Where to deploy your AI agent for fast growth

Most AI agents get built into apps and websites. But there are other options, and they’re underused, which makes them an opportunity.

Here are five underused platforms where AI agents can be deployed — plus how to deploy them.

1. WhatsApp and SMS AI agents: The overlooked goldmine

One of the first surprises after launching Jotform’s AI Agents was that users weren’t just embedding them into forms and web pages. They were plugging them into WhatsApp threads and SMS flows.

Why it works:

• Untapped markets: Billions of users rely on WhatsApp and SMS for business interactions. For many of our users — especially in LATAM, India, and parts of Africa — WhatsApp is the primary channel for business.
• Lower friction: Users don’t need to install anything or sign up — they just message a phone number on WhatsApp or SMS, and the agent responds.
• Trust factor: People open texts and WhatsApp messages faster and more reliably than emails.

How to build it:

Choose your base platform:

• Use Twilio (for SMS and WhatsApp), Jotform WhatsApp Agent, or 360dialog / Vonage for WhatsApp-specific needs.
• You'll need to register a WhatsApp Business number (takes 1-3 days).

Build your backend logic:

• Use LangChain or Flowise to define the conversation flow.
• Use OpenAI, Claude, or Mistral for generating responses.
• Use Jotform AI Agents if you want to connect the agent to a form, workflow, or structured submission logic.

Handle context and memory:

• Use Twilio’s session ID or create a simple Redis store for user state.
• Save basic user inputs: name, intent, history.

Add webhooks and triggers:

• Connect to a Google Sheet, a CRM, or Stripe for actions.

Test flows manually:

• Run end-to-end tests with 3-5 users before deploying widely.
• Use fallback replies and error handling from day one.

2. Voice AI agents: Unlocking a new audience

Text-based AI is everywhere. But voice-driven AI agents are still rare.

Why it works:

• Faster adoption: Talking is easier than typing for most people.
• Inclusive growth: Voice-first interfaces appeal to non-tech users, older users, and accessibility-focused customers.
• Emerging applications: Voice AI is still underused in areas like phone-based support, smart home devices, and hands-free workflows — making it a fresh opportunity for reaching users in new contexts.

How to build it:

Choose your voice interface:

• Twilio Voice: easiest to deploy for phone calls.
• Google Dialogflow, Amazon Lex, or AssemblyAI: for speech-to-text.
• Jotform AI Agents: for building the actual agent logic, response flow, and structured output (forms, actions, etc.).
• ElevenLabs, PlayHT, or Amazon Polly: AI-generated voice replies.

Convert voice to text:

• Pipe audio from Twilio into AssemblyAI or Whisper API.
• Clean up the transcript (e.g., remove filler words, long pauses).

Run AI logic:

• Send the transcript to your LLM of choice (OpenAI, Claude, Mistral).
• Use LangChain, Jotform AI Agents, or custom logic to define flows.
• Add intent detection or classification to route messages..

Convert text back to speech (optional):

• Use Polly, ElevenLabs, or PlayHT to convert responses back into audio.
• Stream back the AI-generated voice in real-time.

Deploy to real phone numbers:

• Buy a number via Twilio.
• Route inbound calls to your voice agent logic.

3. AI agents inside progressive web apps (PWAs): Lightweight, high-retention deployment

Most startups build AI products as web apps or native apps — but PWAs can offer better retention and engagement.

Why it works:

• One-tap install: No App Store or Play Store delays.
• Re-engagement: Use push notifications to bring users back.
• Offline support: Great for emerging markets or field use cases.
• Faster iteration: Deploy updates without waiting for app review.

How to build it:

Build a simple PWA shell:

• Frameworks: Next.js, Vue, and SvelteKit all support PWA modes.
• Enable offline access by storing core assets locally — typically with a service worker.
• Add a basic manifest file (which defines things like the app’s name, icon, and theme color) to make it installable.

Embed your AI agent:

• Use a custom chat UI, embed a third-party agent, or directly integrate your LLM logic via an API.
• You can also drop in Jotform AI Agents as a widget or iframe, especially if your agent is form-driven or tied to structured workflows.

Store state locally:

• Use localStorage or IndexedDB to hold conversation history, context, or input when offline.
• Sync to your backend when connection is restored.

Enable push notifications:

• Use Firebase Cloud Messaging or OneSignal to send updates, follow-ups, or nudges.
• Trigger from backend workflows or the AI agent itself

Optimize for install and re-engagement:

• Prompt users to install on first visit (but don’t be annoying).
• Show a welcome push after install.
• Track usage to trigger lifecycle-based messages (e.g. “You haven’t used your assistant in 3 days — need help?”).

4. Embedding AI agents in SaaS products: Borrow distribution

Instead of fighting for new users, why not embed your AI agent inside existing SaaS platforms?

Why it works:

• Built-in users: You’re tapping into an existing user base.
• Context-aware: The agent can use data from the host tool to personalize responses.
• Cross-promotion: If your agent adds value, the host platform might feature it.

How to build it:

Pick a SaaS platform with ecosystem reach:

• Good options: Notion, Slack, Airtable, HubSpot, Shopify, QuickBooks, Xero.
• Prioritize platforms with APIs and user-facing app directories.

Define a tight, useful use case:

• For example, a doc summarizer on Notion or a task updater on Slack.

Build the integration:

• Use the SaaS platform’s SDK or API.
• Authenticate via OAuth if needed.
• Hook into real-time events (e.g., message posted, record updated).

Add the agent logic:

• Use LangChain, Flowise, or Jotform AI Agents to handle prompts, context, and LLM replies.
• Pull relevant data from the host app

Package and distribute:

• List your app in the platform’s marketplace.
• Offer one-click installs or public links.
• Include demo workspaces or prebuilt templates to reduce setup time.

5. AI agents in niche communities: Slack, Discord, Reddit

Slack, Discord, and Reddit are powerful places to deploy AI agents that do real work inside conversations.

Why it works:

• Highly engaged users: Their users love experimenting with new AI tools.
• Built-in distribution: If your AI agent solves a problem, community members will spread the word for you.
• Become part of the workflow: AI agents can automate tasks, track data, or answer questions in real time.
• Less competition: Your AI agent stands out in a smaller, more engaged space.

How to build it:

Choose a platform:

• Slack: great for startups, teams, B2B workflows.
• Discord: perfect for AI, crypto, productivity, or creative communities.
• Reddit: slower to integrate, but great for exposure, feedback, and early users.

Join the community first:

• Don’t drop a bot cold — join, contribute, listen.
• Find the real pain point (repetitive questions, lost info, broken workflows).

Build a narrow, useful agent:

• For example, a bot that pings reminds on Slack or summarizes discussions on Discord.

Integrate with the platform:

• Use Slack API, Discord bots, or Reddit API.
• Authenticate with OAuth (for team-based installs).
• Store minimal data (channel, user ID, recent history).

Monitor, adjust, and grow:

• Watch usage closely.
• Add /commands, context-awareness, or integrations over time.
• Create a simple config UI so others can install or fork your bot into their own workspace.

There you have it. Just remember, deployment matters as much as intelligence. An AI agent that lives where work gets done is more useful, more used, and more valuable.