 5 mainstream platforms and 50–100 core questions), or you can choose a 12-month continuous annual engagement (including quarterly content updates and continuous monitoring).

We recommend starting with an audit because it is a complete deliverable in its own right: question-set design, cross-platform sampling, competitor comparison, a six-dimension diagnosis and a 90-day roadmap. It has standalone value the moment it is delivered, regardless of whether you go on to work with us. For a specific proposal, please contact our sales team.

Sinnet Technology Co., Ltd. (SZSE: 300383.SZ) is the listed parent company; Sinnet Cloud Data Co., Ltd. is Sinnet Technology's core brand for cloud computing and AI compute, and has deployed more than 4,000P of compute clusters; aileo is the brand of the AI-era brand visibility product that Sinnet Cloud offers to enterprise customers.

The practical difference this background makes is: aileo's AI visibility monitoring and knowledge graph reasoning run on our own compute, so high-frequency automated sampling is not constrained by third-party compute costs.

It depends on whether your customers look for suppliers in AI. If they are B2B procurement decision-makers, in high-ticket decision scenarios, or in industries where trust is built on qualifications and professional capability, then the answer is yes — because when generative engines filter sources they depend less on domain authority than conventional search does. That gives small and mid-sized companies a relatively level playing field: as long as the facts are clear, the structure is complete and the sources are verifiable, a small company can be cited just as well.

Conversely, if your customers are purely offline, come purely through personal recommendations, or are instant purchases at a very low ticket size, GEO should be a lower priority.

Look at three things. First, are they willing to give you a diagnostic baseline — a trustworthy provider measures before it promises; anyone unwilling to do a baseline but happy to talk about results definitely has a problem. Second, do they draw red lines around what they promise — rule out anyone promising “guaranteed top recommendation”. Third, are the deliverables verifiable — fact entries, Schema files and monitoring reports should all be concrete files you can open and check, not adjectives in a slide deck.