by SponsorLens (LX AI)
SponsorLens — Know if a brand deal is fair before you sign. Use it as decision-support: demo mode works without a live key; live runs require configuration. No fabricated metrics, and no claims for SSO/CSV/Slack unless that surface is actually shipped.
Decision-support only — confirm before you publish or act.
I built SponsorLens to take the raw details you have about a brand deal and turn them into a quick sanity check. You start by entering the offered compensation, the list of deliverables, the platform where the content will appear, and the size of the audience you expect to reach. Those four inputs are the minimum the model needs to produce a useful output.
When you submit the form the system first checks that each field has a sensible value. Empty fields or obviously impossible numbers trigger a warning asking you to review the entry. This prevents garbage‑in garbage‑out situations.
The core of the engine looks at publicly available rate information for similar creator profiles. It pulls from aggregated industry surveys, platform‑specific creator reports, and anonymized deal data that users have opted to share. The model then adjusts the base rate for the specific mix of deliverables you entered. For example, a video command usually carries a higher weight than a static image post.
Parallel to the rate check the system scans the wording you plan to use for the sponsorship. It compares your planned disclosure language against the FTC endorsement guides and the OWASP Top 10 for LLM Applications to spot phrases that could be deemed insufficient. The scan does not read your mind; it only works with the text you provide.
Demo mode lets you explore the interface without configuring any external keys. I added this so you can see the layout, try sample inputs, and understand what the outputs look like before you decide to connect a live provider.
The demo runs entirely in the browser. No data leaves your machine, and no external API is called. This makes it safe to experiment with any numbers you want.
Using these placeholders the demo returns a benchmark range and a disclosure checklist. The numbers are illustrative only; they are not tied to any real market data.
Because demo mode does not contact a live model the output cannot be trusted for actual negotiations. It is meant to show you the shape of the result, not to give you a decision you can act on. When you are ready to rely on the output you must switch to live mode and provide a valid API key.
Live mode connects SponsorLens to a language‑model endpoint that performs the benchmark and disclosure checks. You need to supply an API key from a provider that offers the specific model version we support.
The key is stored only in your local browser storage unless you have opted into sync across devices. We never send it to our servers.
If you are concerned about sharing sensitive deal terms you can run the analysis on a sandbox account first.
Each live call consumes tokens from your provider’s quota. I recommend monitoring your usage dashboard to avoid unexpected charges. The demo mode remains free because it makes no external calls.
Understanding how the benchmark is derived helps you judge whether the output fits your context. I will walk through the data sources, the adjustment logic, and how to read the final numbers.
These sources are refreshed quarterly. The model weights each source by its recency and sample size.
You can see the exact weights applied by expanding the “Show calculation” link after a live run.
The benchmark appears as a range: low‑end, median, and high‑end. The low‑end reflects the floor for similar deals given conservative assumptions. The median represents the typical market rate. The high‑end shows what top‑tier creators with strong engagement might secure.
If the offered amount falls below the low‑end you have a strong signal to ask for more. If it sits above the high‑end you may want to verify that the brand is not overpaying for low‑engagement content.
| Output label | What it means | How to use it |
|---|---|---|
| Low‑end | Conservative estimate based on lowest observed rates | Use as a floor for negotiation |
| Median | Mid‑point of the observed market | Target this if you have average use |
| High‑end | Upper bound from top‑quartile deals | Aim for this only if you have exclusivity or premium reach |
The disclosure check looks at the wording you plan to place near the sponsored content. It does not guarantee compliance; it only highlights common pitfalls.
The check is built around the FTC’s “clear and conspicuous” standard. It looks for phrases that are ambiguous, hidden, or use unfamiliar abbreviations.
After you adjust the wording you can rerun the check to see if the flags disappear.
For creators who work repeatedly with brands I added a simple rate‑card tool. Agencies can also view a team‑level dashboard to monitor multiple creators.
The builder does not pull live market data; it uses the numbers you provide as a starting point.
Access to the dashboard requires that each team member has a live API key configured in their personal settings.
I want to be clear about the limits of SponsorLens so you do not rely on it for things it cannot do.
The tool gives decision‑support only. It does not promise that a deal will succeed, that a brand will pay, or that a disclosure will pass regulatory review. You must still apply your own judgment.
If you need a contract reviewed, or you are unsure about exclusivity terms, payment schedules, or liability clauses, you should consult a qualified attorney. SponsorLens does not draft or interpret legal language.
The product does not generate agreements, manage signatures, or store executed contracts. It focuses on the pre‑sign evaluation of fairness and disclosure risk.
Each social network has its own rules about branded content. SponsorLens does not know those rules; you must check the platform’s help center separately.
Know if a brand deal is fair before you sign.
Operators and builders who need a fast first draft or checklist from SponsorLens.
Yes in explicit Demo mode. Live AI requires a configured key.
No. Outputs are decision-support; you still review before publishing or acting.
Only if those features are implemented in this product build — do not assume them from marketing copy.
Runs may be stored locally under the product's .data/ boundary; treat demos as ephemeral.