I’m Tonny, and I’m in the early stages of building a "Research as a Service" (RaaS) business. My goal is to help high-stakes decision-makers (executives, investors, founders) stop endlessly searching and start deciding faster by turning raw data into private, actionable knowledge assets.
How I use AI: Primarily as my core “research engine.” I orchestrate multiple AI tools to compress what used to take 30+ hours of manual research into focused 90-minute strategic sprints. This includes deep web/X searches, data synthesis, competitive intelligence, market validation, trend analysis, and turning it all into clear strategic deliverables.
Current automation systems I’m working with: 🤖🧐
- Multi-model orchestration (Grok + Claude/Gemini/Perplexity for cross-verification)
- Prompt chaining and structured workflows (building my “Conductor Method”😀)
- Exploring n8n / Make.com for automated research pipelines and client reporting
- Planning private RAG/knowledge base setups for repeat clients
Results I’m trying to achieve with AI infrastructure:
- Deliver consistently high-quality, customized research outputs at speed and scale
- Build repeatable systems so I can move from solo delivery to productized services/subscriptions
- Create a defensible service that combines AI speed with human strategy and curation
🔎Main business problem I’m solving:
Busy leaders and teams don’t have time (or the right tools🚫) to stay on top of fast-moving markets. They need trusted, synthesized insights without the noise.
I am looking forward to learning from everyone here, sharing workflows, and getting feedback on my infrastructure stack. Happy to collaborate or swap ideas on research automations!
Let’s build! 🚀🤖