When I examined user behavior, I noticed something subtle: people weren’t really searching. They were voicing half-formed ideas — almost thinking out loud. Traditional filters and keyword search didn’t match that mental process.

 

So I reframed the problem:What if users could just ask — and the system understood the intent, retained the context, and served the answer?

 

That’s why I called it Thought. Unlike search, which matches keywords, Thought mirrors cognition:

• Captures messy intent instead of requiring polished queries.

• Retains context, like memory in a real conversation.

• Responds visually and naturally, so answers feel immediate and human.

This shaped the foundation of AI-powered conversational search — where users type naturally (“Show me all Vodafone contracts with COLA clause”), the system understands nuance, remembers context, and responds in ways that reduce back-and-forth.

 

But here’s where Thought goes beyond tools like ChatGPT:

• Domain-specific intelligence → It’s grounded in contracts and clauses, so answers are precise and trustworthy.

• Visual + conversational hybrid → Results aren’t just text; they become clause explorers, dashboards, and summaries that lawyers can act on.

• Task-oriented memory → It remembers context across workflows (“the NDA I asked about earlier”), not just within a single chat.

• Explainability → Every answer shows why (the exact clause, rule, or data source), building trust in high-stakes legal work.

 

In short, Thought isn’t just about delivering answers — it’s about delivering trusted, actionable insights in the way professionals actually think and work.