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The easiest way to get GenAI into your CRM

Bring Generative AI powers to your business users to enhance productivity, operational efficiency and customer satisfaction

Key Magnet AI Highlights

Magnet AI is a free and open-source solution deployed on your Azure instance that makes it simple

for CRM professionals to leverage GenAI capabilities with their CRM solutions. 

No-code configuration

Provides no-code configuration using Admin UI to build, test and access audit trail logs of the solution

Integration with CRM systems

Integrates with Oracle Siebel CRM, Salesforce, RightNow, ServiceNow and Fusion Applications

Knowledge access for Q&A

Answers questions using the knowledge from SharePoint, Confluence, Salesforce and RightNow

Key Features

Prompt Templates

Design, test, and make your LLM prompts accessible for your CRM.

Semantic Search

Connect your knowledge sources and monitor the Q&A flow usage.

AI mini-apps

Mix configuration and Python code to build task-specific mini-apps using agents.

API Access

Leverage REST API to bring prompts and semantic search into your CRM UI and background jobs.

AI Panels

Bring AI mini-apps into CRM UI to speed up task execution or help users with their questions.

Take a moment to see Magnet AI

in action

Sample Use Cases

Help users quickly find the answers on CRM functionality, business processes and products

Summarise information about a CRM record, highlighting critical information for a specific role 

Automate the routing of customers' requests by classifying its type and sentiment

Craft personalised emails to customers responding to a compelling event at the company or a customer

Run business rules against a set of CRM records and populate notes or send emails with findings

Streamline processing of customer inquiries from inbound text to calling the right APIs to a draft reply

Find semantically similar CRM records using free text fields, e.g., service request description

Improve the quality of various FAQs by analysing the types of questions customers and employees ask

Translate incoming and outgoing customer communication from and to foreign languages

Implementation Costs

Magnet AI

Magnet AI is a free and open-source solution deployed on your Azure instance

Free

€ 0

Azure Costs

Cost for running Azure resources as such Azure OpenAI, vector store, and container app

Starting From

€ 80/month

Initial Consulting

Quick wins use case identification and solution setup delivered by a Magnet AI Partner

Starting From

€ 1500

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:

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Let's explore what Magnet AI can do for you

Whether you work for the end customer or a consulting company, let's discuss how Magnet AI can benefit you.

Fill out the form, and we will get back to you within 24 hours.

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FAQ

Can Magnet AI be deployed in OCI, GCP, AWS, or the private cloud?

Currently, Magnet AI can be deployed only to the Microsoft Azure cloud. In the coming months, we will make it available first on OCI and then on another cloud platform, depending on the customer's interests. 

How do you integrate with a CRM system?

We integrate in two ways. First, the CRM system can invoke Magnet AI API, providing unstructured or JSON-formatted text as input and receiving the output as JSON. Second, Magnet AI Panel can be integrated into the hosting CRM UI natively or as an iFrame. When it comes to Magnet AI's mini-apps, they can read and update CRM data using standard REST services.

Does Azure OpenAI train on my data?

Azure OpenAI never trains its standard models on the data you pass to it via API. At the same time, the request and response data are stored in Azure for a certain period, and Microsoft employees can review this data to assess potential service abuse. Customers may request Microsoft not to store this data to achieve ZDR (Zero Data Retention). Read more about Azure OpenAI service data, privacy and security here.

Do you fine-tune foundational models?
No, we do not; so far, we have achieved our goals with prompt engineering. If you already have fine-tuned models in your Azure instance, you can leverage them in Magnet AI.
Do you support RAG?

Absolutely! On this webpage, we try to avoid technical terms such as RAG (retrieval augmented generation) and refer to it as Q&A flow or semantic search. While the RAG concept is very straightforward, there are various techniques to improve the results, and we are gradually implementing them in Magnet AI.

Can we develop custom AI mini-apps with specific functionalities unique to our business?
Yes, you can. While developing a specific AI mini-app requires custom coding, Admin UI can help you configure some parts (e.g., RAG and prompt template usage) and access the audit trail logs. Use our RAG, Email Processing, and SR Approver AI mini-apps as a foundation for your custom mini-app. 
Can Magnet AI integrate with other IT solutions or only with mainstream CRM platforms like Salesforce and Siebel?
Yes, you can leverage Magnet AI with other CRM, ERP, HCM or IT systems. See the integration question above for details.
How quickly can Magnet AI be integrated into our existing CRM system?

It depends on your use case. Assuming that you can set up Azure resources and provide access to your knowledge bases and CRM system API without delay, it will take just a couple of days to start testing RAG and prompt templates' API. Implementing and testing custom mini-apps might take from several days to several weeks.

Can we conduct a pilot program or proof of concept before we fully commit to Magnet AI?
Yes, of course. Please get in touch with Ideaport Riga or another Magnet AI implementation partner.
What Large Language Model do you use?

For prompt completion, we use Azure OpenAI GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo, and for embeddings, Azure OpenAI Ada-002. As a next step, we will start leveraging Cohere models due to their performance and availability both on Azure and OCI. LLM space is very dynamic, and we keep monitoring it, paying close attention to Llama, Mistral, and Claude models.

How do you monitor Magnet AI?
We rely on Azure's capabilities to monitor Magnet AI's technical performance. Additionally, we developed the ability to analyse the usage of Q&A/ RAG/ Semantic search functionality and check mini-apps audit trail logs.
Can we use your Azure environment?
Being an ISO27001-certified company, Ideaport Riga is especially concerned about customer data security. Before allowing you to use our Azure environment, we want to understand what kind of data we will process. Usually, using our Azure environment for a POC is fine, but production deployment should be separately agreed.
Can I customise my copy of Magnet AI code or even fork it?
You can, as we have open-sourced Magnet AI under the MIT licence.
What kind of support can we expect after the initial deployment?

We have built Magnet AI Admin UI so that your current CRM administrator or maintenance team can operate it while implementing an increasing number of use cases. While Magnet AI's defects can be reported and most likely will be solved, the MIT licence does not provide any SLA. However, you can request premium support services from Magnet AI implementation partners.

What is the technical stack of Magnet AI?
We both leverage Azure services and have a decent amount of custom code. We wrote our backend in Python and used Vue.js for the front end.

Get in touch

We are eager to discuss your business needs, and answer any questions you may have. Send us a message and then we’ll figure out the next move together.
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