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Year: 2026

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You’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise SearchYou’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise SearchYou’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise SearchYou’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise SearchYou’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise SearchYou’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise Search

You’re Sitting on a Goldmine of Your Own Data: The Story of Glean and the Future of Enterprise Search

May112026

It was 2019. I was at Rubrik, the data security company I co‑founded, trying to pull up an internal document from a specific project in our knowledge base. Fifteen minutes of Slack searching. Another ten in Google Drive. More time in Jira, Confluence, and the company wiki. Every tool promised to make work faster. Instead, I was burning an hour on something I knew existed.

That was the moment I looked at my screen and said out loud: “I built search systems at Google for years—why can’t I find my own company’s data?”

“Arvind Jain couldn’t find his own company’s data at Rubrik. So in 2019, before ChatGPT, before the AI boom, he built Glean, the first enterprise generative AI company.”

The irony stung. I had spent more than a decade at Google as a distinguished engineer leading teams across Search, Maps, and YouTube, and then helped build Rubrik into one of the fastest growing companies in cloud data management. Yet inside my own organization, finding information was harder than searching the entire public web. Every SaaS tool was its own silo—Slack, Google Workspace, Jira, Salesforce, Confluence, Figma, GitHub, ServiceNow. Companies had spent billions digitizing their operations, only to leave employees with disconnected fragments: a knowledge graph splintered across hundreds of apps.

I walked away from a comfortable role at a successful company—a “cozy Google job,” as some called it—to fix a problem no one realized was crippling the modern workforce. I was not chasing hype. ChatGPT did not exist yet. The phrase “generative AI” meant nothing to most people. But I understood what nobody else seemed to grasp: the most valuable AI wouldn’t train on public internet data. It would train on your company’s private data, understand your permissions, and speak your language. If you could connect the dots across an enterprise’s fractured knowledge graph, you could build something exponentially more valuable than general‑purpose search.

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chatbot; The word Chatbots is displayed in white 3D letters on a black speech bubble with colorful lights underneath.
May112026

Automated Sales Chatbot: A No-Code Guide to Capturing and Converting More Leads

You wake up to a new lead form submission from 3 AM. By the time you reply at 9 AM, that person has already booked a call with a competitor. Sound familiar?

Most businesses take 42 hours to reply to a new lead. Forty‑two hours. By then, the person who filled out your form has found someone else, bought from a competitor, or simply forgotten they ever reached out. It gets worse: research shows that waiting just 30 minutes drops your odds of closing by a factor of 21. Half an hour is your window. Most of us miss it because we’re in a meeting, making dinner, or sleeping.

The solution isn’t to chain yourself to your phone 24/7. It’s to build an automated sales chatbot that handles the first reply, qualifies the lead, answers common questions, and nudges people toward a buying decision—whether you’re awake or not.

automated sales chatbot; A person holds a smartphone with a chatbot interface displayed, featuring a robot icon and speech bubbles.

This guide walks you through the exact process, using a library of prompts you can give to an AI assistant (like ChatGPT or Claude). No coding required. Just strategic thinking and a few hours of setup.

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sms marketing
Apr282026

SMS Marketing Strategy: How to Use AI Prompts for High-Converting Campaigns

You’ve heard the stats: SMS messages have open rates as high as 98%, and most are read within three minutes. But knowing that and actually building a compliant, high-converting SMS strategy are two very different things.

Where do you start? How do you write a message that doesn’t feel spammy? How do you segment your audience, stay legal, and measure success—all without getting overwhelmed?

SMS marketing strategy is no longer optional—it’s one of the fastest, most direct ways to reach your audience. With open rates as high as 98%, SMS gives you instant access to attention. But without the right structure, compliance, and messaging, it can quickly become ineffective or even damaging to your brand. This guide shows you how to build a high-converting SMS marketing strategy using proven AI-driven prompts.

Let’s dive in.

sms marketing strategy
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Kai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without FundingKai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without Funding

Kai Collective Case Study: How Fisayo Longe Built a £2M Fashion Brand Without Funding

Apr282026

Kai Collective is a London‑based contemporary womenswear brand founded by Nigerian‑born Fisayo Longe in 2016. Longe bootstrapped the company with an £8,000 ($11,000) loan from her mother after dropping out of university and leaving an auditing role at KPMG. The brand struggled for its first four years, generating only 23 orders at launch despite Longe’s 40,000 social‑media followers — a painful lesson that influence alone does not equal sales.

This Kai Collective case study highlights how Fisayo Longe navigated challenges to build her brand.

Everything changed in early 2020, when Longe wore a sheer, earth‑toned mesh dress to a BAFTA party. The Gaia dress went viral on Instagram and TikTok, sold out immediately, and generated an estimated £200,000 in revenue. By 2024 Kai Collective’s annual revenue had reached £2 million, with lifetime sales totaling approximately £6 million. The brand has been featured in Vogue, Elle, Marie Claire, and Forbes, and Longe was named to the Forbes 30 Under 30 Europe (Art & Culture) list in 2021.

Kai Collective remains 100% founder‑owned, has never taken outside funding, and prioritises community co‑design, size‑inclusive silhouettes (US 0–20+), and prints that celebrate the female form and African heritage. The brand’s enduring lesson: authenticity and resilience outweigh follower counts.

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