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Semantic Distillation: A Brief Primer

The fact that business teams are drowning in disconnected data is getting to be a bit of a cliche. Adding a semantic layer to an enterprise data platform can bring order to chaos, allowing teams to collaborate effectively and leverage AI to unlock valuable insights.

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Kobai & Industry News
Celebal Technologies Partners with Kobai
Celebal Technologies Partners with Kobai

to Launch Turnkey Knowledge Graph Solutions For Global
Enterprises on Databricks

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Latest Event:
Webminar on Wednesday, October 29th, 2025
Play now
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Context-Powered Ontology & Semantic Intelligence for Enterprise AI

Unify enterprise data, ontology, and meaning into a single semantic layer that enables AI systems to reason, understand, and act with real-world context. Deployed fast. Scaled in the cloud.

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Kobai + Databricks | Learn More
From Disconnected Data to Connected Intelligence

HOW KOBAI WORKS

Kobai creates a semantic knowledge graph layer that sits between your existing data infrastructure and your business applications. Here's the process:

1
Data Discovery & Mapping
Kobai connects and analyzes metadata across systems (Databricks, Snowflake, Azure, SAP, Oracle) using pre-built connectors, identifying entities, relationships, and metadata without moving or duplicating data.
2
Semantic Modeling
Business users build ontologies using a no-code visual interface, defining real-world concepts (e.g., "Asset," "Supplier," "Work Order") and their relationships, creating a business-friendly semantic layer.
3
Context Enrichment
The platform automatically adds lineage tracking, data quality scores, and business context to every data point, transforming raw tables into meaningful knowledge
4
Query & Analysis
Users query data using natural language or visual tools without requiring users to write SQL or SPARQL. The semantic layer translates business questions into optimized queries across all connected systems.
5
AI & Analytics Integration
The enriched knowledge graph feeds directly into BI tools, ML pipelines, and LLMs, providing trusted context that improves accuracy and reduces hallucination risks.
6
Deployment Timeline
Customers using industry accelerators typically see initial value within weeks rather than the months often required for custom integration projects.

Available for replay:

Webminar on Wednesday, October 29th, 2025.
View Now

WHAT SETS US APART

Business-Ready Modeling

Empower domain experts with a no-code interface that lets them build and evolve semantic models—without relying on engineers.
Databricks Built On Partner
builton-partner-badge-2x-1Kobai operates within Databricks — enhancing data discovery and AI capabilities.  Read more →
AI-Ready Data Layer
Contextualize your data with integrated semantics, lineage, and relationships—ready to feed BI tools, LLMs, and automation pipelines.
Industry Accelerators
Prebuilt ontologies and templates tailored for sectors like aerospace, energy, and manufacturing help you get value in weeks, not quarters.
Flexible Deployment
Run where you need to—Kobai works across cloud, hybrid, and on-prem environments, adapting to your enterprise architecture.
Built for Your Data Cloud
Native integration with Databricks, Snowflake, and Azure means Kobai runs where your data lives—no movement, no duplication, no lag.

COMMON PROBLEMS KOBAI SOLVES

Explore 3 real-world problem scenarios that Kobai solves—and see how knowledge graphs turn complexity into clarity, speed, and better decisions.

SCENARIO 1

Challenge

 A pharmaceutical company has supplier data in SAP, quality data in LIMS, compliance data in Veeva, and procurement data in Coupa. Each system shows different supplier names and IDs.

Kobai Solution

Creates a unified "Supplier" entity that links all four systems, resolving name variations and maintaining lineage. Quality teams can now see procurement history; procurement can see quality issues, all from one view.

Time to Value

3 weeks using Pharma Accelerator

SCENARIO 2

Challenge

An aerospace manufacturer wants to use LLMs to answer maintenance questions, but the AI invents part numbers and maintenance procedures because it lacks proper context.

Kobai Solution

Provides the LLM with a structured knowledge graph containing verified part specifications, maintenance procedures, and relationships between components. The AI can now cite specific sources and provide accurate answers.

Accuracy Improvement

 Customers report a significant reduction in incorrect or hallucinated responses.

SCENARIO 3

Challenge

An energy company acquired three facilities, each with 20+ years of historical data in different formats, naming conventions, and systems.

Kobai Solution

Uses semantic mapping to create a unified plant data model, normalizing naming conventions and creating cross-facility views without rewriting existing systems.

Integration Time

6 weeks vs. 18+ months with traditional ETL approaches

When Complexity Meets Clarity—This Is What Happens

Disconnected systems. Siloed teams. High-stakes decisions. Our customers faced the same challenges—until they put context at the core of their operations. With Kobai, they’ve unlocked faster insights, smarter decisions, and real outcomes across supply chains, healthcare, energy, and beyond. Here's how clarity changes everything.

Connect What You Have. Deliver What You Need.

Kobai integrates across your legacy infrastructure, analytics tools, and modern data platforms—without refactoring or delay. Start generating insight in days, not months.
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A Semantic Layer That Works Where You Do

Kobai creates a shared, reusable knowledge layer that connects siloed data across systems, teams, and platforms—without replacing what you already have. It runs natively on Databricks, integrates deeply with Snowflake and Azure, and overlays your architecture to bring meaning, consistency, and trust to every decision.

