Why Trouver exists

As someone who eats out often, I became frustrated with how much restaurant information is available, yet how difficult it is to actually use in a precise way. Most systems mix too many signals together, making it hard to isolate what you actually care about.

What is fundamentally broken about typical restaurant discovery

Sponsored placement distorts visibility, making it harder to find the most relevant options. When ranking is influenced by payment rather than fit, search stops being neutral.
Single aggregate ratings collapse many dimensions into one number. A restaurant might have great food but poor service, or the reverse. One score hides that structure.
Unstructured reviews introduce noise and inconsistency. One-off experiences or irrelevant context can disproportionately shape perception.
Filtering is often too weak to be useful. Instead of expressing exactly what you want, you end up manually scanning and mentally filtering results.
Most importantly, restaurant search is usually built around blended impressions instead of intent. You are forced to interpret results after the fact, rather than define your criteria beforehand.

Trouver is built to reverse that structure.

What Trouver does today

-Search by specific qualities, not blended impressions

Trouver lets you search directly on the dimensions that matter to you. Filter across taste, value, service, menu price, cuisine using a detailed taxonomy, dress code, healthy options, authenticity, noise level, and more.
Instead of browsing broadly and interpreting results yourself, you define exactly what you want, then retrieve matches that fit those conditions.

-Negative filtering

You can include qualities you want and exclude qualities you do not. For example, you can search for a pizza place that is not an Italian restaurant, or an Italian restaurant that is not focused on pizza.

-Discrete metrics instead of walls of text

Trouver converts experiences into structured signals across specific dimensions. You see outcomes such as good, OK, or bad for the attributes that matter, allowing faster and more consistent comparison.

-Scaled, multi-dimensional evaluation

Rather than collapsing everything into one blended score, Trouver presents ratings across multiple dimensions so you can see a restaurant’s strengths and weaknesses more clearly.

-Confidence and reliability signals

A restaurant with only a few reviews should not appear as reliable as one with hundreds. Trouver surfaces confidence levels so you can distinguish between stable signals and sparse data.

-Compare, review, and save configurations

Compare restaurants side by side, leave structured feedback tied only to dimensions you experienced, and save filter setups for reuse.

What we commit to

-No paid influence on visibility or ranking

Restaurant placement is determined strictly by relevance and fit to your selected criteria. Ranking and exposure are not for sale.

-Search defined by user intent

Trouver is designed so you can search by precise qualities alone, rather than rely on aggregated impressions. Each filter represents a direct dimension of choice, giving you control over discovery.

-A fairer review system over time

As usage grows, scoring will incorporate weighting and normalization to reduce manipulation and improve stability. Review influence will account for factors such as account age, review volume, and scoring consistency.