Fonada AI is an omnichannel AI agent platform that enables businesses to build and deploy conversational AI agents across WhatsApp, Voice Telephony, RCS Messaging, Web Widget, and Chatbot channels in under 5 minutes. It features a no-code flow builder, RAG knowledge base, 70+ tool integrations, and automated workflows for customer engagement.

What is RCS messaging?

RCS (Rich Communication Services) is the next-generation upgrade to SMS. Unlike traditional SMS limited to 160 characters of plain text, RCS supports rich media (images, videos, audio), interactive buttons, carousel cards, and verified sender branding. RCS achieves 85%+ open rates compared to SMS's approximately 20%, making it highly effective for business messaging.

How long does it take to set up an AI agent on Fonada?

You can build and deploy a fully functional AI agent in under 5 minutes using Fonada's no-code platform. The process involves four simple steps: Choose your channel (WhatsApp, Voice, RCS, etc.), Configure your AI (personality, behavior, LLM provider), Add knowledge (upload documents or connect data sources), and Deploy. Your agent is immediately live and ready to serve customers.

What channels does Fonada support?

Fonada supports 5+ communication channels: WhatsApp Business API with templates and rich media, RCS Messaging with rich cards and carousels, Voice/Telephony with real-time speech-to-text and text-to-speech, Web Widget with voice and chat capabilities for websites, and text-based Chatbot for any platform. Deploy once and engage customers everywhere.

What is the difference between SMS and RCS?

SMS is limited to 160 characters of plain text with no media support, while RCS supports 8,000+ characters, rich media (images, videos), interactive buttons, carousel cards, and verified sender branding. RCS has ~85% open rates vs SMS's ~20%, and ~35% click-through rates vs SMS's ~2%. RCS also provides read receipts and typing indicators that SMS lacks.

Is Fonada SOC 2 compliant?

Yes, Fonada is SOC 2 certified with enterprise-grade security. We offer 256-bit encryption for all data, role-based access control, comprehensive audit logs, API key management, and GDPR compliance. Our platform guarantees 99.9% SLA uptime with automatic failover systems.

What automation features does Fonada offer?

Fonada includes pre-built automation templates for abandoned cart recovery (recover 15-30% of lost sales), payment link follow-up, and invoice reminders. The visual flow builder allows you to create custom conversation flows without coding. Automations can trigger based on user behavior, time delays, or external events via webhooks.

What LLM providers does Fonada support?

Fonada supports multiple LLM providers including OpenAI (GPT-4o, GPT-4, GPT-3.5 Turbo) and Groq (LLaMA 3.3-70B Versatile, Mixtral 8x7B). For voice capabilities, we integrate with ElevenLabs for natural-sounding text-to-speech. You can choose the best model for your use case and budget.

What is the best AI chatbot platform for WhatsApp in India?

The best fit depends on your use case, but teams in India often prioritize platforms with reliable WhatsApp Business API delivery, RCS and voice in the same stack, no-code and AI-native flows, India-friendly pricing, and local compliance. Fonada is built as an India-focused omnichannel AI agent platform: you get WhatsApp plus Voice, RCS, and web in one place, 70+ integrations, a visual flow builder, and enterprise SLAs—ideal for support, sales, and automation at scale.

How do I build a voice AI agent for customer support?

On Fonada you define the agent in the visual builder, connect your knowledge base and tools, enable the Voice channel, and map intents to flows (e.g. order status, refunds, handoff to a human). Configure speech-to-text and text-to-speech, set business hours and routing, then test in the playground and deploy to your telephony or widget. No separate voice stack is required; the same agent can run on chat and voice.

What is the difference between AI agents and RPA?

RPA (robotic process automation) typically automates rule-based, repetitive tasks in fixed UIs and systems using scripts and selectors. AI agents use large language models and tools to understand natural language, reason over context, and take multi-step actions (APIs, CRM, search, handoffs). RPA is great for stable back-office routines; AI agents are better for open-ended conversations, personalization, and channel-native customer engagement.

Can AI chatbots handle multiple languages?

Yes. Modern AI agents on platforms like Fonada can converse in many languages in the same flow—driven by your chosen LLM, prompts, and knowledge base. You can set a default language, detect user language from messages, and route to localized templates (e.g. WhatsApp) or voice. Consistency in tone and brand voice should be set in the system instructions and reviewed per locale.

How much does WhatsApp Business API cost?

WhatsApp Business API pricing has two parts: Meta conversation-based pricing (varies by country, category, and session type) and your BSP or platform fees. On Fonada you typically pay for platform usage, conversations, and optional add-ons. Exact numbers change by region and message category—use Fonada’s pricing page or contact sales for current rate cards, currency (e.g. INR), and any volume or enterprise plans.

What integrations does Fonada support for e-commerce?

