Agentic

Revolutionize game development with scalable, intuitive AI integration and insights.

Automation & Agents AI AgentsPaid

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About Agentic

Agentic is an innovative tool designed to revolutionize the way game developers interact with AI, making it simpler than ever to create and deploy AI agents that work seamlessly within the gaming environment. This platform is a game-changer for developers, offering a suite of AI-driven services that can perform tasks ranging from bug finding to providing live player support without needing a PhD in artificial intelligence. Tailored specifically for the gaming industry, Agentic simplifies complex AI deployment, offering non-toxic, balanced, and directable agents that can be deployed at any scale and anywhere, anytime. Key Features: AI Players As a Service: Agentic provides AI agents that can keep company to live players, ensuring they always have someone to compete with or against, enhancing the gaming experience. Data-Driven Insights: The tool offers deep insights into gameplay, helping developers understand how levels can be completed or which opponents are most lethal by playing the game at scale. Ease of Integration: With SDKs that natively support Unreal, Unity, and proprietary C++ engines, Agentic is made specifically for game development environments. Cloud-Based Training: Agents are trained in the cloud, which means there’s no need for additional hardware beyond what developers already use.

Key features

AI Players As a Service
Data-Driven Insights
Ease of Integration
Cloud-Based Training
Scalability
Developer-Friendly
Deep Insights
Open Source SDKs

Use cases

Game Developers: Utilizing the platform to enhance live player experiences and test game environments.
Quality Assurance Teams: Leveraging AI agents to automate the discovery of bugs and generate performance reports.
Indie Game Studios: Taking advantage of scalable AI players to simulate live environments without a large player base.

Pros

Simplifies AI agent deployment for game developers without requiring advanced AI expertise
Provides AI Players As a Service to enhance player engagement by offering AI opponents or companions
Offers data-driven insights into gameplay to inform level design and opponent behavior
Supports integration with major game engines like Unreal, Unity, and proprietary C++ engines via SDKs
Enables cloud-based agent training, reducing the need for additional hardware investment

Cons

Limited to gaming industry use cases, restricting broader applicability
Dependence on cloud-based training may introduce latency or connectivity requirements
Requires familiarity with game development environments for optimal integration

Frequently asked questions about Agentic

What does Agentic do?

Agentic provides AI-driven services for game developers to create, train, and deploy AI agents that operate within gaming environments. These agents can perform tasks such as bug detection, player support, and gameplay analysis.

Who is Agentic designed for?

Agentic is tailored specifically for game developers and studios looking to integrate AI agents into their games. It is suitable for teams of all sizes, from indie developers to large studios.

How do I integrate Agentic into my game engine?

Agentic offers SDKs that natively support popular game engines like Unreal, Unity, and proprietary C++ engines. The platform is designed for seamless integration into existing development workflows.

Can Agentic agents be deployed in live games?

Yes, Agentic agents can be deployed at any scale and operate in live gaming environments. They can interact with players, provide support, and enhance gameplay experiences in real time.

Does Agentic require additional hardware for training agents?

No, Agentic trains agents in the cloud, eliminating the need for developers to invest in additional hardware beyond their existing setups.

What kind of insights does Agentic provide about gameplay?

Agentic offers data-driven insights into gameplay, such as identifying how levels can be completed or which opponents are most challenging by analyzing agent performance at scale.