Skip to main content

20 One-Liners

Context Intelligence Platform

Purpose: Quick, memorable pitches for different contexts (elevator, email, social, press) Last Updated: November 26, 2025

Category: Problem/Solution​

1. The Conversation Loss Problem​

"Developers waste 2-3 hours daily re-asking AI assistants the same questions because conversations disappear—we built the first AI conversation memory system to fix that."

2. Institutional Knowledge From AI​

"Turn your Claude/Copilot conversations into permanent, searchable institutional knowledge with automatic git commit linking and team analytics."

3. The AI ROI Blackbox​

"Companies spend $50-100/month per developer on AI tools but can't measure ROI—we provide the analytics to prove AI is actually working."

Category: Market Opportunity​

4. $26B Greenfield Market​

"We're creating a new category—AI conversation management—in the $26 billion GenAI market with zero direct competitors."

5. 100M Developers Problem​

"100 million developers now use AI assistants daily, generating 5 billion conversations annually that all disappear into the void."

6. First-Mover Advantage​

"We have 12-18 months to own the AI conversation management category before GitHub or OpenAI notices this $14 billion opportunity."

Category: Product Differentiation​

7. Hybrid Search Magic​

"Our hybrid search finds 'authentication bug' even when you wrote 'JWT security'—95% relevance in under 100 milliseconds."

"We're the missing link between AI conversations and git commits—automatically correlating discussions to code changes for complete audit trails."

9. Multi-Provider Moat​

"Unlike ChatGPT Teams (OpenAI-only), we support every AI assistant (Claude, Copilot, Gemini, Cursor)—the Switzerland of AI conversation management."

Category: Business Model​

10. Freemium SaaS Play​

"Classic PLG: free tier for viral growth, $15/month Pro for power users, $50/month Enterprise for Fortune 500 compliance."

11. Unit Economics Perfection​

"LTV/CAC ratio of 5:1 across all segments with 85% gross margins—SaaS investors' dream metrics."

12. Land-and-Expand Model​

"Individual developers start free, convert to Pro at $15/month, then we upsell entire teams at $1K-5K/month when managers see the value."

Category: Traction / Validation​

13. Technical Architecture Complete​

"We've completed what most startups skip—a production-ready architecture (IEEE 1016 compliant SDD) with 383 test specifications and SOC 2 security design."

14. Path to Series A​

"With this $2M seed, we'll hit $180K ARR in 12 months and raise a $10M Series A at $40M valuation with $1.8M ARR."

15. Conservative $90M ARR Path​

"Our 5-year projection shows $90M ARR with 500K users—and that's assuming zero virality and organic growth only."

Category: Competitive Moat​

16. Network Effects at Scale​

"More conversations = better search = higher retention—classic network effects that make us exponentially harder to displace."

17. Data Moat + Algorithm IP​

"Our proprietary 3-signal correlation algorithm (temporal + semantic + explicit) gets smarter with every conversation-commit pair."

18. Enterprise Lock-In​

"Once a Fortune 500 company deploys our SSO, integrates our IDE plugins, and trains their team—switching costs become prohibitive."

Category: Vision / Big Picture​

19. The AI Productivity Layer​

"We're building the productivity layer for the AI era—every knowledge worker will need conversation memory as AI becomes ubiquitous."

20. From Ephemeral Chats to Permanent Assets​

"Today, AI conversations are ephemeral noise. Tomorrow, they're your company's most valuable knowledge assets—and we're making that transition happen."

Usage Guide​

For Investor Emails (Cold Outreach)​

Use #4, #11, #14

Example: "Hi [Name], we're creating a new category—AI conversation management—in the $26B GenAI market with zero direct competitors. LTV/CAC ratio of 5:1 with 85% gross margins. With this $2M seed, we'll hit $1.8M ARR and raise Series A at $40M valuation. 15-minute call to discuss?"

For Twitter/X Thread​

Use #1, #8, #9

Example: "🧵 Developers waste 2-3 hours daily re-asking AI the same questions.

We built the missing link between AI conversations and git commits.

Unlike ChatGPT Teams, we support every AI assistant—the Switzerland of conversation management.

Here's how it works... [thread]"

For Conference Introductions​

Use #2, #7, #16

Example: "We turn Claude/Copilot conversations into searchable institutional knowledge. Our hybrid search finds 'auth bug' even when you wrote 'JWT security'—95% relevance in <100ms. Network effects make us exponentially harder to displace as we scale."

For Press / TechCrunch​

Use #5, #6, #13

Example: "100M developers now use AI assistants daily, generating 5B conversations annually that disappear. We have 12-18 months to own this category before Big Tech notices. Unlike most startups, we've shipped production-ready architecture (IEEE 1016 compliant) before our seed round."

For Slack/Discord Communities​

Use #1, #3, #12

Example: "Ever waste hours re-asking Claude the same question? We built AI conversation memory to fix that. Companies can't measure AI ROI—we provide the analytics. Start free, convert to Pro at $15/month, then we upsell your team when managers see value. Try it: [link]"

For LinkedIn (Executive Audience)​

Use #3, #15, #19

Example: "Companies spend $50-100/month per developer on AI tools but can't measure ROI. We're building the productivity layer for the AI era—conversation memory as AI becomes ubiquitous. Conservative projections: $90M ARR by Year 5. This is the future of knowledge work."

For Product Hunt Launch​

Use #2, #7, #20

Example: "🚀 Context Intelligence Platform: Turn AI conversations into permanent, searchable knowledge

  • Hybrid search: finds 'auth bug' even when you wrote 'JWT security'
  • Auto-links conversations to git commits
  • From ephemeral chats to permanent company assets

Free forever tier. Try it today! [link]"

Variations by Audience​

For Technical Founders/CTOs​

Focus: Architecture, performance, technical moat "Our hybrid search (keyword + semantic with RRF fusion) delivers 95% relevance in <100ms p95 latency at 50M+ message scale—built on PostgreSQL + Weaviate with multi-tenant RLS for database-level isolation."

For Enterprise Buyers​

Focus: Compliance, security, ROI "SOC 2 Type II certified, GDPR compliant, on-premise deployment option, and complete audit trails for AI-generated code—plus measurable productivity gains of 15-20% in enterprise pilots."

For Developers/Users​

Focus: Pain relief, time savings, ease of use "Never lose an AI conversation again—automatic capture, instant search, and git commit linking that saves you 10-15 hours per week."

For Investors​

Focus: Market size, unit economics, exit potential "$14.7B TAM, LTV/CAC of 5:1, 85% gross margins, and clear acquisition path to GitHub/GitLab/Atlassian at 30-50x ARR multiples."

Tips for Delivery:

  1. Start with the problem (#1, #5) to establish empathy
  2. Follow with the solution (#2, #8) to show you get it
  3. End with traction or moat (#11, #16) to prove credibility
  4. Adapt to context: Investor? Use financials. Developer? Use technical details.
  5. Memorize 3-5 favorites for natural delivery

Document Version: 1.0 Last Updated: November 26, 2025