What platforms does Agent M support?

Agent M is available on Web App.

What are the limitations of Agent M?

No public pricing or plan comparison on the homepage, so cost must be obtained from sales. Feature scope is broad enough that setup and governance can take real configuration effort. Sub-5-second latency and hallucination reduction are vendor claims without published benchmarks.

Agent M

Name: Agent M
Author: Agent M

Build and orchestrate specialized LLM agents without writing code

Intermediate API

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Screenshot of Agent M, Build and orchestrate specialized LLM agents without writing code

What is Agent M?

Agent M is an AI chat bot tool that builds and orchestrate specialized LLM agents without writing code. Agent M is Floatbot's no-code agentic framework for building multi-agent LLM assistants that chat, call APIs, search internal data and deploy across 15+ channels.

Agent M is Floatbot's agentic AI framework for building, training and running specialized LLM-driven agents. A master agent acts as a manager, coordinating smaller agents that each own a single process such as answering FAQs, pulling CRM records, booking meetings or completing a sales quote. The framework handles session management, long running memory and the routing between agents, so a conversation can move across several tasks without the user restarting. In practice, teams use the no-code studio to attach skills. Pre-defined skills cover common support and sales work (orders, tickets, calendars, CRM lookups), and custom skills can be assembled for narrower jobs like freight calculation or travel planning. Agents are grounded with uploaded documents and internal knowledgebases through RAG cognitive search, and they reach business systems through API integrations with CRM, ERP or custom applications. Guardrails include PII redaction and a verification layer aimed at reducing hallucination. Everything can be tested in a service terminal with live logs before it goes live. The model layer is deliberately open. Agent M runs on FloatGPT or on GPT, Claude, Gemini, Llama or a custom enterprise LLM, and deployment spans chat, voice, SMS, email plus channels such as WhatsApp, Messenger, MS Teams, Telegram and the web. Compliance claims include SOC 2, HIPAA and GDPR, with sensitive data excluded from model training. The tool suits contact centers, support and sales operations, and product teams embedding an assistant into their own application. It is closest to general agent frameworks such as LangChain, but it trades library-level flexibility for a managed, channel-ready product. Buyers should note that the homepage publishes no pricing, and that the breadth of the feature set means real value depends on how much of the integration and orchestration layer a team actually uses.

How do you use Agent M?

1Map the processes you want agents to own
Split the target workflow into discrete jobs such as FAQ handling, order lookup or quote generation. Each job becomes the scope of one specialized agent under the master agent.
2Create agents and attach skills
In the no-code studio, start from pre-defined skills (calendars, tickets, CRM data) or build custom skills for domain tasks like freight or calorie tracking.
3Ground agents in your data
Upload knowledgebases and documents so RAG cognitive search can answer from internal material, and connect CRM, ERP or custom APIs where live data is needed.
4Set guardrails and model choice
Pick the LLM (FloatGPT, GPT, Claude, Gemini, Llama or custom) and configure PII redaction and behavior controls to limit hallucination and data exposure.
5Test in the service terminal
Run queries, validate responses and inspect real-time logs before any customer sees the agent. Correct orchestration and skill routing at this stage.
6Deploy across channels
Publish the agents to chat, voice, SMS, email, WhatsApp, Messenger, MS Teams, Telegram or the web, then monitor conversations and refine over time.

Pros and cons

Pros

Master agent orchestration is built in rather than bolted on through external toolingAI
No-code skill builder plus API and pro-code options for developers who need more controlAI
LLM-agnostic: runs on FloatGPT or GPT, Claude, Gemini, Llama and custom enterprise modelsAI
Wide deployment reach across chat, voice, SMS, email and messaging platformsAI
Testing terminal with live logs and PII redaction before go-liveAI

Cons

No public pricing or plan comparison on the homepage, so cost must be obtained from salesAI
Feature scope is broad enough that setup and governance can take real configuration effortAI
Sub-5-second latency and hallucination reduction are vendor claims without published benchmarksAI
Proprietary framework ties orchestration and monitoring to Floatbot's own platformAI
Compliance certifications are stated but documentation is not linked from the homepageAI

How much does Agent M cost?

Integrations

Agents connect to CRM, ERP and custom applications through API integrations without coding, and reach customers over WhatsApp, Facebook Messenger, MS Teams, Telegram, web chat, voice, SMS and email.

Features

Multi-agent orchestration under a master agent, pre-defined and custom no-code skills, long-conversation memory and session management, RAG cognitive search over uploaded documents, API connections to CRM and ERP, PII redaction and hallucination guardrails, omni-channel deployment, a service terminal for testing with live logs, and support for FloatGPT plus third-party LLMs.

Frequently asked questions about Agent M

Does Agent M have an API?
Yes, Agent M offers an API.
How do you use Agent M?
The walkthrough on this page covers 6 steps: 1. Map the processes you want agents to own 2. Create agents and attach skills 3. Ground agents in your data 4. Set guardrails and model choice 5. Test in the service terminal 6. Deploy across channels.
What platforms does Agent M support?
Agent M is available on Web App.
What does Agent M integrate with?
Agents connect to CRM, ERP and custom applications through API integrations without coding, and reach customers over WhatsApp, Facebook Messenger, MS Teams, Telegram, web chat, voice, SMS and email.
What are the limitations of Agent M?
No public pricing or plan comparison on the homepage, so cost must be obtained from sales. Feature scope is broad enough that setup and governance can take real configuration effort. Sub-5-second latency and hallucination reduction are vendor claims without published benchmarks.