OntoFable

No-code Ontology Studio for Enterprise AI Teams

Enterprises have built RAG systems by ingesting and vectorizing data from across CRMs, SharePoint, Google docs, Jira, Asana, cloud repositories, databases and other silos. And they’ve optimized embeddings, chunking, rerankers and models to their maximum limits, yet hallucinations remain stubbornly persistent. It is because standard vector databases are fundamentally designed for similarity, not logic. Due to contextual fragmentation and semantic noise accumulation, vector search suffers relational blindness and has no concept of time or status. In the process, the structural reality of how business data operates is stripped away.

The result: Agents and LLMs produce confident but inconsistent answers that fail to reflect your actual business reality or enable contextual reasoning. In high-stakes enterprise use cases, this is not only a barrier to scale trustworthy AI but also a direct risk to revenue, compliance and reputation. The solution is to adopt a foundational, connective structure that acts as digital twin of your business’ analogy reality, i.e., Ontology.

OntoFable Closes That Gap

OntoFable, our zero code Ontology Studio, helps you build production-grade Ontology-Augmented Generation (OAG) and GraphRAGs. It ingests your organizational intelligence from diverse sources and automatically builds a custom, living ontology. Which is a formal, auditable, machine-readable schema in your company’s precise business language.

This ontology defines the entities & their attributes, preserves the exact rules & relationships that connect them, enforces logical constraints and provides a verifiable grounding layer. From that foundation, it constructs a governed Knowledge Graph and fuses it with semantic retrieval to deliver reliable neuro-symbolic RAG system.

Get Real Results From Your AI Investments

Whether you are scaling agentic workflows, building domain-specific copilots or setting up enterprise AI governance, OntoFable delivers the missing piece: formal, actionable institutional knowledge. OntoFable stops rising operational expenses and fixes the four biggest drains on your budget:
– Minimal Hallucinations: Prevents waste from AI spend; eliminates financial & legal liabilities due to fabricated outputs.
– Lower Token Bills: Stops the exponential token drain of agentic loops.
– Faster Time-to-Market: Erases the cost of delay from building bespoke pipelines.
– Minimized Latency Costs: Cuts processing delays that kill user adoption.

How OntoFable Works

1. Unifies your knowledge. CRM, ticketing, file storage, databases, it ingests and de-duplicates across systems that don’t normally talk to each other.
2. Builds Ontology. Our proprietary core engine proposes the entities, relationships, and rules that define your business and builds ontology graph both in standard (OWL/RDF) and visual formats. No months of manual modeling.
3. Validates & Enriches Schema: against its own constraints & explicit rules and does light reasoning over implicit relationships via standardized rule-based inference (RDFS / OWL 2 RL). While your team can review them and refine with in-built editor before anything goes live.
4. Heavy Reasoning On Demand*: When your domain really requires it, an integrated formal reasoner performs deep Description-Logic (DL) consistency checks over complex axioms to classify everything completely.
5. Generates Knowledge Graph. Your real data gets mapped onto that ontology model, creating a live, queryable graph that represents operational reality of your business. It provides structured world model that RAGs were missing.
6. Builds Neuro-Symbolic RAG. Retrieval combines semantic search with graph traversal & multi-hop reasoning. This construct grounds every output, by enforcing your ontology’s rules before generation.
7. Deploys as Master Foundation. Every future agent, copilot or autonomous workflow queries the same governed source, instead of each team re-solving the same retrieval problems separately.
   

Advantage OntoFable?

OntoFable turns what is traditionally expensive and complex into a governed, maintainable foundation that scales with your business.

Standards Compliance & Integrations: Built on open standards including OWL, RDF, SHACL (for constraints and validation), and supports SPARQL alongside Cypher. You can export/import ontologies in standard formats and integrate seamlessly with existing tools like Neo4j, Neptune and other graph databases.

Governance: With role-based access control (RBAC). Domain experts, data stewards, and compliance teams can review, comment, and approve updates via the visual editor before they go live.

Living Knowledge Graph: Supports continuous, incremental ingestion and synchronization from operational systems. Changes in source systems are reflected in on scheduled delta updates, minimizing latency while preserving performance.

Security & Compliance: Full support for data residency (choose your region/cloud), PII redaction/masking, encryption at rest & in transit.

Tech Stack: Hybrid architecture with a leading graph database backend, optimized symbolic reasoner, state-of-the-art embedding models and enterprise vector store. Exact components are tailored during onboarding for best performance and security.

Pricing

We offer transparent, flexible models tailored to your organization’s size, data volume, and maturity.
All contracts include Automatic ontology & KG generation, Visual editor, schema reasoner and audit trails.

Request a Demo With Your Data

See the difference on a real sample of your documents and queries, not a canned demo.
Contact us at [email protected]