Tech

Chatbots are Predicted to Reduce Business Costs by 2022

Published

6 years ago

November 7, 2019

Artificial Intelligence is taking businesses to another level. And chatbots is one kind of Artificial Intelligence that increases productivity and reduces costs. It was Oracle which predicted that 80% of businesses plan will be using chatbots by 2020. And it also predicted that chatbots are expected to reduce business costs by $8 billion by 2022.

Avi Benezra, who is the CTO of SnatchBot, said that chatbots really helped them cut the costs and it bumped up the conversion rates. That is why others are now adopting chatbots more rapidly.

AI technology is indeed changing every aspect of our lives. Now chatbots aren’t just about gadgets but there are also Chatbot lawyers, Chatbot therapists and more. Chatbots are also changing the business-to-consumer (B2C), business-to business (B2B) and business-to-employee (B2E).

For a single task a single bot is enough. The task takes place through a fixed set of scenarios in the single use bot. But when there are multiple tasks then multi-tasking bots come to play.

The Chatbot platform must provide the ability to track and streamline multiple functions simultaneously within a single task Chatbot. And it is important to have the ability to create and deploy a multi-purpose chatbot for communication.

For multiple tasks to be performed the chosen platform must offer pre-built bots. And these bots must be ready to deploy in order to address specific tasks. These tasks could consist of customer support, lead generation, and many more. Also the bots must be customizable. This feature makes it easy to further interactions according to the type of business you are dealing with.

The platform for the Chatbot development program must have customized user interfaces.There is a preferred channel for every Chatbot. And it could be various channels like websites, mobile apps, social media, email and SMS. Bots can also interact with Skype, Slack and Telegram, but it’s mostly for corporate purposes.

NLP and Speech Support are the most used tools of best chatbots platform in field of language and speech. These tools help them to train and to maintain the accurate interactions, and conversations through both text and speech. By the NLP and Speech Support chatbots understand the user and give relevant response.

Bots can perfect their natural language processing capabilities with the help of Machine learning. Therefore the chatbots must be smart and intelligent so that they will gauge and remember the data and learn from it. The interactions with customers will improve over time and they collect the information from the conversations. This way they can serve the customer’s request once they hone their machine learning and language.

An internal bridging map is vital for the Chatbot platform. It helps with the sharing of messages between users. Moreover, chatbots and the cross-functional systems should also have the bridging. A bridge records the success and the failures. It categorizes messages, so that the bot manager can have a comprehensive understanding of the chatbots function.

Chatbots are indeed the future of business, as they will help cut the costs. But proper research is necessary to build a right bot platform. The features must match the functionality of the chatbot used in a particular business.

Tech

My Main AI Turns Complex Workflows into Simple, Voice-Driven Conversations

Published

2 months ago

February 9, 2026

Jonathan Grilli

Photo Courtesy of My Main AI Inc.

By: Chelsie Carvajal

Managing modern workflows often means juggling dashboards, documents, and long email threads before a single task is complete. My Main AI Inc, an AI technology platform that spans text, image, voice, and video, has built a system where many of those steps can be handled through spoken or written prompts instead of manual clicks.

Turning Tasks Into Conversations

My Main AI groups several automation tools around a voice and chat layer so users can move through work by giving instructions rather than configuring each step. The platform lists AI Web Chat, AI Realtime Voice Chat, AI Speech‑to‑Text Pro, and AI Text‑to‑Speech engines from providers such as Lemonfox, Speechify, and IBM Watson, creating a loop between spoken input and generated output.

Speech‑to‑text tools support accurate transcription of audio content in multiple languages, with options to translate those recordings into English. That capability gives businesses a way to record meetings, calls, or field conversations, then convert the results into text that can be summarized, edited, and turned into documents or scripts. Text‑to‑speech tools, including multi‑voice synthesis with up to 20 voices and SSML controls, take written content in the other direction, producing voiceovers for training, marketing, and support material.

Chat assistants extend the same pattern to files and websites. My Main AI lists AI Chat PDF, AI Chat CSV, and AI Web Chat, which allow users to ask questions of documents or site content through natural language prompts. Instead of sorting through long reports, a user can query a file, receive concise answers, and then send follow‑up requests to generate emails, briefs, or summaries in the same environment.

From Content Pipelines to Voice‑Led Workflows

The company reports that its platform connects to more than 100 models from OpenAI, Anthropic, Google Gemini, xAI, Amazon Bedrock and Nova, Perplexity, DeepSeek, Flux, Nano Banana, Google Veo, and Stable Diffusion 3.5 Flash. Public materials state that these models support text, image, voice, and video generation in more than 53 languages, giving the voice‑driven tools reach across several regions and markets.

Content creation sits at the center of many of these workflows. My Main AI offers modules for blog posts, email campaigns, ad copy, social captions, video scripts, and structured frameworks such as AIDA, PAS, BAB, and PPPP. A user can dictate key points or paste a brief into the chat, receive draft text, ask the assistant to adjust tone or length, and then pass the result into voice synthesis to create a narrated version.

Visual tools fit into the same flow. DALL·E 3 HD, Stable Image Ultra, and an AI Photo Studio support image creation, product mock‑ups, background changes, and multiple variations from a single upload. AI Image to Video and text‑to‑video connections with engines such as Sora and Google Veo, alongside an AI Avatar feature labeled “coming soon,” make it possible to turn a spoken or typed brief into images, then into short clips that accompany the newly generated audio.

Why Businesses See Conversation as Infrastructure

Company data shared with partners cites more than 77,000 customers worldwide, annual revenue near 3 million dollars, and monthly revenue growth around 250,000 dollars, driven largely by subscription sales. The 49‑dollar plan is described as the best‑selling tier, with My Main AI presenting it as the entry point to the broader suite of conversational and automation tools.

Business‑oriented features show how these voice‑driven workflows connect to operations. The platform lists payment gateways such as AWDpay and Coinremitter, integrations with Stripe, Xero, HubSpot, and Mailchimp, and tools for SEO, finance analytics, dynamic pricing, wallet systems, and referrals. A manager can ask a chat assistant to pull figures, draft a report, and prepare customer messages, then move directly into sending campaigns or reviewing payments through linked services.

Company communications describe ongoing work on proprietary models, expanded training flows from text, PDFs, and URLs, and deeper tools for chat, analytics, and video. That roadmap suggests that My Main AI views conversation—spoken or typed—as a central control surface for complex workflows, with automation stepping in behind the scenes so users can focus on clear instructions rather than manual configuration.