Latest in AI…

India’s company success…save money!

The story in simple terms:

Meesho, one of India’s leading e-commerce players, just found a way to slice its customer support costs by 75% and it’s all thanks to AI.

Here’s what’s happening:

• AI on the line: Meesho introduced a generative AI-powered voice bot that handles 60,000 calls daily in both Hindi and English. It’s a first-of-its-kind move among Indian e-commerce platforms.

• Why it matters: With over 160 million customers (mostly from smaller towns and villages), Meesho relies heavily on solid customer support. The AI bot cuts call handling times in half while resolving 95% of queries without needing human backup.

• The tech behind it: Meesho isn’t reinventing the wheel. Instead of building its own AI model, it’s tweaking existing tools to understand regional accents, low-end phone audio, and noisy backgrounds (think honking buses).

• Human touch: While the bot handles the basics, human agents are still around to manage more complex queries—so no, it’s not about replacing jobs.

Our take:

This is a glimpse into how AI can help businesses grow without sacrificing customer care. Meesho’s approach of adapting AI to local challenges instead of going all-in on building new tech is smart. Maybe it’s not about who builds the fanciest system but who uses it best. MAYBE…

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Anthropic’s $8 Billion Bet on Smarter AI Connections

The story in simple terms:

Anthropic, fresh off an $8 billion investment from Amazon, is rolling out a game-changing way to connect AI assistants with the tools and data they need. It’s called the Model Context Protocol (MCP), and it could be the key to making AI smarter, faster, and way more useful.

Here’s what’s exciting about it:

• What is MCP? MCP is an open-source standard designed to help AI chatbots (and other tools) pull data from apps, content repositories, and business software. Essentially, it bridges the gap between AI and data silos.

• Why does it matter? AI assistants today often struggle to integrate with different systems, making seamless workflows hard to achieve. MCP simplifies this by allowing developers to set up two-way data connections that are easy to scale.

• Big names are already on board. Companies like Block and Apollo are using MCP, and developer platforms like Replit and Sourcegraph are adding support.

• How does it work? Developers can create “MCP servers” to expose data and “MCP clients” to build apps that interact with that data. For example, Anthropic’s Claude AI integrated with GitHub via MCP to create repos and pull requests in under an hour.

• Competition is heating up. OpenAI has a similar feature called “Work with Apps,” but it’s not open-source. MCP’s future hinges on whether developers and industry rivals adopt the protocol.

Here’s What I Think:

Anthropic’s vision for a connected AI ecosystem is ambitious, and the Amazon backing certainly gives it muscle. But in a competitive space, it’s all about adoption. If MCP can deliver on its promise, it could be a game-changer for AI’s role in our workflows.

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