AI Workflows and Agents

Folderr's AI workflow capabilities provide a powerful platform for building and executing complex AI-powered automation. Key features include:

1) Comprehensive Node Ecosystem

  • Over 80 pre-built nodes covering AI/ML, data processing, and integrations.
  • Specialized AI capabilities including summarization, vision, and training.
  • Enterprise-grade reliability and security features.

2) Robust Execution Engine

  • Handles complex workflows with conditional logic and loops.
  • Optimized for performance with topological sorting and caching.
  • Scalable architecture supporting large workflows.

3) Powerful AI Integration

  • Multiple AI model integrations (OpenAI, DALL-E, ElevenLabs).
  • Conversational AI through Agent nodes.
  • Data processing AI (tabular data, OCR, speech).

4) Enterprise Features

  • Role-based access control.
  • Usage tracking and limits.
  • Audit logging.
  • Model configuration management.

5) Monitoring and Analytics

  • Detailed execution history tracking.
  • Performance metrics and analysis.
  • Error tracking and debugging.
  • Usage reporting.

Use Cases

  • AI-powered document processing pipelines.
  • Automated customer support workflows.
  • Data enrichment and analysis.
  • Content generation and publishing.
  • Business process automation.

The combination of a comprehensive node ecosystem, robust execution engine, and enterprise-grade features makes Folderr a powerful platform for building and deploying AI-powered automation at scale.


Workflow Example 1 |

Concept: Ask 1 quetion to multiple LLMs and compare their outputs.
Action Nodes:  (Text Input, Ask AI, Output)

Text Input Node: Ask a question, and connection the question to 'Action Nodes' with 'input' fields.

This example we ask a difficult question for AI, and that is to write 10 sentences ending in the word apple. As you can see in the example below, GPT 3.5 and GPT4o both failed this test‍


Workflow Example 2 |

Concept: Read our github code repositoty and write relase notes for our users! 
Action Nodes: Used: (Github Pull Request Reader, Join Texts, Combine Text, Ask AI, GitHub Pull Request Commentor)

Ask AI Instruction: "Review pull request. User will provide list of files that were changed and list of Git Patches.
Create release notes for end-users"

This example we use internally to read our code and create nice user friend code updates.


Workflow Example 3 |

Concept: Analyze Financial Data (CSV or XLSX) data imported from ERP system, write an executive, send report via email)
Action Nodes: Used: (AI Assistant containing files and linked to LLM, Text Input, Combine Text, Ask AI, Output, Send Email)

Base Promp in AI Assistant: 
"I need you to function as an accurate accountant analyzing the uploaded document.
Do not talk with me.
Only answer the question asked.
Do not make up data.
Do not provide example data if you dont know the answer.
Your output will be used in a computer program."

Ask AI Instruction: "Write an executive Report summarizing the inventory status"

Folderr converts CSV and XLS data to SQL allowing for reliable analysis and automation relaated to financial data analysis.

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