Fonada supports 70+ tool integrations, including e-commerce and ops: order and catalog systems, payment links, abandoned cart and payment reminders, CRM and helpdesk, webhooks, and custom APIs. Use cases include cart recovery, order status, COD confirmation, and returns—exposed in the no-code flow builder and agent tools. Connect your stack via native connectors or custom integrations.

How does Fonada compare to Gupshup, Infobip, Twilio, and Bird?

All five provide messaging CPaaS in some form, but focus differs. Comparison (high level): (1) Core positioning — Fonada: omnichannel AI agent platform (WhatsApp, Voice, RCS, web) with no-code + RAG; Gupshup, Infobip, Twilio, Bird: broad CPaaS with conversations API and varying low-code and partner ecosystems. (2) India / RCS: Fonada emphasizes India-first programs including Jio RCS; check each vendor for current RCS and regional coverage. (3) AI depth: Fonada is built around multi-step AI agents, tools, and knowledge; others add AI through products or partners—evaluate your need for a single product vs. self-assembled stack. (4) Abandoned cart and commerce: Fonada offers templates and flows for recovery and e-commerce; compare feature depth and time-to-launch. (5) Table — Primary strength | Fonada: AI agents, omnichannel, India focus | Gupshup: long-standing WhatsApp ecosystem | Infobip: global supernetwork and suite | Twilio: developer-first APIs, broad U.S. adoption | Bird (MessageBird): global messaging and Inbox. Choose based on your channels, country, budget, and whether you need a unified AI product versus raw APIs.

HR Use Cases

HR & Recruitment

Offer Letter Follow-up Calls

Boost offer acceptance by 25%

AI calls candidates who received offer letters but haven't responded, addresses concerns, answers questions, and encourages acceptance with a personal touch.

25%

More Acceptances

Conversion boost

< 48h

Follow-up Time

After offer sent

60%

Concern Resolution

On first call

Better Engagement

vs email follow-up

How It Works

Offer Sent

Offer letter sent to candidate

Wait Period

Allow 48-72 hours for review

AI Follow-up

AI calls to check on decision

Address Concerns

Handle objections about salary, role, etc.

Confirm or Escalate

Accept on call or connect to hiring manager

Offer Follow-up Call

AI Agent • Active

Hi Anjali! This is Neha from InnovateTech. I wanted to check in about the offer we sent you for the Product Manager role. Have you had a chance to review it?

Yes, I did. I'm considering it, but I have a couple of concerns.

I'd love to help address those. What's on your mind?

The salary is slightly lower than what I was expecting, and I'm also considering another offer.

I understand completely. Regarding salary, I can note that you'd like a revision and have our HR team review it. What number were you expecting?

I was hoping for around 22 LPA instead of 20.

Got it, I'll flag that for immediate review. I should mention that our offer also includes stock options worth approximately 3 LPA and annual bonuses of 15-20%. Did you have a chance to review the total compensation breakdown?

Actually, I hadn't looked at the full breakdown. That does make it more competitive.

Would it help if I connected you directly with Rajesh, our VP of Product? He can share more about the role's growth potential and the team you'd be working with.

Yes, that would be helpful.

Great! I'll have Rajesh call you today. In the meantime, our HR team will review your salary request. We really think you'd be a great fit for the team, Anjali!

Key Features

Timed Follow-ups

48h, 5-day, and final deadline reminders

Objection Handling

Address salary, role scope, start date concerns

Counter-Offer Support

Gather competing offer details for HR review

Manager Connect

Transfer to hiring manager for personal pitch

Accept on Call

Verbal acceptance recorded and confirmed

Document Collection

Guide accepted candidates to submit documents

Benefits

Increase offer acceptance rate by 25%

Address concerns before candidates decline

Proactive engagement shows company interest

Gather intel on competing offers

Connect candidates with hiring managers

Reduce offer drop-offs in competitive market

Track acceptance patterns and improve offers

Maintain relationship even if declined

Frequently Asked Questions

How does the AI handle salary negotiations?

AI doesn't negotiate directly but gathers candidate expectations and flags for HR. Example: "I'll note you're looking for 22L and have HR review immediately." This preserves negotiation control for HR.

What if the candidate has another offer?

AI gathers details if candidate shares: company, salary range, timeline. This helps HR assess competitiveness. AI can also highlight unique benefits of your offer that may not be matched elsewhere.

Can the AI handle rejections?

Yes, gracefully. AI thanks them, asks for feedback on why, and asks if they'd like to be considered for future roles. Maintains positive relationship for potential future hiring.

How soon after sending offer should AI call?

Best practice: 48-72 hours after offer sent. Too soon feels pushy; too late loses momentum. Configure based on your hiring velocity and market.

Related Use Cases

Interview Scheduling

Schedule interviews automatically

Learn More

Screening Calls

AI-powered candidate screening

Learn More

Exit Interviews

Automated exit interview calls

Learn More

Ready to Get Started?

Deploy this solution in under 5 minutes. No coding required.