Context is fragmented
Critical knowledge remains scattered across conversations, people, and disconnected tools.
JUNO AI / company pitch
The shared operating layer for people and AI agents.
YYLO helps organizations coordinate agents, preserve shared knowledge, and evaluate outcomes—across users, workflows, and AI providers.
Available now Three public open-source products · working platform · internal validation
Shared contextWhat the organization knows
YYLOCoordinate · remember · evaluate
People + agentsWork with continuity and control
Measurable outcomes
One shared layerfor organizational context
Three productscoordination, memory, evaluation
Many providerswithout dependence on one model
01 / Problem
Agent capability is rising. Organizational readiness is not.
Companies can access powerful AI, but the context and operating practices around it remain fragmented.
Coordination is inconsistent
Teams lack one repeatable way to direct people and agents across providers.
Quality is hard to prove
Organizations need clearer evidence of what happened, what worked, and what should improve.
02 / Solution
Move from isolated AI tools to a shared way of working.
YYLO connects organizational knowledge, coordinated action, and outcome evaluation in one modular platform.
- ContextGive people and authorized agents shared knowledge.
- CoordinationRun repeatable work across agents and providers.
- EvaluationRetain evidence and improve future outcomes.
03 / Product
One system. Three focused products.
Each product works independently. Together, they connect memory, action, and learning.
01Coordinate
YYLO CLI
A provider-independent way to coordinate AI agents and repeatable workflows with visibility and control.
02Remember
YYLO Ledger
The shared source of truth for tasks, decisions, knowledge, workflows, and evidence available to people and authorized agents.
03Evaluate
YYLO Benchmark
A structured way to compare agent attempts, retain evidence, and learn which approaches produce better outcomes.
04 / Value
Make AI-assisted work repeatable, visible, and governable.
- Give authorized agents the context they need
- Preserve decisions and knowledge across users and tools
- Coordinate repeatable work without provider lock-in
- Evaluate outcomes instead of measuring activity alone
05 / Why now
Organizations are choosing how AI work will operate.
Capability is accelerating faster than the systems needed to coordinate it responsibly.
Agents are becoming coworkers
AI is moving from individual experiments into everyday organizational workflows.
The stack is becoming multi-provider
Organizations increasingly need continuity across models, agents, and interfaces.
The operating layer is still open
The standards for context, coordination, governance, and evaluation are being formed now.
06 / Market + model
Start with software teams. Expand wherever people and agents share knowledge.
Initial market
Software organizations using multiple AI tools
Engineering leaders, platform teams, developer-productivity teams, and technical founders need continuity, visibility, and quality across agents.
Go to market
Open-source, product-led entry
Earn developer trust and learn from real workflows, then develop repeatable team adoption through design partnerships and pilots.
Planned model
Recurring team and enterprise software
Future paid capabilities can include collaboration, administration, governance, analytics, integrations, managed services, and support.
Direction, not current traction: paid team capabilities, design partnerships, pilots, and enterprise expansion are goals under validation.
07 / Defensibility
The source of truth becomes more valuable as the organization builds on it.
Ledger is designed to become the trusted context layer for people, agents, and business systems.
As an organization adds decisions, workflows, policies, integrations, and relationships between information, the platform becomes embedded in how work gets done.
The moat comes from continuity, accumulated organizational knowledge, operating experience, and trust—not artificial data lock-in.
Shared contextWorkflowsIntegrationsOperational historyCompounding trust
08 / Progress
Built the foundation. Next, prove the commercial path.
Available now
What we have achieved
- Three working, publicly available open-source products
- Public distribution, website, and product documentation
- Internal use of YYLO to coordinate YYLO development
- A clear platform architecture and commercial direction
Next 6–12 months
What we intend to validate
- Recruit design partners and early-adopter software teams
- Run structured discovery and measurable pilots
- Define the first paid team offering and pricing
- Show repeatable activation and evidence of willingness to pay
- Strengthen the advisory network and fundraising readiness
Design partners · advisors · early investors
Help shape the operating layer for people and AI agents.
We are looking for software organizations and partners who want to make AI-assisted work more continuous, measurable, and governable.
JUNO AI INC. · support@yylo.dev