docs: update descriptions

data/projects/mpc-stats.ts

@@ -11,11 +11,10 @@ export const mpcStats: ProjectInterface = {
       tldr: "A framework for private and verifiable statistical analysis across multiple data providers.",
       description: `
 ## Overview
-We are developing a framework that enables data consumers to query statistical computations across multiple data providers while ensuring privacy and result correctness. By integrating privacy-preserving technologies such as ZKP, MPC, and FHE, our goal is to provide tools and guidance for integrating privacy-preserving analysis into their workflows. We also aim to identify real-world applications that can benefit from this framework.
+MPCStats is a framework that enables data consumers to query statistical computations across multiple data providers while ensuring privacy and result correctness. By integrating privacy-preserving technologies such as ZKP, MPC, and FHE, our goal is to provide tools and guidance for integrating privacy-preserving analysis into their workflows. We also aim to identify real-world applications that can benefit from this framework.
 ## Features
 - **Privacy-preserving and verifiable statistical analysis**: Allows data providers to keep their inputs confidential while giving data consumers the assurance that computations are performed accurately and securely.
 - **Data validity**: Integrates TLSNotary to authenticate inputs from verified web sources, ensuring data consumers can trust that data inputs are genuine and accurate.
-- **Reusable demo infrastructure**: Enables rapid testing and feedback by deploying demos across various scenarios, allowing us to iterate quickly and refine potential applications.
 ## Use Cases
 - **Cross-department data sharing and surveys**: Enables secure, private data sharing across government departments for streamlined operations and collaborative analysis.
 - **Healthcare research**: Aggregates data from sources such as fitness apps and sleep trackers, allowing researchers to uncover relationships between health factors, such as fitness and sleep patterns.
@@ -30,7 +29,7 @@ We are developing a framework that enables data consumers to query statistical c
   tags: {
     keywords: ["MPC", "statistics", "data analysis"],
     themes: ["build"],
-    types: ["Legos/dev tools", "Lego sets/toolkits", "Infrastructure/protocol", "Plugin",],
+    types: ["Legos/dev tools", "Lego sets/toolkits"],
     builtWith: ["MP-SPDZ", "tlsn", "python"],
   },
 }