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Standpoint Labs

AI Agents Are Here. Understanding Isn’t.

See decisions from every standpoint. Deploy AI that coordinates, not just connects.

We build infrastructure for perspective-aware AI.

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The Agent Babysitter Problem

You have a team of 8 AI agents. One makes a decision without understanding how it affects the others. Now multiply that by 100 agents.

The problem isn’t wrong instructions. It’s that agents don’t have access to the full picture. They don’t understand implications. They don’t see knock-on effects.

Are you an agent babysitter? Or do you have infrastructure that lets them coordinate?

No One’s Job

Engineering just changed the onboarding process to accommodate new AI tools.

Legal updated the employment contract for compliance.

Marketing redesigned the job posting template.

Linda in HR found out when three new hires showed up confused on day one.

Why? Because no one’s job is to understand how changes ripple through the system.

Until now.

And it’s about to get exponentially worse as AI agents multiply the coordination problem.

Current AI tools can’t solve this. Here’s why.

The Context Graph Revolution Is Incomplete

This is the year of context graphs. Every AI company is racing to give their systems more organizational context.

That’s necessary. But it’s not sufficient.

Context graphs give AI ACCESS to information. They don’t model how it RELATES. They don’t track IMPLICATIONS. They don’t COORDINATE actions.

Greater autonomy + Limited understanding = Chaos

We’re the missing layer.

Infrastructure for Perspective-Aware AI

Standpoint Core

Core maps the standpoints.

A relational core that maps what connections mean to each party. Not just that connections exist, but what matters, why, and how, from each perspective.

  • Maps relationships from multiple perspectives
  • Captures what’s at stake for each party
  • Models how the same connection means different things to different parties
  • Provides the foundational layer for perspective-aware AI

Standpoint Mesh

Mesh lets systems act on them together.

A collaboration mesh that lets AI systems, humans, and human-AI teams share context and work together while respecting boundaries and preserving what matters to each participant.

  • Enables AI systems to collaborate across boundaries
  • Supports human-AI collaboration and human-human coordination
  • Preserves context and perspective during collaboration
  • Builds on Core’s perspective awareness

Who This Serves

Enterprise Leaders

Run scenarios on strategic decisions. See what ripples through your org before you commit.

AI/ML Teams

Deploy agent systems that actually coordinate instead of stepping on each other.

Product Managers

Understand how feature changes affect engineering, support, sales, legal, and users. Simultaneously.

Individuals with AI Agents

Your personal team of 8-15+ agents working in harmony, not chaos. Know they’re considering what matters to you.

Built by Someone Who Needed This

Christoph Plough, Founder

20+ years building enterprise technology. Employee #13 at G-Log, designed the architecture for what became Oracle Transportation Management. Co-founded MavenWire, grew it from zero to $14M/year revenue, 150+ employees, global offices, entirely bootstrapped. Sold 2016. Not the outcome I’d hoped for, but I learned what matters: protecting people, aligning incentives, and acting decisively when it counts.

I built this because I needed it for my own work. Couldn’t find it anywhere. Spent months looking. So I’m creating it. Why this matters to me.

In Partnership with Oznog

We collaborate with Oznog on building sovereign infrastructure for the fifth story: genuine human-AI interdependence. Different entities, shared values. What’s the fifth story?

Seeking

  • Operations / Integrator: Someone who thrives on systems, processes, and making trains run on time
  • Go-to-market advisor: AI infrastructure experience, enterprise relationships