Consensus est un moteur de recherche alimenté par l'IA, conçu pour la recherche scientifique. Il parcourt plus de 200 millions d'articles évalués par des pairs pour fournir des réponses synthétisées et fondées sur des preuves aux questions des utilisateurs, faisant gagner du temps aux chercheurs, étudiants et professionnels en extrayant les principales conclusions directement de la littérature scientifique.
STORM est un prototype de recherche en IA de l'Université de Stanford qui automatise la génération de rapports complets, de type Wikipédia, sur n'importe quel sujet. Il prend en charge la curation interactive des connaissances, permettant aux utilisateurs de guider le processus de recherche, de modifier les plans et de produire efficacement des articles bien structurés et cités.
Aperçu du produit
Consensus Aperçu du produit
Consensus est un moteur de recherche alimenté par l'IA, conçu pour la recherche scientifique. Il parcourt plus de 200 millions d'articles évalués par des pairs pour fournir des réponses synthétisées et fondées sur des preuves aux questions des utilisateurs, faisant gagner du temps aux chercheurs, étudiants et professionnels en extrayant les principales conclusions directement de la littérature scientifique.
STORM Aperçu du produit
STORM est un prototype de recherche en IA de l'Université de Stanford qui automatise la génération de rapports complets, de type Wikipédia, sur n'importe quel sujet. Il prend en charge la curation interactive des connaissances, permettant aux utilisateurs de guider le processus de recherche, de modifier les plans et de produire efficacement des articles bien structurés et cités.
Detailed feature comparison
| Feature | Consensus | STORM |
|---|---|---|
| Catégorie principale | Apprentissage | Apprentissage |
| Ajouté | 2025-08-10 | 2025-08-15 |
| Tarification | Freemium | Gratuit |
| Site officiel | consensus.app | storm.genie.stanford.edu |
| Type de produit | Site web | Site web |
| Performance data | ||
| Note utilisateur | Non vérifié | Non vérifié |
| Commentaires | 0 | 0 |
| Visites mensuelles | 5.7M | 4.2K |
| Croissance mensuelle | -2.5% | Non vérifié |
| Favoris | 98 | 128 |
| Details | Voir les détails | Voir les détails |
Consensus vs STORM monthly traffic
Compare Consensus and STORM by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Consensus vs STORM monthly traffic comparison, Consensus currently shows 5.7M visits and STORM shows 4.2K; Consensus has about 1,375.7 times the visible traffic of STORM, an absolute difference of about 5.7M visits. This reflects visible reach, not feature quality or paid users.
Only Consensus has complete third-party traffic details; STORM uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
Consensus monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 3.5M Visites mensuelles
- 2026/1: 3.9M Visites mensuelles
- 2026/2: 4M Visites mensuelles
- 2026/3: 5.1M Visites mensuelles
- 2026/4: 5.9M Visites mensuelles
- 2026/5: 5.7M Visites mensuelles
Principales régions
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇮🇩Indonesia | 35.36% | 2M |
| 🇺🇸United States | 29.41% | 1.7M |
| 🇵🇪Peru | 12.81% | 735.4K |
| 🇮🇳India | 11.61% | 666.5K |
| 🇩🇪Germany | 10.81% | 620.6K |
Sources de trafic
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 85.92% | 4.9M |
| Référence | 12.3% | 706.1K |
| 1.78% | 102.2K |
Mots-clés
STORM monthly traffic:
Latest traffic
Usage comparison
Compare the core capabilities of Consensus and STORM
Consensus Core features
STORM Core features
Use cases
Consensus Use cases
STORM Use cases
Consensus vs STORM:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Consensus vs STORM comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Consensus is primarily listed under “Apprentissage”, while STORM is primarily listed under “Apprentissage”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Pricing (Consensus: Freemium; STORM: Free); Monthly visits (Consensus: 5.7M; STORM: 4.2K); Favorites (Consensus: 98; STORM: 128); Website (Consensus: consensus.app; STORM: storm.genie.stanford.edu); Added (Consensus: 2025-08-10; STORM: 2025-08-15). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Consensus vs STORM monthly traffic comparison, Consensus currently shows 5.7M visits and STORM shows 4.2K; Consensus has about 1,375.7 times the visible traffic of STORM, an absolute difference of about 5.7M visits. This reflects visible reach, not feature quality or paid users.
Only Consensus has complete third-party traffic details; STORM uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Product positioning, use cases, and roles
Consensus and STORM currently overlap in shared categories: Apprentissage; shared tags: revue de la littérature et Recherche. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Consensus's unique categories/tags are Médecine, Écriture, Revue de Littérature, Recherche académique, Moteur de recherche IA, analyse de données, fondé sur des preuves et vérification des faits; STORM's are Assistant d'écriture, Gestion des connaissances, Rédaction académique, Recherche automatisée, Création de contenu, Conservation des connaissances, Synthèse des connaissances et Génération de rapports. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
Consensus has no verified rating, 0 comments, 98 favorites, and 90 likes;STORM has no verified rating, 0 comments, 128 favorites, and 120 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Consensus first
Put Consensus on the priority trial list when the task aligns with “Apprentissage” and especially Médecine, Écriture, Revue de Littérature, Recherche académique, Moteur de recherche IA et analyse de données. This follows recorded positioning and does not imply unlisted capabilities are absent.
Consensus also currently records: pricing is freemium, product type is website, 5.7M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate STORM first
Put STORM on the priority trial list when the task aligns with “Apprentissage” and especially Assistant d'écriture, Gestion des connaissances, Rédaction académique, Recherche automatisée, Création de contenu et Conservation des connaissances. This follows recorded positioning and does not imply unlisted capabilities are absent.
STORM also currently records: pricing is free, product type is website, 4.2K on-site monthly views, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Consensus and STORM, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




