BDB Semantic Objects
are not a metrics layer.
They are a governed business object graph — where every entity in your business has defined attributes, governed actions, and native AI agents that can query and act on it.
*Databricks, Snowflake etc. stores your data. BDB knows what it means and what to do with it.
One Platform.
Unlimited Apps.
Zero Hallucination.
AI-scaffolded Satellite Apps, built in days not months, governed by the Kinetic Semantic Layer — deterministic, auditable, and enterprise-ready.
BDB's Agentic AI
Agentic AI generally refers to AI systems that possess the capacity to make autonomous decisions and take actions to achieve specific goals with limited or no direct human intervention.
Transform Your Data Into
Intelligent Insights
Deploy AI-powered Data Agents that understand, analyze, and act on your data autonomously. No coding required, instant insights delivered.
AI Agents Based Retail Analytics Solution
Transforming Retail Intelligence Through Advanced Analytics & AI
Fits in Budget | Scale with Usage | E2E & Flexible
BDB Saas Platform
Empowering Over 100 Schools and 10+ Associations
Education Analytics
Smart Manufacturing: IIoT Analytics Solutions
Manufacturing/IOT Analytics
One Platform for all Analytical Use Cases
Retail Analytics
Learning BDB
Integrate seamlessly with BDB for success
*Based on internal benchmarks comparing ontology-grounded queries vs. raw LLM-to-SQL generation across enterprise datasets.
Output Layer
AI Agent
Autonomous Workforce
Self-Service BI
Zero-Training Dashboards
Enterprise Apps
Embedded Intelligence
BDB Kinetic Semantic Layer
Active Graph Ontology · The Digital Brain
Attributes
Business Ontology
Measures
Measures Derived KPIs
Actions
Business Ontology
Services
API & Event Fabric
Any Data Source
Snowflake
Lakehouse
Databricks
Lakehouse
PostgreSQL
RDBMS
MongoDB
NoSQL
Add Any Source
JDBC, API & more
Graph-native ontology query — how the Kinetic Layer resolves every data request
Connects natively to any data source — no vendor lock-in, no replication required
Azure
AWS Athena
Google Cloud
JDBC
*Databricks, Snowflake etc. stores your data. BDB knows what it means and what to do with it.
Static schemas break.
Kinetic ontologies never do.
Rigid. Brittle.
Probabilistic.
When business logic changes, the semantic layer breaks — leading to probabilistic LLM guesses that silently corrupt executive decisions.
Living. Evolving.
Deterministic.
When business logic changes, the Kinetic Semantic Layer auto-adapts to deliver deterministic, ontology-grounded answers executives trust.
Built on
Deterministic Truth.
Every BDB Business Object is defined once in the Kinetic Layer and consumed universally. Define it right once. Trust it everywhere, forever — by agents, dashboards, APIs, and partner systems.
ATTRIBUTESBusiness Ontology Mapping
Canonical definitions of every enterprise entity — customer, product, region, campaign — mapped precisely to your physical schema. Eliminates the CFO nightmare: AI picking "active_customers" when "paying_customers" was meant. One definition. One truth.
MEASURESDerived KPIs & Aggregations
Complex executive metrics — Churn Rate, Customer LTV, Net Revenue, ARPU — encoded with exact SQL calculations and business meaning. No two systems can ever disagree on a number. The "AI says X, dashboard says Y" board meeting disaster becomes structurally impossible.
ACTIONSAutonomous Execution Engine
Agents that don't just observe — they act. BDB Actions expose approved, governed workflows that agents execute autonomously: trigger campaigns, escalate anomalies, open tickets, update forecasts. Deterministic, fully auditable, and reversible on demand.
SERVICESAPI & Event Orchestration Fabric
REST and GraphQL APIs that expose your governed ontology to external systems, MCP-compatible AI frameworks, and partner ecosystems. Rate-limited, row-level secured at source, and consistent whether consumed by a dashboard, an LLM agent, or an enterprise ERP.
Data Restriction
by Design.
Not Afterthought.
In BDB, governance is structural — not a plugin, not a separate permission table. Every query, agent response, and exported insight is scoped at the semantic layer before data is ever touched.
Data Restriction Filter
A Data Restriction Filter is a governance and intelligence layer designed to ensure that all analytical processes operate strictly within approved, high-quality, and contextually relevant data boundaries.
Row-Level Security via User attributes
A native, identity-aware security model where user context is directly embedded into query execution, enabling seamless and automatic data access control at the row level.
Full Ontological Audit Trail
A Full Ontological Audit Trail provides end-to-end traceability of every data interaction, decision, and output by capturing not just what happened — but the semantic meaning, relationships, and lineage behind it.
Your Autonomous
Workforce.
Move beyond conversational chatbots. BDB Platform delivers true Agentic AI — systems with agency, full enterprise context, and the capability to execute multi-step workflows without human intervention.
Data Agents
Autonomous analysts that monitor KPIs, detect anomalies, and run root-cause analysis without prompting — grounded in the Kinetic Layer for zero-hallucination outputs.
- ✓ Proactive KPI Monitoring 24/7
- ✓ Automated Anomaly Detection
- ✓ Root Cause Analysis
- ✓ Executive Narrative Generation
Doc Agents
Intelligent researchers that synthesize unstructured enterprise documents — contracts, PDFs, emails, filings — against your structured data ontology. Cited sourcing. Zero fabrication.
- ✓ Contract Intelligence
- ✓ Regulatory Compliance Review
- ✓ Cross-source Document Synthesis
- ✓ Structured ↔ Unstructured Bridge
Code Agents
Automated engineers that generate, test, and deploy deterministic data pipelines — with full semantic context, not raw schema guesswork or hallucinated join paths.
- ✓ Pipeline Auto-generation
- ✓ Semantic-aware SQL synthesis
- ✓ Automated Test & Deploy
- ✓ Zero Schema Hallucination
Watch hallucinations
disappear in real-time.
Stop Guessing. Start Knowing.
See the Kinetic Semantic Layer eliminate hallucinations in your data.