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Why Companies Are Paying 260% More for AI Context
PLUS: 3 Startup Ideas in this space based on groundbreaking research by Anthropic
The Opportunity Scanner
September 17, 2025
Hello there,
In today's edition, we're uncovering the $100 billion context problem that's secretly choking enterprise AI - and the massive opportunity hiding in plain sight. This edition reveals Anthropic's shocking research on why context curation, not AI itself, is the real goldmine, plus 3 startup ideas ready to capture it.
Don't worry, we've made it so simple even a 10-year-old can understand.
The Hidden Bottleneck in AI Nobody's Talking About
Anthropic's latest research reveals something counterintuitive: the biggest barrier to AI deployment isn't the AI itself - it's context.
Imagine walking into a movie halfway through. Even the smartest person can't make sense of what's happening without knowing the first hour. That's exactly what's happening with enterprise AI right now.
What the Data Shows
When Anthropic analyzed their API customers - businesses that wire Claude directly into their systems - they found a striking pattern. For every 1% increase in contextual information companies provide, they only get 0.38% increase in useful output.
API customers pay per token (like paying per word in a text message). When companies consistently provide extensive context despite the cost, they're proving these tasks genuinely need it.
Nearly half of enterprise AI usage centers on software development. Why? Because code repositories already centralize the context AI needs. But notice what's missing - complex business strategy, customer management, market analysis.
The Real Problem is Context
The most valuable AI applications are being held back by scattered information. Want AI to develop a sales strategy for your biggest client? You need:
CRM data (easy - it's digital)
Your sales rep's relationship insights (locked in someone's head)
Market intelligence (scattered across departments)
Historical context (buried in old emails and conversations)
Look at the progression: "answer questions about store merchandise" versus "develop new biological research methods." The complexity gap is massive.
The data proves this intuition. For every 1% increase in contextual information companies provide, they only get 0.38% increase in useful output - revealing diminishing returns that get worse as tasks become more complex.
This scatter plot demonstrates the core bottleneck: it's not that AI can't handle complex problems - businesses can't efficiently organize the context AI needs to solve them.
3 Startup Ideas for you
Companies that solve the context problem first will unlock AI's potential for the most valuable business challenges. We're talking about systems that centralize tacit knowledge, create intelligent context aggregation, and build information pipelines that feed AI the right background for complex decisions.
The next wave of AI transformation belongs to whoever cracks the context code first. Here are some low-cost startup ideas for you to start building immediately:
Category | Description |
|---|---|
Problem | Lawyers waste significant time manually gathering case precedents, regulatory updates, and client history before drafting documents. |
Solution | A specialized AI context engine for law firms that assembles all necessary legal, regulatory, and client context for AI-powered brief generation. |
Revenue Potential | High — Vertical SaaS for law firms. Premium pricing justified ($1000s per month per firm). Legal tech market growing rapidly (~$30B+). |
TaskContext | |
|---|---|
Problem | AI tools often fail because they lack the right context from scattered sources (CRM, Slack, email, project tools), forcing users to manually assemble info. |
Solution | Middleware that pulls data from multiple systems and packages the most relevant context automatically, optimized for the AI’s task at hand. |
Revenue Potential | Very High — Infrastructure play; priced per seat or API usage. TAM overlaps AI middleware & workflow automation (multi-billion). |
Convo Capture | |
|---|---|
Problem | Critical insights from client meetings and sales calls often get lost or never entered into CRMs, leading to missed opportunities and weaker relationships. |
Solution | An AI “observer” that analyzes conversations in real time, extracts client preferences, decision-making patterns, and builds dynamic relationship graphs for CRM enrichment. |
Revenue Potential | High — SaaS subscription for enterprises, upsell via advanced analytics, integration fees. Market: Sales intelligence & CRM (~$50B+). |
Thanks for reading! Share this with your aspiring entrepreneur friends who are planning to build something big. We promise these are the most data-backed and thoroughly researched ideas around enterprise AI context solutions that you'll find anywhere on the internet. The next AI unicorn is hiding in this bottleneck - don't let someone else find it first. Okay Bye!