diff --git a/programs/summerofcode/2025.md b/programs/summerofcode/2025.md
index 7e13eed9..31df983b 100644
--- a/programs/summerofcode/2025.md
+++ b/programs/summerofcode/2025.md
@@ -243,6 +243,39 @@ Note that the initial idea is to solve this with **3-way Git merges**. However,
   - Sarthak Jain (@SarthakJain26, sarthak.jain@harness.io)
 - Upstream Issue (URL): https://github.com/litmuschaos/litmus/issues/5042 
 
+#### Meshery
+
+##### Multi-player Collaboration: Resilient Websockets and GraphQL Subscriptions
+
+Meshery's current implementation of websockets and GraphQL subscriptions is in need of refactoring for increased reliability and resiliency. This client and server-side refactoring includes use of webworkers and separation of concerns for the client-side, and the use of a message broker for the server-side. The project has implications on Meshery's implementation of multi-player collaboration functionality.
+
+- Expected Outcome: Resilient websockets and GraphQL subscriptions for Meshery, enabling multi-player collaboration functionality.
+- Recommended Skills: Golang, Kubernetes, Azure, well-written and well-spoken English
+- Expected project size: large (~175 hour project)
+- Mentor(s): Lee Calcote (@leecalcote, leecalcote@gmail.com), Aabid Sofi (@aabidsofi19, mailtoaabid01@gmail.com)
+- Upstream Issue: https://github.com/meshery/meshery/issues/13554
+
+#### Support for Azure in Meshery
+
+- Description: Enhance Meshery's existing orchestration capabilities to include support for Azure.  The [Azure Service Operator](https://azure.github.io/azure-service-operator/)Azure Service Operator (ASO) provides a wide variety of Azure Resources via Kubernetes custom resources.
+as first-class [Meshery Models](https://docs.meshery.io/concepts/logical/models). This involves enabling Meshery to manage and orchestrate Azure services and their resources, similar to how it handles other Kubernetes resources.  The project will also include generating support for Azure services and their resources in Meshery's Model generator.
+
+- Expected Outcome:  Meshery will be able to orchestrate and manage all Azure services supported by ASO. This includes the ability to discover, configure, deploy, and operate the lifecycle of Azure services through Meshery.  The Meshery Model generator will be updated to automatically generate models for Azure services, simplifying their integration and management within Meshery. This will be an officially supported feature of Meshery.
+- Recommended Skills: Golang, Kubernetes, Azure, well-written and well-spoken English
+- Expected project size: large (~175 hour project)
+- Mentor(s): Lee Calcote (@leecalcote, leecalcote@gmail.com), Mia Grenell (@miacycle, mia.grenell2337@gmail.com)
+- Upstream Issue: https://github.com/meshery/meshery/issues/11244
+
+#### Distributed client-side inference (policy evaluation) with WebAssembly (WASM) and OPA in Meshery
+
+- Description: Meshery's highly dynamic infrastructure configuration capabilities require real-time evaluation of complex policies. Policies of various types and with a high number of parameters need to be evaluted client-side. With policies expressed in Rego, the goal of this project is to incorporate use of the https://github.com/open-policy-agent/golang-opa-wasm project into Meshery UI, so that a powerful, real-time user experience is possible.
+
+- Expected Outcome:  The goal of this project is to enhance Meshery's infrastructure configuration capabilities by incorporating real-time policy evaluation using the golang-opa-wasm project. This project will integrate the capabilities of golang-opa-wasm into the Meshery UI, enabling users to experience the existing, powerful, server-side policy evaluation client-side.
+- Recommended Skills: WebAssembly, Golang, Open Policy Agent, well-written and well-spoken English
+- Expected project size: large (~175 hour project)
+- Mentor(s): Lee Calcote (@leecalcote, leecalcote@gmail.com), James Horton (@hortison, james.horton2337@gmail.com)
+- Upstream Issue: https://github.com/meshery/meshery/issues/13555
+
 #### Open Cluster Management
 
 ##### Privacy-preserving and efficient AI model training across multi-cluster