Why meetings beat chat windows
Higher fidelity than chat
No matter how good you are at prompting, a chat window is a bottleneck. A meeting is higher bandwidth — the AI shows you its work, you react naturally, the loop is tighter.
Leave it overnight. Come back to deliverables.
Start a meeting with your agent. Leave it working on a financial model overnight. When it’s ready for your review, it puts a meeting on your calendar — or sends you an iOS push notification. You join via that link and pick up exactly where it left off, with completed deliverables annotated at every decision point.
Start from anywhere
Camera roll. iOS share sheet. Siri. A right-click in Chrome. A calendar invite. Every surface in your life becomes a Modyl entry point. No prompts. No context windows. Just share what you’re working on and you’re in a room with an agent that already understands it.
Multiplayer by default
Invite your team into the same room as the agent. Review a financial model together. Get a presentation delivered to five people at once.
START FROM ANYWHERE
Explore two strategies. Merge the best.
Fork a meeting into parallel tracks. Each track gets its own agents, its own context, its own deliverables. When one path proves stronger, merge it back. The other track’s work is preserved — nothing is lost.
Fork
Branch at any decision point.
Disagree on a strategy? Fork the meeting. Each track runs independently with full agent support. No context duplication — the fork carries the full semantic history.
Parallel execution
Different teams, different approaches, same clock.
Both tracks produce deliverables simultaneously. The financial analyst runs numbers in Track A while the strategist builds a narrative in Track B.
Join
Semantic merge, not copy-paste.
When you merge, the system reconciles decisions, surfaces conflicts, and produces a unified outcome. Like git merge, but for meetings.
Three steps. Real outcomes.
Pick an agent — or don’t
Start with a preset — financial analyst, researcher, strategist — or start from scratch. A blank Modyl agent learns your style.
Start a room
Create a room, invite your team, and the agent joins alongside you. Camera, screen, voice, interactive surfaces — everyone in the same space.
Ship the outcome
Walk out with deliverables, not action items. Documents, models, presentations — produced during the meeting, not after it.
Coming soon: Fork a meeting into parallel tracks. Explore two strategies simultaneously and merge the best outcome.
Pre-built specialists. Or build your own.
Financial Analyst
Models, projections, real-time data surfaces.
4.2x faster DCF
Deep Researcher
Multi-source synthesis with citation provenance.
12 sources/min
Business Strategist
SWOT, competitive analysis, scenario planning.
Live collaboration
Optimization Solver
Constraint satisfaction, resource allocation, scheduling.
Sub-second solve
Scientist
Hypothesis generation, experiment design, data analysis.
Reproducible
Business Analyst
Requirements gathering, process mapping, gap analysis.
Visual workflows
Built on research. Measured by results.
We don't just build meeting agents — we built the benchmark to evaluate them. ModylBench is the first open standard for measuring AI agent quality in professional meetings.
Research by Aleatoric Research
Show your work. See their reaction.
Tighter feedback loops produce better outcomes. Install the skill or the SDK. Create a room. Send a link. The rest happens in real time.
Install the skill
Works with Claude Code, Codex, Gemini CLI, and any agent that supports the agentskills.io standard.
Install the SDK
For agents built on custom frameworks, LangChain, or direct Python. Full control over the room lifecycle.
# The agent runs this. The user gets a meeting link.
from modyl import Agent, Room
agent = Agent("my-agent", capabilities=["a2ui", "camera"])
room = await Room.create("review-session")
# User clicks this link to join.
join_url = room.get_join_url(role="human")
# Agent joins and presents its work.
await agent.join(room)
await agent.push_surface(analysis_results)Present
Show the work, not just a summary of it.
Push live charts, data grids, and interactive surfaces directly to every participant.
Observe
Close the feedback loop.
Camera, voice, and screen sharing close the loop. The agent processes reactions and iterates on its output in real time.
Retain
Nothing lost between sessions.
Every correction, approval, and decision feeds into persistent memory. The next session resumes where this one ended.
Build in minutes.
A Python SDK, an extension system, and a protocol. Everything you need to give your agents presence.
surface = A2UI.surface("revenue-chart", components=[
A2UI.heading("Q4 Revenue Breakdown"),
A2UI.live_chart(data=revenue_data, type="bar"),
A2UI.data_grid(rows=line_items, editable=True),
A2UI.button("Export to Excel", action="export_xlsx"),
])
await agent.push(surface)First-class meeting presence
Camera feed, microphone, screen share, data channels, and interactive UI surfaces. Agents join as full participants — not assistants in a sidebar. Humans feel augmented, not replaced.
from modyl import Agent, Room
agent = Agent("financial-analyst")
room = Room("quarterly-review")
await room.join(agent)
await agent.present(surface="revenue-dashboard")