One layer. Multiple wins:

  • Reduce decision latency with business-ready context
  • Eliminate redundant data integration and rework
  • Build trust and lineage into every report
  • Accelerate AI and automation across your existing stack

Your teams stop duplicating effort. Insights become consistent. Compliance gets easier. And AI initiatives finally have trusted context to build on.

People collaborating on a semantic graph
Clarity Without Rebuild

Why Leading Teams Choose Kobai

Kobai blends no-code modeling, semantic context, and enterprise integrations—turning disconnected data into reusable intelligence without replacing your existing stack.
Dark Themed image of a macbook showing charts while codeless queries come out into a knowledge graph that comes out from the screen like hologram
TOUCH
Code-less Querying
Code-less Querying

Business users can easily explore, ask questions, and filter data without needing SQL or SPARQL, using intuitive visual tools and semantic context.

A data network seamlessly blended with a knowledge graph glowing in motion representing the fusion of AI and semantic layers
TOUCH
AI & ML Enablement
AI & ML Enablement

Use connected graph data to train, validate, and deploy models with rich, meaningful features.

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Integrations

Easily connect to platforms like Snowflake, Databricks, Azure, SAP, and more, with APIs to handle both structured and unstructured data.

Integrations

Easily connect to platforms like Snowflake, Databricks, Azure, SAP, and more, with APIs to handle both structured and unstructured data.

Explore even more capabilities built into Kobai’s platform — designed to accelerate outcomes and eliminate friction across your data lifecycle.

  • Build complex queries visually without writing code.

  • Generate insights faster using AI-assisted exploration.

  • Track ontology changes with built-in version control.

  • Design and govern knowledge graphs in real time.

  • Connect and join data across all your systems instantly.

  • Deploy anywhere — cloud, on-prem, or hybrid.

  • Push data directly into BI dashboards or ML pipelines.

  • Apply enterprise access rules down to the node level.

  • Collaborate across teams with synced modeling tools.

  • Detect and flag impactful changes automatically.

CONNECT WITH AN EXPERT

Learn how Kobai stacks up against traditional data platforms and graph technologies.
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FREQUENTLY ASKED QUESTIONS

 

What is a knowledge graph platform? A knowledge graph platform organizes data using real-world business concepts and their relationships rather than tables and columns. Kobai's knowledge graph platform creates a semantic layer that connects data across all enterprise systems, making information findable, trustworthy, and AI-ready without replacing existing infrastructure.
How is Kobai different from a data catalog? Data catalogs inventory what data exists and where. Kobai goes further by creating a semantic layer that models how business concepts relate to each other, enables code-free querying, provides real-time lineage tracking, and feeds contextualized data directly to AI and analytics tools. Think of it as "data catalog + semantic intelligence + business logic."
Can Kobai work with my existing data warehouse (Snowflake/Databricks)? Yes. Kobai is built to overlay your existing data infrastructure. It connects natively to Databricks, Snowflake, and Azure without requiring data movement or duplication. The semantic layer runs where your data lives, adding intelligence without disruption.
How long does implementation take? Implementation timelines vary based on data complexity and organizational requirements. Customers using Kobai's industry accelerators (pre-built ontologies for aerospace, energy, pharma, etc.) often achieve initial value within weeks. Full deployments typically range from weeks to months depending on scope, compared to traditional integration projects which can extend significantly longer.
Do I need data engineers to use Kobai? Kobai provides a no-code visual interface designed for business users and domain experts. While data engineers can be valuable for complex integrations and optimizations, business teams can build and evolve basic semantic models independently, reducing the bottleneck that often occurs when every data question requires engineering support.
What size companies use Kobai? Kobai is designed for mid-market to enterprise organizations ($100M+ revenue) in asset-intensive, compliance-heavy industries with complex supply chains. Common verticals include aerospace, energy, pharmaceuticals, manufacturing, and infrastructure sectors where data integration challenges can significantly impact operational efficiency and decision-making.
How does Kobai pricing work? Kobai uses a transparent, usage-based pricing model that scales with your needs. Contact our team for a customized quote based on your specific requirements.
Does Kobai support on-premise deployment? Yes. Kobai supports cloud, hybrid, and on-premise deployment models, and is typically deployed based on a customer’s security, compliance, and existing infrastructure needs.
How does Kobai ensure data security? Kobai inherits your existing data security policies and adds enterprise-grade access controls at a granular level. Data remains in your environment and Kobai doesn't store or move sensitive information outside your security perimeter. The platform is designed to work within your existing security and compliance framework.
What makes Kobai "AI-ready"? Kobai creates semantically enriched data with built-in lineage, relationships, and business context, the elements that improve AI reliability. The knowledge graph serves as a "grounding layer" that helps AI systems reference verified organizational information rather than relying solely on general training patterns, addressing common accuracy challenges in enterprise AI applications.