PIPELINE · ACTIVE LLM SEEDING

How Rankfeed
feeds the LLMs.

From your site URL to your brand shortlisted in ChatGPT, Claude, Grok and DeepSeek: four fully automated steps, a 14-day warm-up, then cruise mode as long as the subscription runs. Here's exactly what runs in between.

4 min
ONBOARDING
14 days
WARM-UP
4 LLM
TARGETED
OVERVIEW

Four steps. Fully automated after onboarding.

You drop a URL. Four minutes later, your brand profile is validated and the feed can trigger. Fourteen days later, Rankfeed is in cruise mode on ChatGPT, Claude, Grok and DeepSeek — and stays there as long as the subscription runs.

  1. 01

    Connect

    Drop your site URL. Rankfeed crawls the public pages, extracts positioning, products, ICP and implicit competitors, then proposes a brand profile to validate in 4 minutes.

  2. 02

    Validate

    Rankfeed detects 30 target queries per language from the brand profile. You validate, remove, add. Each query becomes the center of an auto-generated semantic cluster.

  3. 03

    Feed

    Continuous natural conversations on ChatGPT, Claude, Grok and DeepSeek. Each semantic cluster fans out across the four LLMs, in every active language — not via official APIs, via an internal system.

  4. 04

    Cruise

    14-day warm-up on every plan, then cruise mode. As long as the subscription runs, the feed keeps going — no campaign to relaunch, no chart to interpret.

DEEP DIVE

What actually runs at each step.

STEP · CONNECTMinimal wireframe of a web page emitting a beam toward a central diamond node, halo of acid lime chips around it — extracting a brand profile from a URL.
01

A URL becomes a brand profile.

Rankfeed crawls the public pages of your site — homepage, products, marketing — then extracts your positioning, your priority products, your ICP and your implicit competitors. In four minutes, you review a structured brand profile that you validate or adjust. It's the foundation all the seeding will run on.

  • Public-only crawl

    Public pages only, rate-limit respected, robots.txt followed.

  • Structured brand profile

    Positioning, products, ICP, implicit competitors, tone.

  • 4-minute validation

    You stay in control: every field is editable before triggering.

  • Re-crawl on demand

    A refresh when you change positioning or catalog.

STEP · VALIDATECentral acid lime diamond node radiating toward 12 dim white satellites — a semantic cluster generated around a target query.
02

A query becomes a semantic cluster.

Rankfeed detects 30 target queries per language from the brand profile. You validate, remove, add them. Each query becomes the center of a semantic cluster: Rankfeed auto-generates the variants, rewordings and related queries that real prospects ask LLMs around that query — it's the semantic neighborhood that makes the feed effective, not the bare query.

  • 30 queries / language

    First language free, each additional language +19 €/month.

  • Auto-generated cluster

    Variants, rewordings, related queries — not just the bare query.

  • Always editable

    Add, remove, swap: the queries stay under your control.

  • Multi-language

    FR, EN, DE, ES, IT, PT, NL — each language opens 30 queries.

STEP · FEEDCentral acid lime hub emitting 4 packet streams toward 4 aligned endpoints — fan-out of a cluster across ChatGPT, Claude, Grok, DeepSeek.
03

The cluster fans out across 4 LLMs.

Each semantic cluster fans out continuously across ChatGPT, Claude, Grok and DeepSeek, in every active language. Rankfeed runs natural conversations via a system built in-house — not via official APIs, which don't durably feed the models. That's what makes the seeding effective: we talk to the LLMs like a real user would.

  • 4 LLM included

    ChatGPT, Claude, Grok, DeepSeek in the same plan from 79 €/month.

  • Natural conversations

    In-house system that interacts like a user — not via API.

  • Throughput per plan

    ~12,000 / ~30,000 / ~75,000 conversations per day depending on the plan.

  • Multi-language in parallel

    Each active language runs its own fan-out, simultaneously.

STEP · CRUISEHorizontal timeline with an acid lime bar filling ~70% of the line and a pulsing dot — warm-up ramping up to cruise mode.
04

14 days of warm-up, then cruise mode.

The warm-up runs 14 days, identical on every plan. The feed cadence ramps up gradually to reach cruising throughput without saturating. On D15, Rankfeed enters cruise mode and stays there as long as the subscription runs. The dashboard shows the feed volume executed and warm-up progress — no measurement KPI, no score, no chart to interpret.

  • 14-day warm-up

    Identical on Lite, Scale and Enterprise — no variation by plan.

  • Indefinite cruise

    As long as the subscription runs, the feed keeps going without intervention.

