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ZOOM Meeting
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ChatFlow Agents • Organizational Knowledge • Tools • Human Handoff

AI Agents that don't just talk —
they execute

Build an AI Agent that understands intent, retrieves answers from your knowledge base (RAG), performs actions in systems (CRM / ERP / Tickets / Orders), and escalates to a human agent when needed — with control, measurement, and security.

See Best Practices
-55%
Response Time
+28%
Conversions
24/7
Availability
Guardrails + Action Logging
RAG on Documents/FAQ/DB
Smart Handoff to Agent
 
Agent Control Center
AI Agent Control Center View: Monitoring, Processes and Tools
Action Completed
Ticket opened + CRM updated
Knowledge Found
Based on internal procedures
Connects to your stack: Channels, Knowledge and Tools
WhatsApp
Web
Slack
CRM
Tickets
API
Best Practices for AI Agent

More "answers", less "headaches"

A good AI Agent is a system: updated knowledge, secure tools, measurement, and human escalation. ChatFlow is built exactly for this.

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Reliable Knowledge (RAG)

Search in procedures, documents, knowledge bases and FAQ — with citations/internal sources to reduce "hallucinations".

Secure Tool Calling

Approved actions only: opening tickets, updating CRM, creating documents, checking order status — with permissions.

Control and Security

Audit logs, role-based permissions, information policy, and escalation to human agent when there's risk/uncertainty.

 
Multi-channel view: Chat, WhatsApp and Email
01
 

Omni-Channel Inbox: All inquiries in one place

AI Agent works best when it sees all context: website, WhatsApp, email and chat. Unify one conversation per customer — including history, files and documentation.

  • Smart Channel Unification
    Prevents duplicates and automatically connects context.
  • SLA-based Prioritization
    Priority, VIP customer, urgency — all according to rules.
Frequently Asked Questions
02
 

Knowledge + RAG: Answers based on real knowledge

Instead of "guessing", the agent retrieves information from sources you define: procedures, product catalogs, return policies, guides, DB and more.

Controlled Sources
What goes into knowledge and who sees what.
Verification Before Answer
When there's no confidence — ask/escalate.
 
Documents and code view: Knowledge sources for AI Agent
 
Automation and tools: System connections and workflows
03
 

Actions & Tools: The agent performs actions

A quality AI Agent doesn't just respond. It acts: opens tickets, changes status, creates quotes, verifies details, and updates systems — according to permissions.

Connection to Existing Tools
CRM, Tickets, Payments, ERP, Webhooks.
Verification Before Execution
"Confirm" step for sensitive actions.
04
 

Human-in-the-Loop: When AI, when human

Critical Best Practice: the agent has "autonomy levels". When risk increases or confidence decreases — perform an organized handoff to an agent, with summary, context and recommended steps.

Automatic Handoff
By topic, sentiment, SLA or confidence.
Summary for Agent
What the customer requested + what's already been done.
 
Team collaboration: Organized transition from AI agent to human agent
 
Analytics dashboard: Measurement, quality and results
05
 

Analytics & Evals: Continuous improvement

Measure what matters: first-contact resolution, answer quality, handling time, conversions, abandonment reasons. Add tests (Evals) to improve systematically.

Business KPIs Scenario Testing Trends and Improvement
06
 

Governance: Security, Permissions and Logging

To deploy an agent in production you need control: who can perform which actions, what's saved, what's marked as "sensitive", and how to detect anomalies.

Role-based Permissions
RBAC for teams and units.
Audit & Trace
Who did what, when and why.
 
Information security: Keys, permissions and data protection

More Capabilities for AI Agent in Production

Everything you need to deploy, monitor and scale — without gambling.

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07

Monitoring & Observability

Latency, errors, anomalies, and conversation analysis to identify issues before they explode.

08

Simulations & Testing

Run scenarios before deployment, test answer quality and policy compliance.

09

Hebrew + Multilingual

Natural language, brand tone, and consistent writing rules — for customers in Israel and worldwide.

10

Integration Hub

Connect existing tools with API/Webhooks and get standard actions for reuse.

Frequently Asked Questions

Want to deploy an Agent quickly and safely? We work according to Best Practices: knowledge, tools, control and escalation.

Average Deployment Time
From a few days to a few weeks — depends on knowledge and tools being connected.
What's the difference between a "Chatbot" and an "AI Agent"?
A chatbot mainly "responds". An Agent also retrieves knowledge from sources, activates tools, performs processes and escalates to an agent when needed — with control and logging.
How do you reduce "hallucinations" and incorrect answers?
Work with RAG on sources you define, add answer rules (guardrails), measure quality, and set automatic escalation when there's no confidence.
Can you connect to existing CRM and tickets?
Yes. Connect through integrations or API/Webhooks. Actions are predefined and protected with permissions.
What about privacy, permissions and logging?
There's role-based permission management, action logging (audit), and the ability to define information policy and human escalation for sensitive actions.

AgentLabs

We build Agentic systems that connect AI to real work: knowledge, tools, processes and measurement. ChatFlow Agents are designed to make service/sales/operations measurable, efficient and secure — without giving up control.

RAG on Internal Knowledge Secure Tool Calling Governance + Audit
Want to Get Started Right?

We'll send a short checklist: knowledge, actions, escalation, monitoring and metrics.

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