Sema4.ai

Features

• Natural Language Runbooks: Define and update AI agents using plain English—no code or workflow tools required. • Runbooks act as the agent’s instructions, making it simple for business or process owners to describe objectives, logic, and decision processes. • Built-in AI Co-pilot (Sai): Guides users step-by-step through building agents, from defining requirements to generating runbooks and recommending actions. • Action Gallery & SDK: Access a library of pre-built actions for enterprise apps like HubSpot, Zendesk, SharePoint, and Google Workspace, or create custom actions using the SDK to connect to virtually any application. • Secure, Local-First Development: Build and test agents locally on Windows or macOS, with full control over data. Deploy securely within your AWS VPC or Snowflake environment using zero-copy access. • Transparent Reasoning: View an agent’s real-time “thought process” for full visibility into how decisions are made, enabling trust and compliance. • Flexible LLM Support: Choose from leading enterprise-grade models (OpenAI, Microsoft Azure, Amazon Bedrock, Snowflake Cortex) to balance cost, performance, and security. • Seamless Publishing: Deploy agents to production-ready environments – Enterprise Edition in AWS or Team Edition in Snowflake – with a single click. • MCP Integration: Connect securely to hundreds of enterprise systems through Docker’s MCP gateway, and create agents that are MCP endpoints, enabling deep integrations without data duplication.

Use Cases

Emerson, a global technology and software company serving industrial, commercial, and consumer markets, collaborated with Sema4.ai to develop an AI agent that streamlined remittance matching for thousands of customer payments. Matching accuracy improved from roughly 20% to 80–90%, significantly accelerating cash application and reducing days sales outstanding. Built and refined through Sema4.ai Studio, these agents process unstructured email data, map remittances to bank transactions, and continuously learn to improve performance over time. Koch Inc., the 2nd largest private company in the U.S., manages hundreds of natural gas pipeline invoices each month, each ranging from 10 to over 100 pages. Employees previously had to manually reconcile invoice totals against internal records in the company’s Energy Trade and Risk Management (ETRM) system, an intensive process prone to delays and human error. Using Sema4.ai Studio, Koch teams can now design and test AI agents that read and compare invoice data, identify discrepancies, and connect securely to internal systems for validation. Once tested, these agents are deployed through Sema4.ai’s Enterprise Platform to run at scale, automating reconciliation for hundreds of customer invoices each month. This has led to an 80% reduction in manual work, improving accuracy, productivity, and overall cost efficiency.

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