Mentioned in 0 AI use cases across 0 industries
Think of a future MBA program that behaves more like Netflix and Duolingo combined: it recommends the right courses, adapts in real time to each learner, uses AI tutors instead of TAs for basic questions, and plugs into real company data and tools instead of static textbooks.
Think of this as a smart digital prospector for sales teams: instead of humans manually hunting for potential customers and guessing who might be interested, AI tools automatically scan data, score which prospects are most likely to buy, and surface ready-to-contact leads for reps.
Think of this as a super-fast recruiting assistant that can read thousands of resumes, shortlist matches, and help manage the hiring workflow so your managers only spend time on the most promising candidates.
This is like a 24/7 digital career advisor that talks to workers, helps them understand how AI will affect their jobs, and suggests skills and training paths so they can stay employable.
Think of Findem as a supercharged hiring detective that scans millions of public signals about people and turns them into a short, qualified list of candidates who actually match what you need—skills, experience, and diversity goals—before your recruiters ever start manual sourcing.
Think of it as a super-fast digital recruiter that scans huge piles of resumes and job descriptions in seconds, shortlists the best matches, and keeps candidates moving quickly through the hiring process instead of getting stuck in inboxes and spreadsheets.
This is like giving your sales team a smart metal detector that scans a huge crowd and quietly points to the people most likely to buy from you right now, based on thousands of subtle signals they couldn’t see themselves.
This is like having an always-on digital analyst that reads every customer review, support ticket, social media post, and survey response, then tells you in plain language whether people are happy or unhappy and why.
This is like giving your company a super-listening ear that reads all customer comments, reviews, and survey answers and tells you, in plain language, how people feel and why they’re happy or upset.
This is like giving your company a super‑listener that reads what customers write (emails, chats, reviews, social posts) and instantly tells you if they’re happy, angry, or confused—at large scale and in real time.
This is like having an always-on assistant that reads every customer message, review, or chat and tells you in plain language whether people are happy, angry, or confused – then rolls that up into clear dashboards for your teams.
Think of Kaaj as an AI-powered underwriter that sits next to your credit team. It reads all the financial data, policies and historical loans, then automatically proposes whether to approve, decline or price a loan, while keeping a clear audit trail for regulators.
Imagine having millions of online conversations automatically summarized into a simple daily briefing that tells you what people feel about your brand, your content, and your competitors. That’s what AI social listening does.
Think of this as using a very smart calculator to help HR sift through candidates and employee data faster and more consistently than humans can, while HR still makes the final calls.
Imagine a super-fast, tireless credit analyst that has read millions of past loan files, market reports, and financial statements. It helps human underwriters decide who to lend to, on what terms, and with what risks—more quickly and consistently than a traditional team doing everything by hand.
Think of this as a smarter, faster credit and insurance judge that looks at far more information than a human underwriter could, then makes a decision in seconds instead of days.
This is like giving your loan operations team a super-smart assistant that reads all the documents, checks rules, and suggests approve/decline decisions so humans only handle the tricky edge cases.
This is like having a 24/7 smart radar that listens to everything people say online about your brand, competitors, and topics you care about—and then summarizes what matters so your team can react fast.
Think of this as a smart ad-placing assistant that studies who actually clicks and buys from your ads on social platforms, then automatically shows future ads to more people who look and behave like those best customers.
Imagine your recruiting team got a super-fast, tireless assistant who can read every resume, screen every candidate, and flag the best matches 24/7, while also learning from 20 years of what has and hasn’t worked in hiring.