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CASE STUDy

How We Helped Meet-Ting Go From Concept to Funded AI Startup

MVP Incubation
AI Infrastructure
Capital Raise
Multi-Agent Architecture

What stood out immediately with System7 was their depth in AI systems design. This wasn’t surface-level automation - they architected a proper multi-agent framework that gave Ting real intelligence and acting authority. They understood what we were building before we fully did.

Daniel Bulteel - Founder
3 Months
Time To Market
3rd
Product Hunt
1000s
Meetings Booked

Have a custom workflow built for you.

Challenge

During incubation, we defined a clear, ambitious vision for the product and laid the foundations to bring it to market.

An AI agent that:

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  • Lives in your inbox
  • Learns your scheduling preferences
  • Understands context inside live threads
  • Coordinates multiple parties autonomously
  • Integrates seamlessly with Google Calendar
  • Operates without dashboards, links, or friction

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This was not a simple scheduling tool.

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It required:

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  • Agent-based reasoning
  • Real-time decision-making
  • Preference modelling
  • Multi-step orchestration
  • Clean UX despite complex backend logic
  • Infrastructure that could scale beyond MVP

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The challenge was incubating a production-ready agentic AI system rather than a simple rules-based automation.

SOLUTION

System7 supported the incubation of Meet-Ting across product definition, AI architecture, and early technical execution.

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AI System Architecture

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We designed and implemented the core AI infrastructure using:

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  • LangChain framework
  • Multi-agent communication architecture
  • Agent orchestration logic
  • Context-aware thread parsing

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Rather than a single monolithic assistant, Ting was built as a coordinated multi-agent system.

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Specialised agents handle:

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  • Availability reasoning
  • Calendar interpretation
  • Conversation Parsing for time and other meeting details intent
  • Decision routing
  • Booking execution

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These agents communicate and pass structured outputs between each other, allowing Ting to operate with controlled autonomy inside live email threads.

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This created a scalable foundation instead of a fragile prototype.

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Google-Native AI Infrastructure

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Meet-Ting leverages:

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  • Google Cloud infrastructure
  • Gemini-powered reasoning layers
  • Deep integration with Google Calendar
  • Secure authentication workflows

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Their acceptance into the Google AI Startup Program validated both the technical direction and product ambition.

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The architecture we built positioned them for that level of partnership.

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MVP Development

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As part of the incubation process, we focused on proving one core promise:

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Meetings should book themselves inside real email conversations.

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The MVP included:

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  • Email thread participation logic
  • AI-based time suggestion generation
  • Autonomous booking confirmation
  • Rescheduling intelligence
  • Backend agent orchestration

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No feature bloat.

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No UI-heavy distraction, simple setup dashboard.

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Focal point on AI and agentic inside live workflows.

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Fundraising Enablement

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The incubated product gave investors a working demonstration of the company’s core technology, allowing them to evaluate:

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  • Real product, not slides
  • Functional multi-agent orchestration
  • Infrastructure built for scale
  • Early usage validation

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This directly supported Meet-Ting’s successful £250k raise.

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Product Hunt Launches

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Meet-Ting has had multiple successful launches on Product Hunt, including:

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🏆 3rd Place Product of the Day
🏅 Top Badge Placement

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This provided early public validation and social proof.

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RESULTS

Meet-Ting Today

£250k
Pre-Seed Raised

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3rd
Product Hunt

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Google AI
Startup Program

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Multi-Agent
LangChain Architecture

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1,000s
Meetings Booked

INDUSTRY
SaaS
FUNDING
£250k
STAGE
Pre-Seed
HQ
London, UK