Platform Documentation
NexBI Architecture & Guide
A comprehensive deep-dive into NexBI's 8 core modules, Semantic Layer knowledge graph, integration ecosystem, and military-grade security infrastructure.
Platform Architecture & Deployment Mechanics
Data Integration & Automated Semantic Modeling
NexBI connects directly to your existing infrastructure, ensuring data sovereignty without requiring a massive warehouse migration. Under the hood, we leverage a high-throughput proprietary ingestion pipeline, maintaining strict tracking of extraction lineage (_nexbi_extracted_at, _nexbi_meta) to guarantee data provenance.
Within the Data Studio, engineers can visualize raw tables, automatically infer Primary/Foreign Key relationships across disparate schemas (e.g., purchases.user_id -> users.id), and define computed columns or row-level filters prior to ingestion. This guarantees the neuro-symbolic engine interacts with a strongly-typed, deterministic semantic layer rather than raw, chaotic database architectures.
Pipeline & Integration Specifications
- Extraction: Standardized metadata integration for complete traceability.
- Transformation (ELT): Visual interface for pre-ingestion row filtering and computed column definitions.
- Context Management: Modular Knowledge Collections with explicit
#reference invocation. - Execution: Isolated environments for the Code Interpreter and ML Notebook to ensure secure, deterministic analytical outputs.
The 8 Core Modules
Data Studio
Explore your data as a living knowledge base, queryable in natural language by anyone in your organization.
Architecture & Role Specifications
- Transformation Engine: Visual pipeline mapping directly to underlying DAG execution nodes.
- Entity Resolution: Automated schema inference mapping abstract schemas to business entities.
- Type-safe Operations: Pre-computation of scalar values and type enforcement at ingestion.
Secure ML Studio
A sandboxed MLOps workspace to build, train, and deploy predictive models in a secure, isolated environment.
Architecture & Role Specifications
- Sandboxed Execution: Ephemeral runtime environments isolated from internet-facing networks.
- Zero-Data Movement: Models are trained and evaluated directly against local clusters.
- Model Lineage: Strict versioning of serialized weights and algorithmic hyper-parameters.
Anomaly Detection
Continuous monitoring of your parameters with smart alerts — detect deviations before they become incidents.
Architecture & Role Specifications
- Statistical Baselines: Continuous deviation tracking using bounded confidence intervals.
- Threshold Heuristics: Programmable logical triggers acting on high-velocity data streams.
- Alert Routing: Role-based dispatching of incidents through defined webhook channels.
Regulatory Watch
Automated tracking of sector-specific regulations, standards, and compliance updates integrated into your knowledge base.
Architecture & Role Specifications
- Semantic Indexing: Continuous processing of unstructured compliance literature.
- Policy Cross-referencing: Automated flagging of database schemas against indexed policy constraints.
- Audit Immutability: Tamper-evident logs of all system configurations and data access.
Conversational Search
Query your internal documents — standards, audit reports, technical sheets — by simple conversation in Arabic, French, or English.
Architecture & Role Specifications
- Intent Parsing: Neuro-symbolic resolution of ambiguous queries against enterprise taxonomy.
- Hybrid Search: Dense vector embeddings combined with sparse keyword indexing.
- Contextual Sandboxing: Search scope bounded explicitly by user's permission parameters.
Auto Reports
Generate executive summaries and PowerPoint presentations directly from your data, eliminating manual formatting.
Architecture & Role Specifications
- Data-Driven Compilation: Dynamic injection of aggregated metrics into structured template files.
- Scheduled Aggregation: Time-based orchestration of intensive aggregations without locking tables.
- Multi-Format Export: Native serialization to application-specific buffers (PDF, PPTX).
Access Control
Granular role-based access — each department sees only their data perimeter, with no compromise on security.
Architecture & Role Specifications
- Row-Level Sandboxing: Hard isolation of records at the query compiler level.
- Identity Synchronization: Automated parsing of corporate directories for permission propagation.
- Comprehensive Auditing: Persistent logging of all read/write actions mapped to session IDs.
Native Integrations
Connect to SAP, Oracle, Sage, IBM DB2, Odoo and more — without disruption to your existing systems.
Architecture & Role Specifications
- Connection Abstraction: Unified interface masking the complexities of vendor-specific APIs.
- Schema Drift Resilience: Graceful handling of upstream table modifications via semantic mapping.