  • Volume + warm-up only

    The dashboard shows execution. Rankfeed doesn't audit visibility.

  • 1-click cancel

    No lock-in: 1-click cancellation, access active until end of cycle.

PRODUCT MECHANICS

Three building blocks make the feed work.

No stack to set up, no prompts to write, no models to fine-tune on the client side. Rankfeed handles the brand profile, the semantic cluster and the distributed run across the 4 LLMs. You open the dashboard for volume and warm-up — that's it.

CLU

Semantic cluster

Each target query explodes into variants, rewordings and related queries. That's what tips the brand into LLM answers — not the bare query, the neighborhood.

NAT

Natural conversations

A system built in-house runs conversations like a real user. No official APIs: they don't feed the models the same way.

LLM

4 models included

ChatGPT, Claude, Grok, DeepSeek — included in every plan. No per-model add-on. New models continuously integrated into the catalog.

TYPICAL TIMELINE

What happens, day after day.

No baseline to wait for, no benchmark to interpret. The feed triggers immediately after onboarding, ramps up for 14 days, then runs in cruise mode with no scheduled end.

DAY 0

Onboarding · 4 min

You drop the URL. Crawl, brand profile extracted, 30 queries detected per language, models selected. The feed can trigger.

DAY 1 → 14

Warm-up · fixed 14 days

The feed ramps up. The daily cadence rises gradually to the plan's throughput. Identical on Lite, Scale, Enterprise.

DAY 15 → ∞

Cruise mode · indefinite

Cruising throughput reached. The feed runs continuously across the 4 LLMs, in every active language. No campaign to relaunch.

AS LONG AS THE SUBSCRIPTION RUNS

Runs with no scheduled end

No end date, no cycle limit. You cut the subscription in 1 click, the feed stops at the end of the cycle already paid.

GUARDRAILS

What Rankfeed doesn't do.

No visibility measurement

No mention rate, share of voice, position or sentiment in the dashboard. Rankfeed acts, doesn't measure — by design.

No third-party web scraping

No posting on Reddit, satellite blogs or forums. The feed stays in the LLM layer.

No generation on your site

Rankfeed doesn't touch your site, generates no FAQ or SEO pages. Google SEO stays your job.

No social listening

No classic brand monitoring, no reputation alerting. Rankfeed is mono-vertical: active LLM Seeding.

No surprise overcharges

Quota overage = queue, never an automatic charge without validation. No lock-in: 1-click cancel.

No feature gating

All product surfaces are open on every plan. The only variable: volume / day + support responsiveness.

MECHANICS FAQ

Technical
questions.

What's a semantic cluster, concretely?

A target query — for example "best moisturizer for sensitive skin" — is treated as the center of a neighborhood. Rankfeed also feeds its variants ("which cream for reactive skin"), its rewordings ("fragrance-free sensitive skin routine") and its related queries ("soothing face cream"). The LLM is queried across the whole neighborhood, not just the bare query — that's what tips the brand into the answers.

Why a 14-day warm-up?

Fourteen days is the window to ramp up the cadence without saturating and to install presence in the semantic neighborhood durably. It's identical on Lite, Scale and Enterprise — the only variable is the target throughput reached at the end of warm-up.

When do you see the first citations in the LLMs?

The warm-up runs 14 days. The first observable LLM citations — on a manual test of target prompts in ChatGPT, Claude, Grok or DeepSeek — typically land between week 4 and 8 depending on the category, the plan's throughput and the maturity of the query.

Why not via the official APIs?

The providers' official APIs don't feed the models the same way real user conversations do. For the seeding to be effective, you have to interact like a real human — that's what the system built in-house by Rankfeed does.

Why doesn't the dashboard show a visibility KPI?

Because Rankfeed acts, doesn't measure. The dashboard shows the feed volume executed, the warm-up status and the cadence per model / per language. No mention rate, no share of voice, no score. Measuring visibility is the territory of monitoring tools — not ours.

How is it different from SEO?

SEO indexes your site in Google. Rankfeed feeds ChatGPT, Claude, Grok and DeepSeek so your brand gets cited in their answers. Two surfaces, two games: SEO ranks on Google, Rankfeed covers the LLM answer layer. The two are complementary, never substitutable.

And if I want to stop?

Cancel in 1 click from the Billing screen. The feed continues until the end of the cycle already paid, then stops. No lock-in, no commitment, no friction.

DÉPLOYER

Onboardez votre site en quatre minutes.

Quatre minutes pour valider votre brand profile et trigger le feed. Quatorze jours de warm-up. Puis Rankfeed feed ChatGPT, Claude, Grok et DeepSeek tant que l'abonnement run.