The Prisme.ai platform enables your organization to create custom AI agents that can be tailored to specific business needs, knowledge domains, and workflows. These agents leverage the power of large language models (LLMs) while incorporating your organization’s unique knowledge and requirements.

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What are Prisme.ai Agents?

Prisme.ai agents are specialized AI assistants that combine the capabilities of foundation models with your organization’s:

  • Knowledge and expertise: Documents, processes, procedures
  • Data sources: Databases, APIs, knowledge bases
  • Business context: Industry-specific terminology and workflows
  • Security requirements: Enterprise-grade access controls and governance

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Agent Types

Simple Prompting

Basic agents powered by foundation models with specialized instructions

RAG Agents

Agents that access organizational knowledge through Retrieval Augmented Generation

Tool-Using Agents

Agents that can use specialized tools to perform complex tasks

Multi-Agent Systems

Collaborative systems with multiple specialized agents working together

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Agent Creation Process

Creating effective enterprise agents involves several key steps:

1

Define the Agent's Purpose

Clearly articulate what problem the agent will solve, who will use it, and what capabilities it needs.

Key questions to answer:

  • What specific tasks will the agent perform?
  • Who are the primary users?
  • What knowledge or data sources does it need access to?
  • What security or compliance requirements apply?
2

Select the Agent Type

Choose the appropriate agent architecture based on your requirements.

Selection criteria:

  • Simple prompting for basic Q&A and standardized responses
  • RAG for knowledge-intensive applications
  • Tool-using agents for integration with systems and services
  • Multi-agent systems for complex workflows requiring multiple capabilities
3

Configure Knowledge and Tools

Connect the agent to relevant data sources, knowledge bases, and tools.

Configuration options:

  • Knowledge base connections
  • Tool integrations
  • API access
  • Data source connections
4

Test and Refine

Validate the agent’s performance and iteratively improve its capabilities.

Testing approaches:

  • Sample queries
  • User scenarios
  • Edge case validation
  • Continuous feedback incorporation
5

Deploy and Monitor

Make the agent available to users and track its performance.

Deployment considerations:

  • Access controls
  • Usage monitoring
  • Performance analytics
  • Ongoing maintenance

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Agent Creation Platforms

Prisme.ai offers multiple ways to create and manage agents, depending on your technical expertise and requirements:

AI Store

No-code interface for creating and deploying specialized agents

AI Knowledge

No-code platform for creating knowledge-powered agents with RAG capabilities

AI Builder

Low-code and code-based environment for creating advanced, custom agents

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Security and Governance

All agents created on the Prisme.ai platform inherit enterprise-grade security features:

  • Access controls: Comprehensive RBAC (Role-Based Access Control)
  • Audit logging: Detailed tracking of agent creation and usage
  • Data privacy: Secure handling of sensitive information
  • Compliance: Support for regulatory requirements
  • Governance: Centralized management of agent deployments

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Next Steps

Ready to create your first agent? Choose your agent type to get started:

Simple Prompting

Get started with basic agents powered by specialized instructions

RAG Agents

Create agents that leverage your organization’s knowledge

Tool-Using Agents

Build agents that can use tools to perform complex tasks

Multi-Agent Systems

Develop collaborative systems with multiple specialized agents

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