Artificial intelligence is rapidly transforming how organizations interact with business data. Instead of manually searching reports, building queries, or relying on technical resources to answer questions, finance teams can now leverage AI to access information faster and more intuitively.

Sage Intacct’s new AI Gateway brings this capability directly to your financial data. By securely connecting AI applications to Sage Intacct through REST APIs or the new Model Context Protocol (MCP) Server, organizations can accelerate reporting, simplify integration design, and create powerful AI-assisted workflows. This month’s tip explores how the AI Gateway works and how organizations can begin taking advantage of its capabilities.

Tip summary: What is the Sage Intacct AI Gateway?

The Sage Intacct AI Gateway provides secure access to Sage Intacct data and metadata for AI-powered applications, assistants, and integrations. Organizations can connect through REST APIs for structured integrations or the Model Context Protocol (MCP) Server for AI-driven data exploration, reporting, and metadata discovery.

Designed for large language models (LLMs) and AI assistants, the MCP Server allows users to explore Sage Intacct objects, fields, and records using natural language prompts while maintaining read-only access to data.

Key benefits include:

• Faster access to business insights
• Enhanced reporting and data exploration through AI
• Simplified integration planning and design
• Faster generation of queries, mappings, and validation artifacts

Common use cases include AI-powered data assistants, financial reporting and analysis, integration design, developer copilots, and data migration projects. For example, users can ask AI to identify available fields on an object, generate query templates, explain object relationships, or create validation checklists, turning hours of manual research into minutes.

Tip steps: How to get started with the Sage Intacct AI Gateway

Step 1: Select an AI environment

Begin by choosing the AI application that will interact with Sage Intacct data. This could include:

• An AI assistant or chat-based interface
• A custom AI service or agent
• An MCP-capable desktop or development tool such as Claude Desktop

The environment should be capable of sending structured requests and processing responses generated by a LLM.

Step 2: Connect to Sage Intacct

Next, establish connectivity using one or both supported access methods:

MCP Server

• Ideal for AI-powered discovery, reporting, and metadata exploration
• Provides read-only access to Sage Intacct data and object metadata

REST APIs

• Best for integrations and application workflows requiring deterministic results
• Supports transactional and operational processes

The access method you choose depends on your business objective. Many organizations will use both technologies together.

Step 3: Explore metadata and query data

Once connected, users can begin exploring Sage Intacct objects, fields, and records through natural language prompts.

Examples include:

• Identifying available fields within an object
• Understanding object relationships
• Retrieving specific business records
• Generating summaries and insights

This approach significantly reduces the learning curve for understanding Sage Intacct data structures.

Step 4: Generate insights and development artifacts

After retrieving data or metadata, AI can generate valuable outputs such as:

• Natural-language summaries
• API query templates
• Data mapping documents
• Integration specifications
• Validation checklists
• Testing scenarios

These artifacts can help accelerate projects while reducing manual effort.

Step 5: Build smarter business workflows

Organizations can use AI-generated outputs to support a variety of workflows, including:

• Finance data assistants
• Integration builders
• Developer copilots
• Reporting automation initiatives

For example, a finance team could use AI to identify vendor payment information, calculate settlement amounts, generate recommended transactions, and create API requests to automate downstream processes.

Tip insights: AI Gateway best practices

To maximize value from the AI Gateway, consider the following recommendations:

• Use MCP for data discovery and REST APIs for production integrations
• Explore object schemas before building queries
• Start with focused, incremental requests
• Protect authentication credentials and access tokens
• Treat MCP responses as read-only reference information
• Validate AI-generated outputs before deploying them in production workflows

Following these best practices helps ensure secure, reliable, and scalable AI adoption.

Why this tip matters

The Sage Intacct AI Gateway represents an important step forward in how organizations interact with financial data. By combining AI capabilities with secure access to Sage Intacct information, businesses can accelerate reporting, simplify integration development, and empower users to uncover insights faster than ever before.

Whether you’re exploring AI-powered reporting, building intelligent integrations, or evaluating future automation opportunities, our Sage Intacct experts can help you develop the right strategy. Contact us today to learn how the AI Gateway can support your business goals, and be sure to check back next month for another Sage Intacct Tip of the Month.