- High-Throughput Sync: Optimized parallel chunking for bulk data transfers.
Interactive Capabilities
The conversational interface serves as a unified gateway to the entire semantic layer. Instead of requiring users to navigate complex BI dashboards or write custom SQL, NexBI dynamically generates the exact interface required to answer the query. Whether it's rendering a financial forecast, extracting data from a compliance PDF, or building a new machine learning model, the system provisions the right analytical environment in real-time.
Stateful NLP to SQL/API Routing
The neuro-symbolic engine parses complex linguistic intents, resolving ambiguities against the enterprise knowledge graph before compiling deterministic SQL queries or internal API calls. It completely bypasses probabilistic text-to-SQL errors by validating schemas in real-time.
- Abstract Syntax Tree (AST) query validation
- Role-Based Access Control (RBAC) enforced at compilation
- Multi-turn context retention
Dynamic Client-Side Visualization Engine
Instead of rendering static images or relying on iframe embedding, the system dynamically compiles query outputs into native interactive components. The layout engine recalculates dimensions and streams data points directly to the browser for instant exploration.
- Zero-latency client-side rendering
- Native data-to-component serialization
- Interactive drill-downs via event callbacks
Visual DAG Editor & Transformation Pipeline
A low-code orchestration interface mapping directly to underlying DAG execution. Users visually define Directed Acyclic Graphs that the engine translates into scheduled ELT jobs, handling schema drift and dependency resolution natively.
- Auto-inferred entity resolution (PK/FK mapping)
- Type-safe computed columns
- Live data sampling and schema validation
Vectorized Multi-Modal Ingestion Core
Unstructured documents are parsed, chunked, and embedded into a high-dimensional vector space using proprietary embedding models. The indexing pipeline preserves metadata, enabling hybrid search (semantic + keyword) with strict document-level permissions.
- Automated OCR and table extraction
- Hierarchical chunking strategies
- Dense vector storage with HNSW indexing
Sandboxed MLOps Execution Environment
A secure, isolated Python runtime environment for executing data science workloads. The engine spins up ephemeral containers for model training, leveraging the connected data layer securely without exposing raw datasets to public internet.
- Ephemeral container execution
- Pre-configured analytical libraries
- One-click model serialization and API deployment
from nexbi.models import AutoForecaster
dataset = nexbi.query("Q3_Revenue_Data")
model = AutoForecaster(target="revenue").fit(dataset)
Deterministic Knowledge Routing
LLM hallucinations are fundamentally a symptom of unconstrained context windows. NexBI mitigates this by compiling your modeled data into discrete, isolated "Knowledge Collections" (e.g., segregating "Purchases" from "Products").
During query execution, context is explicitly scoped. Users define exact data boundaries by invoking specific collections via # tags. This explicit routing drastically reduces token overhead, minimizes compute latency, and enforces strict access governance by sandboxing the model's search space.
Universal Translation
Maps rigid database schemas to intuitive business metrics.
Access Governance
Applies row-level and column-level security globally.
Continuous Learning
Refines its understanding based on user query corrections.
Ecosystem & Integrations
NexBI is designed to sit on top of your existing architecture. With over 150+ native connectors, you can seamlessly ingest metadata and index documents without creating duplicate data silos.
Available Connectors in Category
Security Architecture
Every request passes through a multi-layered security mesh before processing. Security is strictly deterministic, ensuring AI hallucinations can never bypass data governance.
On-Premise Deployment
Deployed within your own infrastructure — private cloud or air-gapped environments.
Data Sovereignty
Your data never leaves your environment. Full ownership of all models and outputs.
Granular Access Control
Department-level RBAC — production, lab, commercial, and executive each see their perimeter.
Full Audit Trail
Every query, every decision, every access — fully traceable and auditable.
Engagement Models
NexBI offers flexible adoption pathways, from rapid proof-of-concepts to full enterprise sovereign deployments.
Rapid Proof of Value (PoV)
Popular3-4 weeks
Departmental Rollout
90-day cycles
Sovereign Enterprise License
Annual commitment
Strategic Co-Innovation
Multi-year contract
Rapid Proof of Value (PoV) Roadmap
Deploy on a critical use case with your real data. Immediate measurable ROI, zero public cloud risk, and no forced commitment beyond the pilot.
Ready to build your sovereign Semantic Layer?
Contact our enterprise team to design a secure, localized deployment architecture for your organization.