Product CLONE

One system, all the layers

RelationalAI bridges semantics, reasoning, and post-training together in one data-to-decision 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

Tables, views, and enterprise data—in Snowflake, where it already lives.

Snowflake-native environment

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.

RelationalAI—evaluated alongside 16 other vendors— has the only platform built as a Snowflake Data Cloud-native Decision Intelligence Platform in the inaugural Gartner® 2026 Magic Quadrant^™ for Decision Intelligence Platforms. 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.

The semantic model becomes the foundation for richer enterprise knowledge and reasoning in the layers that follow.

RelationalAI is a launch partner to Apache Ossie (incubating), formerly the Open Semantic Interchange, the vendor-neutral standard for exchanging 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).}

Business entities • relationships • policies • hierarchies • constraints • dependencies

RelationalAI extends the semantic model into an executable representation of how the business works.
_{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.

An open, executable ontology. Represented relationally, governed through Snowflake, and queryable through familiar interfaces for downstream applications.

REASONING

What follows from what we know.

Graph • rules • predictive • prescriptive

RelationalAI adds multiple reasoning capabilities to the same enterprise model—combining database, graph, logic, machine learning, and optimization techniques in a relational architecture designed to scale horizontally.
_{Graph Reasoner • Rules Reasoner • Predictive Reasoner • Prescriptive Reasoner}

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

Apply complex policy with rules-based reasoning.
Infer consistently from business rules, policies, requirements, and constraints.

Anticipate outcomes with predictive reasoning.
Generate predictions from relational enterprise data.

Plan & optimize with prescriptive reasoning.
Solve decision problems against objectives and real-world constraints.

Multiple reasoning engines, one model. Relationships, rules, predictions, objectives, and constraints can be 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 Rel and other 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.

Put decisions to work 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.

Post-training moves enterprise semantics and successful reasoning patterns into model weights, reducing how much context and inference must be reconstructed at runtime.

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.

· Apache Ossie contributor

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?