AI-channel Growth Center: get your business into Doubao, Qwen and DeepSeek answersLearn more ›
We build a brand-fact system that AI assistants can recognise, trust, recommend and verify — and turn the decision-stage demand AI generates into traceable leads, opportunities, projects and long-term customer value.
Grade the buying questions your customers ask AI into S/A/B/C tiers and bind each to target facts and a landing page.
Sample across multiple AIs with API and in-app results kept separate: who gets recommended, who gets cited, what is wrong.
Produce content only for gaps with commercial value; every number is bound to a verified fact and its evidence.
Attribute leads to the specific AI and piece of content; quotes, contracts, delivery and acceptance become new evidence.
Twelve stages map to twelve modules in the system (M01–M12); each stage's output is the next stage's input, and every stage has acceptance criteria.
Every tier states its deliverables and acceptance criteria. We do not sell "guaranteed rankings" — only verifiable fact-building, monitoring, content, conversion and the business loop.
Baseline of 60–100 buying questions, sampling across 4+ AI platforms (API and in-app separated), competitor / source / fact-error inventory, 90-day roadmap.
Brand-fact building, content production and approval, publishing on your website and authorised channels, scheduled re-testing, landing pages with lead attribution, monthly report.
Private cloud / dedicated instance: knowledge base, AI service and sales assistants, CRM, quoting and contracts, project delivery, case-evidence flywheel.
Monthly monitoring, content refresh, optimisation experiments, customer reports, lead reviews, service allowance.
Indicative price ranges; final pricing depends on question count, platforms, sampling frequency, content volume, channels, customer authorisation, integrations and service level. Formal quotations are issued in writing.
The above is us doing the work for you. To subscribe and run the system yourself (corpus center included), see MianxiangAI GEO Growth Cloud.
| Deliverable | AI Brand Visibility Audit | 90-Day AI Growth Program | Enterprise AI Growth & Sales System | Ongoing Operations |
|---|---|---|---|---|
| Question library & multi-AI baseline | ✓ | ✓ | ✓ | ✓ |
| Competitor, source & fact-error inventory | ✓ | ✓ | ✓ | ✓ |
| Fact cards & evidence library | — | ✓ | ✓ | ✓ |
| Brief → fact-check → approval → publish | — | ✓ | ✓ | ✓ |
| Scheduled re-tests & experiments | — | ✓ | ✓ | ✓ |
| Landing pages, forms & attribution | — | ✓ | ✓ | — |
| CRM, 3-tier quotes, contracts | — | — | ✓ | — |
| Knowledge base, AI service & sales assistants | — | — | ✓ | — |
| Private cloud / dedicated instance | — | — | ✓ | — |
| Monthly monitoring, refresh & reporting | — | ✓ | ✓ | ✓ |
| Customer portal & service allowance | — | — | ✓ | ✓ |
How we measure, what we track and how we attribute are written into the contract and the system — and so are the things we will not promise or do.
Book an auditSame question set, fixed sampling conditions, repeated across time windows; API sampling and in-app tests are always reported separately; every number drills down to the underlying observation and evidence.
Question coverage, brand mention rate, explicit recommendation rate, owned/authorised-source citation rate, fact accuracy, high-intent coverage, AI share of voice, AI-attributed leads and deals, evidence rate. No "impressions".
Three confidence tiers from landing params / referrer / UTM, plus form self-report and manual confirmation. "Possible" leads are excluded from AI figures; unknown leads are never forced into AI.
Question coverage, sampling frequency and method, content volume and evidence quality, lead handling and attribution rules, report completeness — every item is acceptable and auditable.
"Guaranteed Doubao ranking / guaranteed recommendation / guaranteed #1". AI answers vary by platform, time and randomness; anyone promising otherwise is betting you will never re-test.
Automating consumer AI accounts, bypassing CAPTCHAs, scraping consumer pages at scale, fake reviews, fabricated media, hiding AI-generated labels.
MianxiangAI is operated by Shanghai Paixu Network Technology Co., Ltd., a company registered in Shanghai in September 2011, with unified social credit code 9131011658212749XB. It holds two registered software copyrights covering the MxJSON business description language and its protocol execution engine. Company facts are published at /en/facts with their sources. Read more →
The trial is free for 14 days, with no payment method and no automatic charge. It covers 20 buying questions and API sampling on 2 AI platforms, one round a week. On day 7 you get a visibility baseline and gap list: how often you are named, how you are described, what is stated incorrectly, and where the gaps are. Fact cards and the corpus center are read-only during the trial. Read more →
Every change is measured by a matched re-test: same questions, same platforms, same sampling windows, one variable at a time. Citations count only on an exact normalised-URL match; domain-level resemblance does not count. Rounds that moved nothing are recorded as such. Read more →
That is the case we are set up for. Chinese assistants draw on Chinese-language sources that most foreign sites never produce, so the work is establishing a verifiable Chinese-language fact layer about your company and publishing it where those crawlers actually read. Filing, hosting and platform-account requirements differ by channel and we scope those before quoting. Read more →
Usually one of three things: there is nothing machine-readable about you online; there is content but it sits where crawlers cannot reach it; or there is content that contradicts itself, so the model cannot settle on a claim. The three need different fixes, so we run a baseline sample before changing anything. Read more →
Turn the questions your buyers actually ask into a question set, then ask them repeatedly across assistants at different times of day and record each answer: whether you were named, how you were described, and which pages were cited. A single result proves nothing; repeated sampling is the data. Read more →
SEO optimises where you rank in a list of links. GEO optimises what an assistant says when someone asks a question and reads one answer instead of ten results. Assistants lean on structured, verifiable, attributable facts rather than keyword placement. MianxiangAI works on the second: it turns company facts into citable form and re-tests the answers across 12 AI entry points, including Doubao, DeepSeek and ChatGPT. Read more →
Only facts you have cleared for public use enter the corpus; unapproved material is not used for generation. Every model call is logged, and sensitive fields are masked by rule before a request leaves. Role permissions, tenant isolation and operation auditing are configured as part of delivery. Read more →
Baseline report and 90-day roadmap within two weeks.