Product CLONE

One system, all the layers

RelationalAI brings semantics, ontology, reasoning, decisioning, and post-training together in one Ontology Management System.
Each layer builds on the knowledge and capabilities of the layers before it, creating an executable model that becomes progressively richer—and more capable of supporting decisions and AI.

DATA

Where enterprise
knowledge lives.

Snowflake paradigm

RelationalAI runs as a Snowflake Native App, bringing modeling and reasoning directly to enterprise data within the Snowflake perimeter.
_{Snowflake Native App • PyRel • Native App SQL API}

Work with existing Snowflake data and governance without moving data into a separate graph or decision system.

Run reasoning workloads using horizontally scalable compute designed around Snowflake's cloud architecture.

Only vendor native to the data cloud recognized as such by Gartner® MQ for Decision Intelligence. read more >

SEMANTICS

What the business means.

Concepts • definitions • metrics • requirements • relationships

RelationalAI creates a governed semantic model so people, applications, and AI share the same understanding of enterprise data.
_{Modeler • PyRel • Model repository}

Model concepts, definitions, metrics, requirements, and relationships.

Semantics are the beginning, not the destination. Extend the same model into richer enterprise knowledge and reasoning instead of stopping at consistent definitions for analytics.

RelationalAI is a launch partner of the Open Semantic Interchange (OSSIE), helping establish a vendor-neutral way to express and exchange business semantics across platforms. read more >

1# Product substitution and halo dynamics
2alt = Product.ref ()
3overlap = Product.overlap_with(alt)
4define( Product.substitutes(alt, overlap) ) where ( overlap > 0.9 )
5define( Product. revenue_multiplier(1 + count (Product.bundles) * 0.4))
6
7# Delay impact
8define(Delay.revenue_impact(sum(
9Product. revenue * Product. revenue_multiplier * (1 - max(Product.substitutes))
10))). where (
11Delay.affects(Product)
12)

^{(most Semantic-layer products stop here).}

ONTOLOGY

How the business works.

^{(most ontology and knowledge graph
products stop here).}

Entities • relationships • policies • constraints • dependencies

RelationalAI extends semantics into an executable ontology management system.
_{Relational Knowledge Graph • Modeler • PyRel • Ontology management}

Connect customers, products, accounts, transactions, assets, suppliers, policies, hierarchies, constraints, and dependencies in a governed relational knowledge graph.

Make enterprise knowledge queryable, versionable, governable, and reusable across decisions, applications, and agents.

Only open, executable ontology. Represented as normalized relational tables, governed through Snowflake RBAC, and queryable through SQL by downstream applications.

REASONING

What follows from what we know.

Graph • rules • predictive • prescriptive

RelationalAI combines database, graph, logic, machine learning, and optimization techniques in a relational architecture designed to scale horizontally.
_{Graph Reasoner • Rules Reasoner • Predictive Reasoner • Prescriptive Reasoner}

Discover relationships, dependencies, paths, communities, and connected impact with graph reasoning.

Infer consistently from business rules, policies, requirements, and constraints.

Anticipate outcomes with predictive reasoning.

Optimize actions against objectives and real-world constraints with prescriptive reasoning.

Multiple reasoning engines, one model. Relationships, rules, predictions, and constraints are reasoned over together rather than fragmented across point tools.

1# Product substitution and halo dynamics
2alt = Product.ref ()
3overlap = Product.overlap_with(alt)
4define( Product.substitutes(alt, overlap) ) where ( overlap > 0.9 )
5define( Product. revenue_multiplier(1 + count (Product.bundles) * 0.4))
6
7# Delay impact
8define(Delay.revenue_impact(sum(
9Product. revenue * Product. revenue_multiplier * (1 - max(Product.substitutes))
10))). where (
11Delay.affects(Product)
12)

^{(most reasoning tools stop at one).}

DECISIONING

What should happen next.

Agents • applications • APIs • Snowflake Intelligence • workflows

The ontology and reasoners become a shared decision foundation for AI agents, applications, analytics, and operational workflows.
_{Rel • Agent skills • APIs • Snowflake Intelligence integrations}

Give agents persistent business context and access to specialized reasoning instead of recreating enterprise logic in every prompt or application.

Deliver decisions through Rel, custom agents, enterprise applications, Snowflake Intelligence, APIs, and existing workflows.

Rel, RelationalAI's own decision agent,is built on the same ontology and reasoning capabilities available across the platform. explore Rel >

POST-TRAINING

What AI learns for next time.

Enterprise semantics • reasoning trajectories • model weights

RelationalAI uses enterprise data and semantics to specialize open-weight LLMs for the structures, terminology, and reasoning patterns of the business.
_{Relational Post-training • Superalignment • ScalarLM}

Superalignment combines database-aware techniques including schema linking, data profiling, query consistency, and inference-time reasoning.

Knowledge discovered through inference can be folded into model weights, improving accuracy while reducing repeated inference and latency.

64.35%
‍Spider 2.0 Snow
read more >

93.40%
‍BIRD-SQL dev

1# Product substitution and halo dynamics
2alt = Product.ref ()
3overlap = Product.overlap_with(alt)
4define( Product.substitutes(alt, overlap) ) where ( overlap > 0.9 )
5define( Product. revenue_multiplier(1 + count (Product.bundles) * 0.4))
6
7# Delay impact
8define(Delay.revenue_impact(sum(
9Product. revenue * Product. revenue_multiplier * (1 - max(Product.substitutes))
10))). where (
11Delay.affects(Product)
12)

Different from the start

Expressive

Model more of how the business actually works.

‍Represent concepts, relationships, hierarchies, rules, policies, constraints, predictions, and optimization objectives in a shared enterprise model.

· patented tech

Scalable

Reason over enterprise-scale data.

‍RelationalAI's relational architecture brings graph and advanced reasoning workloads to the scale of the cloud data platform.
‍

· 2026 MQ for DI

Open

Your enterprise knowledge isn't in a proprietary silo.

Governed and queryable through familiar interfaces. Our work with the Open Semantic Interchange helps advance portable, vendor-neutral enterprise semantics.

· OSSIE launch partner

Simple operations

Intelligence to the data, not the other way around.

‍RelationalAI runs natively in Snowflake, allowing enterprise knowledge and reasoning to operate where governed data already lives.
‍

· Snowflake Native App

What is an Ontology Management System?