Bring the Power of Gen AI to Enterprise Apps

No coding Required

Quickly launch generative AI and AI-agent use cases like semantic search, customer support automation, and more, directly within Salesforce, Oracle Siebel CRM, and your enterprise apps.

Supported Use Cases

Generative AI can deliver value to companies in a wide variety of ways. To simplify the landscape, we categorize use cases based on their implementation approach. There are three main categories - each supported by Magnet AI:

Prompt-driven

The most fundamental way to extract value from a Large Language Model (LLM).

Quickly automate routine tasks like translation, summarization, categorization, sentiment analysis, and generating content such as emails.

Vector Embeddings

Turn company knowledge into vector embeddings to enable semantic search and RAG.

Improve search accuracy over semantically similar records or documents and ground LLM responses in your own data and knowledge.

AI Agents

Provide a task and the available tools, and let the LLM determine the steps for the agent to solve it.

Streamline complex customer interactions and internal workflows by empowering AI agents to act on users' behalf.

Connect to your LLM, knowledge sources, and applications. Configure prompt templates, RAG tools, and agents. This phase resembles traditional software implementation and is familiar to teams used to deterministic systems.

Magnet AI: Connect & Configure

It's like traditional testing, but test cases require 50x more data combinations. Run evaluations, analyze results, refine prompts, tool descriptions, and other settings. Repeat the cycle until you reach an acceptable level of accuracy.

Magnet AI: Run Evaluations

A simple post-go-live "smoke test" isn't enough. The real work begins when your AI hits the real world. Analyze responses, track user feedback, monitor costs, and refine your setup following the configuration and evaluation cycle.

Magnet AI: Analyze Usage

Bring the Power of Gen AI to Enterprise Apps

No coding Required Quickly launch generative AI and AI-agent use cases like semantic search, customer support automation, and more, directly within Salesforce, Oracle Siebel CRM, and your enterprise apps.

Who is Magnet AI for?

Magnet AI is for CRM consultants and application experts who understand the potential of Generative AI but aren't AI engineers. Our free, open-source, low-code platform lets you rapidly create AI-powered features—no Python needed.

Supported Use Cases

Generative AI can deliver value to companies in a wide variety of ways. To simplify the landscape, we categorize use cases based on their implementation approach. There are three main categories - each supported by Magnet AI:

Prompt-driven

The most fundamental way to extract value from a Large Language Model (LLM). Quickly automate routine tasks like translation, summarization, categorization, sentiment analysis, and generating content such as emails.

Vector Embeddings

Turn company knowledge into vector embeddings to enable semantic search and RAG. Improve search accuracy over semantically similar records or documents and ground LLM responses in your own data and knowledge.

AI Agents

Provide a task and the available tools, and let the LLM determine the steps for the agent to solve it. Streamline complex customer interactions and internal workflows by empowering AI agents to act on users' behalf.

Functionality for the Entire Lifecycle

Traditional software is deterministic - it follows defined algorithms and produces consistent results. In contrast, Gen AI and AI Agents are probabilistic. Magnet AI provides you with the tools to roll out use cases in this new paradigm confidently.

Traditional software is deterministic - it follows defined algorithms and produces consistent results. In contrast, Gen AI and AI Agents are probabilistic. Magnet AI provides you with the tools to roll out use cases in this new paradigm confidently.

3 Ways to Integrate Magnet AI into Your Business Application

Integrate Magnet AI into your existing business applications in a way that fits your team's needs - simplifying deployment and accelerating time-to-value.

Giving You Choice and Control

Generative AI is a dynamic space with more efficient LLMs emerging every month. While leading LLM providers have largely addressed concerns around data trust and security, it remains essential for companies to retain control over application logs and analytics.

How can I deploy Magnet AI?

You can deploy Magnet AI (three containers and a database) on the cloud of your choice or on-premises.

Is Magnet AI tied to a specific LLM provider, or can it work with different models?

Magnet AI is an LLM provider agnostic as long as the model supports structured output and tool calling.

How does Magnet AI handle logging and analytics?

All application logs are stored locally in the Magnet AI, providing insight into usage, accuracy, cost, and latency.

How is Magnet AI adapting to new standards for connecting tools and agents?

Emerging standards like MCP and A2A are streamlining tools and agent integration - Magnet AI support is coming soon.

Ideaport Magnet AI Services

Premium Support with several options

On-demand expert services

Use case discovery workshops

Free Proof-of-Concept projects

Magnet AI onboarding

Integration with custom knowledge sources

Use case implementation

Optimizing accuracy and costs

Who is involved in Magnet AI development?

Magnet AI is a free, open-source solution promoted and maintained by

a group of end customers, implementation partners and IT enthusiasts:

Book a Call with Us

Discover more of Magnet AI in action We welcome CRM admins to join Magnet AI Workshop to explore its features and get access to admin area.

Knowledge Base

Explore our Knowledge Base to discover more about how Magnet AI operates

Darzciema Street 91, Riga, Latvia, LV-1073

No coding Required

Quickly launch generative AI and AI-agent use cases like semantic search, customer support automation, and more, directly within Salesforce, Oracle Siebel CRM, and your enterprise apps.

The most fundamental way to extract value from a Large Language Model (LLM).

Quickly automate routine tasks like translation, summarization, categorization, sentiment analysis, and generating content such as emails.

Turn company knowledge into vector embeddings to enable semantic search and RAG.

Improve search accuracy over semantically similar records or documents and ground LLM responses in your own data and knowledge.

Provide a task and the available tools, and let the LLM determine the steps for the agent to solve it.

Streamline complex customer interactions and internal workflows by empowering AI agents to act on users' behalf.

Discover more of Magnet AI in action

We welcome CRM admins to join Magnet AI Workshop to explore its features and get access to admin area.