ANTHOS

OVERVIEW

As complexity grows across every sector, organizations need smarter tools to navigate uncertainty and make high-impact decisions with confidence.

Anthos is pioneering new forms of decision intelligence by addressing a key limitation of traditional machine learning: the inability to predict how systems will respond to interventions never seen in training data.

We accomplish this by leveraging cutting-edge agentic programs and natural language processing to translate context from expert analytical frameworks and an organization’s multimodal data into structured, causation-aware formats. Once curated, this information is processed by our proprietary causal reasoning algorithms and integrated into workflows, automating knowledge across the organization. The result is a powerful capability to predict intervention outcomes with greater clarity—turning uncertainty into strategic advantage for forward-thinking organizations.

Scroll below to better understand how we accomplish this.

OUR PROCESS: STEP 1

Uncover Underlying Mental Models

Anthos helps organizations decode how their experts make decisions by extracting tacit knowledge through targeted interviews and discussions. This process captures implicit mental models as formal causal relationships, providing a clear representation of the organization’s unique understanding of the world and its approach to solving problems.

STEP 2

Connecting Your Data Ecosystem

We integrate data from all relevant sources and enrich it with context to turn raw numbers into actionable insights. By uncovering the underlying equations in your data, we build robust causal models that predict how your system will respond to new interventions.

Our integration process focuses on the data most valuable to your team. Using advanced data discovery tools, we work alongside your experts to clarify what the data truly represents and what conclusions it can reliably support.

We then convert this data into structured, causation-aware formats, enabling seamless interaction with Anthos agents.
These agents apply flexible causal reasoning techniques—such as difference-in-differences or automated equation discovery—and translate the results into clear, strategic insights.

STEP 3

Learning Through Real-world Testing

We continuously refine our models through collaborative feedback loops with your team—surfacing blind spots, challenging assumptions, and designing targeted experiments to validate key relationships. This iterative process builds a learning system that improves with every interaction, increasing confidence in predictions about scenarios that have never been encountered before.

STEP 4

Embed Intelligence in Your Workflows

We embed causal decision support directly into your operations, enabling automated scenario analysis so your teams can evaluate interventions before they’re implemented. The result: faster learning, smarter adaptation, and actionable intelligence embedded directly into your critical workflow.

Use Cases

With the help of key collaborators, we’re designing this technology to serve diverse challenges, such as:

Strategic
Planning

Automated
Risk Management

Interconnection
Queue Treatment

Project
Development

Transportation
Optimizations

COMPANY OVERVIEW

Anthos is on a mission to empower leaders with advanced tools to navigate complexity and create meaningful, long-term impact.

We are a small, highly skilled team with deep expertise in artificial intelligence, science, and mathematics. Led by serial entrepreneur Devin Young and applied mathematician Dr. DJ Passey, we bring decades of experience working with leading tech companies like Google X and Microsoft, as well as high-growth, VC-backed startups.

Accelerate your organization’s impact with Anthos. Reach out to learn more about becoming a design partner.

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