Floatbot

What Floatbot is

Floatbot.AI describes itself as an "Enterprise-grade, No-code platform to build LLM powered Multi-Modal Conversational AI Agents (Voice first), Real-time AI Agent Assist (Co-pilot) that can integrate with any data source, service, or channel." In plain terms it is a chatbot and voice agent builder for companies that run a contact center or a high volume of customer conversations: collections, insurance claims, support desks and similar operations. Its own blog also calls it a "no/low-code platform," so expect a visual builder with room for API connections rather than a pure drag-and-drop toy. The site's structured data lists an address in Milpitas, California, and the footer gives a US phone line and the email connect@floatbot.ai.

What you build and how

The homepage frames the product as "1 Platform. 3 Core Modules. 10+ AI Capabilities," and says it unifies "self-service operations, backend workflow automation, and AI-powered team enablement." The capability list covers Conversational AI, Voice AI Agent, Chat AI Agent, SMS and Text AI Agent, Email AI Agent, Real-Time Assist, AI Workspace, AI Copilot, Omni-Channel Collaboration, Document and Data Intelligence, Enterprise Knowledge Search, and Autopilot and Workflow Automation.

Voice agents. Voice is the lead product. The company's blog explains that businesses use voice agents for inbound calls, where customers reach out for help, and outbound calls, such as sales pitches or payment reminders. It gives debt collection as one outbound example and shows an agent called LISA automating claims first notice of loss filing. The contact-center page lists "Bot Interruption," meaning the agent handles pauses, interruptions and background noise so the conversation sounds natural.

How the build works. The page headed "Prompt It. Build It." says you give a prompt and the platform creates an AI agent, or you start from industry-ready, pre-trained agents. The blog's step-by-step guide adds the detail. You customize LLM prompts in a Setup AI section, and you can then set the LLM model and temperature. A snippet feature pushes or pulls data from your backend systems, and variables store user inputs or perform arithmetic. In the Setup AI window you choose the language model, with OpenAI ChatGPT, Floatbot Generative AI, Google AI or a custom LLM named as options, and an intent detector. Within a workflow you can switch ASR (speech recognition) models and languages, and call actions let the agent hang up, transfer to a human agent or dial a SIP address. The guide ends with testing and deploying the agent, and the contact-center page sums the cycle up as build, test, integrate, go live and analyze. Its FAQ says a voice AI agent typically takes around 3-6 weeks to go live, depending on use cases, complexity and integrations. A separate line says you can combine "LLM-driven intelligence with flow-based control to design guided, dynamic conversations or workflows that adapt in real time," so the builder mixes prompts with fixed flows.

Scout. The homepage introduces Scout as "the Built-in AI Assistant for the Floatbot Platform." It lets you create, test, deploy and analyze AI agents across all 3 modules through a chat workspace. This is the prompt-driven way into the same builder.

Other channels. Text and SMS agents are described with unified conversations across call, chat, SMS and email, live chat fallback, personalized messaging based on customer data, and campaign management with AI personalization. Email agents read and respond to customer emails, with email-to-workflow automation. The homepage lists email tasks it can handle: summarizing emails and attachments, indexing and classifying emails with custom business rules, routing and prioritizing support tickets, and extracting key data from documents. Human approvals (HITL) can be added wherever required.

Agent assist and knowledge. Real-Time Assist is a co-pilot for human agents. A customer quoted on the site says it was good at identifying the right knowledge article from the inputs provided. The contact-center page also lists "RAG Cognitive Search," shown as stages from Gen 1 to Gen 3, though the text gives no detail on what each stage adds.

Testing, integration and handoff. You can automate test cases, run simulations from a prompt and adjust responses before going live. The page says you can connect your voice AI to your contact center, CRM, telephony or messaging platforms, and that the platform supports custom APIs for end-to-end automation. Conversations transfer from AI to a human agent with full context. The contact-center page lists privately hosted and fine-tuned LLMs and speech models for specific industries, orchestration across 50+ LLMs and speech models, multilingual support for 100+ languages, and voice biometrics with 2FA authentication. Product demos on the same page show real-time assist running with Genesys for collections and with Amazon Connect for claims.

Analytics. "50+ Analytics" is a headline feature. In the dashboard the FAQ says you see user engagement, calls, outbound campaigns and goal-based analytics.

The evidence from the pages

Pricing. The pages show no prices or plan names, though the menu links a pricing page. There are "Start free trial" and "Schedule a Demo" buttons, and the blog footer adds a "Try for Free" link. The homepage also runs a demo knowledge assistant that tells visitors "You've reached your daily limit of 40 trial messages," which is a limit on that demo and not a statement about plans.

Security and compliance. The FAQ answers "How secure is the Voice AI Agent?" with "enterprise-grade security, including encryption at rest and in transit, PII-safe processing, audit logs, role-based access, SOC 2 compliance, and more." That is the company's own claim on the voice page. HIPAA appears only in a customer quote about collections workflows, where the customer says flexibility matters "when you're dealing with HIPAA, right-party contact, and the reality of collections workflows."

Support. After implementation the company says it provides "a dedicated customer success manager, technical support, and periodic optimization by our team."

Customers. The site quotes several. A collections-focused customer lists voice and chat bots, collections workflows, compliance guardrails and integrations with TCN and ACE, and says Floatbot has been "more like a build partner." A managing attorney at Mountain Peak Law Group credits the "compliance-first approach and fast response time." A customer says they have used the platform since 2022, starting with a basic chat agent and now adding GenAI and a voice agent for the call center. Another customer claims an agent-assist deployment came together 70% faster than similar solutions. The homepage also shows per-customer results, such as "$4.2M+" in payments processed within the first 12 months, and names collections and insurance firms including Capital Recovery, Answer Financial, Cabrillo Coastal and UCB.

The blog also cites a figure that 71% of customers favor voice over typing. That is a marketing statistic from the company's article, not a product feature.

Who it suits and who it does not

Floatbot suits an operations or IT team at a company with real call volume that wants voice, chat, SMS and email agents from one vendor, and that is comfortable with a guided implementation. The testimonials come from collections, legal and service-provider settings, and the SOC 2 claim and audit logs match what a regulated buyer asks about first. A team that already has a contact center, CRM and telephony system can plug the agent into them.

It is a poor match for a founder who wants to launch a website chatbot this afternoon. With pricing handled through the company, implementation framed around integrations and a dedicated customer success manager in the package, the buying motion is closer to enterprise software than to a self-serve builder. Voice-first also means a team that only wants a simple text widget is paying attention to a product built for something larger.