People Loop

What is People Loop?

People Loop is an AI support platform for building and deploying AI agents that answer customer and internal questions. Its core purpose is to automate support and help users find answers, while still routing complex or frustrated requests to a human escalation flow.

The platform is designed for LLM-based agents, with agent training and deployment steps that use your business data and configured actions. It also includes an escalation mechanism that routes certain conversations to a human desk rather than keeping everything inside the chatbot.

Key Features

• AI agent creation, management, and deployment: Build and run conversational agents without requiring technical skills.
• LLM responses with reasoning capabilities: Uses language models designed for effective responses to complex queries.
• Agent training on business data with configurable actions: Train an agent on your data sources, configure what actions it can take, and deploy it for customers.
• Semantic search for answering questions: Uses semantic search alongside LLMs to provide accurate responses grounded in the trained knowledge.
• Human escalation for complex issues: A state machine detects anger or confusion and hands off to the VA Desk.
• Security controls: Includes robust encryption and strict compliance standards.

How to Use People Loop

1. Start with the free plan or free trial: Begin building an agent using the available free offer.
2. Build your agent from your data: Train the agent on your business data and configure what actions the agent can perform.
3. Deploy it for your customers: Connect the agent so it can respond to customer questions and take the configured actions.
4. Review and improve performance: Review chat logs to identify knowledge gaps and update sources.
5. Route edge cases to humans: For complex, angry, or confused requests, rely on the platform’s escalation handoff workflow.

Use Cases

• Customer support automation: Use an AI agent to answer common support questions and resolve issues, with escalation to a human desk when the conversation is complex or the user is frustrated.
• Internal search over documents and policies: Deploy an internal knowledge retrieval assistant so employees can find documents, policies, and answers quickly.
• Lead generation and qualification: Provide 24/7 website engagement that qualifies visitors and books meetings automatically.
• Data analysis via chat: Allow users to chat with data to extract insights and generate reports on the fly.

FAQ

• How does “Human Handoff” work? The platform uses a state machine to detect anger or confusion in a conversation and hands off to the VA Desk.

• Is there a free option to start? Yes. The site states there is a free plan available and a 14-day free trial on paid plans.

• Can I connect People Loop to other tools? Yes. The site lists integrations with Slack, HubSpot, Salesforce, WhatsApp, Notion, Zapier, and Shopify.

• What kinds of questions can the agent answer? The agent is intended to answer questions using semantic search and LLMs, and it supports knowledge retrieval and support workflows built from business data.

• Can I update the agent over time? Yes. The workflow includes reviewing chat logs to identify knowledge gaps and updating sources.

Alternatives

• Helpdesk/chat platforms with built-in AI assistants: These typically focus on ticketing and chat support, with AI answering as a feature; the distinguishing workflow in People Loop is agent deployment plus an explicit human escalation handoff mechanism.
• RAG (retrieval-augmented generation) chatbot platforms: Useful when you want to build knowledge-grounded chat over your documents; you may need to implement or configure escalation logic separately.
• Customer support automation tools with workflow routing: Good for routing and automating ticket triage, but may not provide the same agent-centric creation and semantic-search grounding for conversational answers.
• Internal knowledge base search tools with AI: Useful for employee self-service document discovery; these may be better suited for search than for end-to-end conversational support and action-taking.