New generative AI capabilities have been added to Pipefy ‘s no-code business process automation (BPA), to accelerate workflow deployment, automate complex processes, and analyze data.

Suitable for HR, finance and procurement teams, Pipefy AI simplifies building, automating, and managing workflows and processes for users, including business users, citizen developers, and IT teams.

Pipefy AI consists of three core features: AI Automation, AI Agents and AI Co-pilot. AI Automation eliminates manual and repetitive tasks. AI Agents streamline service delivery, and AI Co-pilot builds new workflows and provides the data analysis and insights teams need to optimize them.

Pipefy's AI Automations execute manual, repetitive, high-volume tasks through natural language, trigger-based prompts. This feature is part of its automation engine and expedites tasks such as image recognition, data extraction, and data interpretation.

It significantly increases team efficiency by automating complex processes like matching data, verifying documents, generating content, and summarizing information.

For example, a legal analyst that needs to review 10 contracts with suppliers – a process that usually takes three hours – now takes just 30 minutes with Pipefy AI. For procurement/purchasing departments, examples of AI-driven Automations with Pipefy AI include:

• Analyzing purchase requests or item descriptions and automatically placing them into the appropriate procurement categories
• Automatically approving simple requests according to preset criteria, such as policies and budgets
• Scanning procurement and transaction documents to ensure compliance with internal policies, industry regulations, and contractual agreements; flagging potential issues for further review and remediation

Pipefy's AI Co-pilot tool builds optimized workflows in seconds and delivers the data analysis and insights teams need to make strategic decisions. AI Co-pilot also guides users to most effectively utilize Pipefy.

For the procurement/purchasing department, examples for uses of AI Co-pilot include:

• Generating financial performance and delivery reports
• Analyzing supplier data to identify best partners based on past performance
• Identifying bottlenecks, trends, and root causes

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