Most AI Chatbots Are Stuck in 2023. Ours Isn't.
Most AI Chatbots Are Stuck in 2023. Ours Isn't.
Ask ChatGPT about something that happened last month. Watch it confidently give you wrong information—or worse, make something up.
That's not a bug. That's how most AI works.
Every AI model has a knowledge cutoff. GPT-4's training ended months ago. Claude's too. They don't know what happened yesterday. They don't know your company's latest product update. They don't know the research paper published this morning.
We fixed this.
The Problem: Static AI in a Dynamic World
| What You Ask | What Static AI Says | What Actually Happened |
|---|---|---|
| "What's the latest on [competitor]?" | Info from 6+ months ago | They launched 3 new products |
| "Summarize this research paper" | "I don't have access to that" | Paper is publicly available |
| "What are current best practices for X?" | Outdated recommendations | Industry moved on |
Static AI is confidently wrong. And in business, confidently wrong is expensive.
Our Solution: RAG That Actually Works
RAG = Retrieval-Augmented Generation
Instead of relying on frozen training data, our AI agents pull live information from:
- Your knowledge base — Documents, PDFs, internal wikis
- The web — Real-time search via Tavily
- Multiple sources simultaneously — Blended search that cross-references
When you ask a question, we don't guess. We look it up, synthesize it, and cite our sources.
What This Looks Like in Practice
You: "What did [competitor] announce at their conference yesterday?"
Static AI: "I don't have information about events after my training cutoff..."
Wysor: "Yesterday at [Conference], [Competitor] announced three major updates: [specific details with source links]"
The Technical Edge
| Feature | Other Platforms | Wysor |
|---|---|---|
| Knowledge cutoff | 6-12 months old | Real-time |
| Your documents | Manual upload, limited | 50MB files, auto-indexed |
| Web search | Bolt-on, unreliable | Native, always-on option |
| Source citations | Rarely | Every response |
| Context awareness | Generic retrieval | Understands what you actually need |
How It Works
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Semantic Search — We understand meaning, not just keywords. Ask for "revenue growth strategies" and we find relevant content even if those exact words aren't used.
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Multi-Source Blending — Web results + your documents + conversation context, all synthesized into one coherent answer.
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1536-Dimension Embeddings — OpenAI's best embedding model ensures nothing relevant gets missed.
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Sub-Second Retrieval — Massive knowledge bases, instant responses.
Use Cases That Actually Matter
Research That Doesn't Suck
Stop opening 20 tabs. Ask a question, get a synthesized answer with sources.
Documentation That Stays Current
Upload your docs once. Every AI agent in your workspace has access. Updates propagate instantly.
Competitive Intelligence
"What's [competitor] doing?" gets a real answer, not a guess from last year's training data.
Customer Support That's Actually Helpful
Your support agents have access to every product doc, every FAQ, every policy—without memorizing anything.
The Bottom Line
AI that doesn't know what happened yesterday isn't intelligent. It's a parlor trick.
Our RAG system turns AI assistants into actual research partners—ones that cite their sources and admit when they don't know something.
Stop getting confidently wrong answers. Try it yourself