Participants: Max, Maha, Reiner (joined later) Duration: ~58 min Video: YouTube
Context
External signal from AI entrepreneurs/investors received around this call:
- Zurich pilot demonstrates a viable product — AI accompanying live conversations and intelligently intervening in real time.
- "Live Companion" concept (AI prompting participants to elevate dialogue quality) called out as a massive value-add.
Strategic direction
- Compliance product dropped. Commodity/scale territory owned by cloud giants; wrong fit for a tailored, niche team.
- Product reframed: AI working on actual conversations (record, rehearse, improve) — not roleplay in "cloudy nowhere-land" like generic coaching bots.
- Zurich = low-hanging fruit, not the whole market. General case: "conversations in defined systems" (organisations, team meetings) — predictable, repeatable structures. Zurich is special because NPS is already measured and conversations are already treated as productive capacity.
- Matches external investor framing: Zurich pilot = already-viable product.
Demo 1 — AI Call Assistant (live companion)
Max shared a working prototype running on the live call.
What it does today
- Real-time transcript with speaker diarisation (distinguished Maha and Reiner on a single mic).
- Tracks intentions per speaker.
- Tracks agenda items, ticks them off as covered.
- Suggests next moves to the host.
Validation so far
- Used on a real work meeting — valuable as a catch-up aid when attention drifts.
- Tested on a YouTube mock-interview video.
Open issues
- Recording etiquette / compliance (Chatham-House-style "Speaker 0/1" mitigation possible).
- UI rough.
- Notion has shipped a similar feature — competitive pressure rising.
Expansion ideas (Maha)
- Per-participant agent ("Reiner, you've been silent 5 min — bring a creative thought").
- "Dojo" for practising better conversations: teams legitimately record meetings, each member privately replays and improves.
- Chairperson/secretary-specific functions (decisions taken vs. decisions still vague).
- Differentiation required: Zoom / Teams will enter this space — "art of dialogue" slant is the moat.
Maps directly to the investor-flagged "Live Companion."
Demo 2 — Agent-based modelling
Feed text → system extracts actors → builds persona graph → simulates their conversation → produces report → lets you chat with any agent or poll the group.
Cases tested
- MiCA regulation (49 actors: central banks, journalists, owners, regulators, incl. Polymarket-style private vs. public stance modelling).
- Personal scenario: 20 people from Max's network reacting to "pivot from ecological to fintech?" — including a family member replying about spring weather (plausible real-life noise).
- Earlier Iran-US test blew up (~1000 actors — too expensive to simulate).
Framing: Max is reading Farmer's Making Sense of Chaos — bottom-up modelling of complex systems as the underlying lens.
Business applications (Maha)
- Convector — EU chemical-directive lobbying. Model the directive process, map coalition options, strengthen the proposal.
- Convector 360 assessment — use cross-evaluations from 25 leaders to project "who they'd be together in 5 years"; reframe proposal as an ongoing leadership modelling base.
- Phoenix Consultancy — leaders preparing for difficult conversations; presentation opportunity this evening.
- Unified leader tool = individual trajectories + strategic simulations.
Open risk (Max): any predictive claim needs backtesting on known past events before it's credible.
Other threads
- Meetup: blocked on lining up 3 speakers; date follows.
- Business connector (former founder of an early entrepreneurship network) — introduced via a mutual contact. Meeting Monday; possible meetup partner, building a new AI-included business club.
- Banker (blockchain in banking) — Maha offering warm intro Friday.
- Trade Republic signal: call centres shifting from chatbots → trained humans. More "Zurich-shaped" prospects in financial services.
- Family-dynamics conversations flagged as a longer-tail segment.
Tension to resolve
Investor enthusiasm points at the live companion (Demo 1). Near-term deal flow points at modelling (Demo 2, via Convector and Phoenix Consultancy). These are not the same product. Decision needed on where to double down — external pull vs. near-term revenue.
Action items
| Owner | Action |
|---|---|
| Max | Collect 3 speakers for the meetup, then set a date. |
| Max | Park compliance product direction. |
| Max | Test whether Demo 1 / Demo 2 resonate at tonight's Phoenix Consultancy meeting. |
| Maha | Reconnect with Convector — pitch modelling-enhanced lobbying proposal. |
| Maha | Follow up with Convector on 360 engagement, reframed with modelling angle. |
| Maha | Send banker contact to Max; approach if Max interested. |
| Maha | Meet the business connector Monday; evaluate as meetup partner. |
| Both | Design a backtesting protocol before making any predictive claims with Demo 2. |