ONTOLOGY FOR DECISION INTELLIGENCE

Better business decisions with AI.

RelationalAI gives agents the context, tools, and intelligence they need to reason over your business and make better decisions on the data and AI platform you already trust.

Native to Snowflake. OSSIE founding member. Snowflake 2026 Telecom Partner of the Year

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What’s possible.

Which 5G cells will breach SLA in the next 2 hours due to the storm?

18 cells at risk; 6 already >80% load. Rebalance to sectors A/B and cap video to 720p in ZIPs 76112–76120. Predicted drop in call‑failures: −67%.

What price floor maximizes Q4 sports revenue without missing delivery?

Set floor at $14.20; revenue +8.3%, under‑delivery risk 1.1%. If $15.00, revenue +10.6% but breach risk 6.4% in weeks 47–48.

Which consignments will miss reserve this month, and how do we fix it?

12 lots at risk; median shortfall 7%. Two levers: lower reserve by 3–5% (+$610k sell‑through) or boost bidder liquidity in TX/AB via targeted email to 4,200 lookalikes (+$480k).

Ask about shipments, supplies, backlogs...

Which consignments will miss reserve this month, and how do we fix it?

What price floor maximizes Q4 sports revenue without missing delivery?

Which 5G cells will breach SLA in the next 2 hours due to the storm?

Every business runs on decisions.

Where should you allocate inventory? How much should you produce? Which risks require action?
What should you price, promote, approve, route, replace, or invest in?

The highest-value decisions rarely depend on one metric or one model; instead, they depend on understanding the business around them. Relationships. Rules. Constraints. Predictions. Objectives.

RelationalAI brings that intelligence together so people and agents can make better decisions about the resources that matter most: inventory, labor, capital, capacity, customers, risk.

AI can do more. It isn't running your business.

still

Today's models are remarkably good at writing, summarizing, coding, and answering questions, but the decisions that run an enterprise require more than a capable LLM. An agent deciding what to produce, where to allocate inventory, whether a transaction is compliant, or how to respond to a network failure needs to understand how the business works, and reason over that understanding.

‍Closing that gap means building better agents.

RelationalAI
makes agents better in 3 ways...

BETTER CONTEXT
Give agents a model of how your business works.
A relational ontology captures the concepts, relationships, semantics, and business logic agents need to understand the enterprise—not just the data in front of them.
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Relational ontology
BETTER TOOLS
Give agents specialized ways to reason.
‍Go beyond SQL and Python with data-aware reasoners for rules, graphs, prediction, and optimization—so agents can answer questions that require more than retrieval or generated code.

Rules · Graph · Predictive · Prescriptive
BETTER MODELS
Make models smarter about your business.
Combine frontier models with open-weight models specialized using enterprise data and ontological semantics.
Enterprise post-training

...by putting your business logic
under new management.

A map of the business and a model that can run it.

True enterprise knowledge: how a recommended order quantity is calculated. How eligibility is determined. What constraints a plan must satisfy. How risk propagates through a network. How a price should change when demand changes.

True operationability: RelationalAI captures that business logic in an ontology that is governed, composable, and executable.

True accessibility: instead of burying business logic in thousands of applications and lines of code, it becomes shared knowledge that people, agents, and applications can understand and use over and over.

Why relational ontologies >

...so you can get better answers
to the questions that run your business.

Connected risk & impact

What is affected, and what's the lowest-risk response?
‍Understand complex dependencies, trace impact across connected systems, and determine what to do next.
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‍Network recovery · Supplier disruption · Fraud networks · Change impact

Planning & optimization

What's the best decision given our objectives and constraints?
‍Combine predictions, rules, resources, and constraints to find the best feasible course of action.

‍Supply chain · Inventory · Pricing · Scheduling · Resource allocation

Policy, risk & compliance

What is allowed, required, or prohibited? Why?
Apply complex rules consistently across connected data while preserving the reasoning behind every decision.

‍AML · IBOR · Eligibility · Regulatory compliance

Predictive intelligence

What is likely to happen next?
‍Use the relationships and context already in your business to predict outcomes and identify where intervention matters.

‍Demand · Churn · Failure · Risk · Customer behavior

explore solutions >

One ontology. Built differently.

Built to understand AND run the business.

Expressive
Capture the concepts, relationships, rules, predictions, constraints, and business logic required for real decisions.

Executable
Reason directly over enterprise data instead of translating the ontology into piles of application code.

Scalable
Use relational architecture and cloud-native infrastructure for enterprise-scale workloads.

Native to your data. Open to the ecosystem.

Native by design
Runs where your enterprise data already lives, inheriting the platform's security and governance.

Built on open standards
‍Your business model shouldn't be trapped in a proprietary ontology.

Snowflake Native App · Apache Ossie · SQL · Python · Iceberg

Build the model your decisions can run on.

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