Government executive dashboards
“What are our top 5 compliance risks this month?”
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AI Insight· AI-Native BI & Analytics● Early Access
Stage 3 · Combustion · plus FADEC · Control
AI Insight
Ask your data anything. Get governed answers.
Conversational BI for enterprise data — natural language questions, AI-generated dashboards, automated reports, and explainable answers from your regulated data environment.
FADEC · FULL AUTHORITY DIGITAL ENGINE CONTROL · AI Insight
HOVER A STAGE TO INSPECT · FIVE STAGES · FOUR PRODUCTS · ONE ENGINE
INTERFACE
What asking your data feels like.
YOU
“Show me permit approval rates by region for Q1 2026.”
AI INSIGHT
Permit approvals · Q1 2026
Gulf Region
92%
GCC South
78%
GCC North
84%
Levant
71%
Permit approvals increased 23% in the Gulf region quarter-over-quarter. Rejection rate highest in [Category X] at 12%.
Source: Permits.gov_internal · regulated_entities table · Q1 2026 records · Row-level security applied.
Illustrative response. Real responses are grounded in your data and your access policies.
ARCHITECTURE
The AI Insight Query Pipeline
Every question flows through the same governed pipeline. Every answer carries its source and reasoning.
01Natural Language Queryuser types in plain English
02Intent Classificationreport · KPI · trend · anomaly
03Schema Mappingtables · fields · joins identified
04SQL Generationvalidated against schema + RLS
05Executionquery runs on governed data
06Visualisation Selectionchart type chosen automatically
07Explainabilitywhy this answer + which sources
08Row-Level Securityviewer sees only their slice
09Dashboardrendered + cached for re-ask
WITHOUT AI INSIGHT
The traditional analyst pipeline
User Request
Analyst+5d
SQL+3d
Answer+2d
~10 business days
WITH AI INSIGHT
Conversational analytics
User Question
Answer+30s
30 seconds
Indicative timings. Traditional pipeline assumes a typical enterprise BI request through a data team; AI Insight numbers reflect cached schema and warm vector index.
[3.1]
Fuel Preparation (Data Readiness)
Structured and unstructured data prepared for AI processing. Chunking, embedding, vector indexing, and metadata tagging.
[3.2]
Ignition (Query Processing)
Natural language intent classified. Query routed to the appropriate engine: conversational BI, document intelligence, or predictive analytics.
[3.3]
Combustion (Intelligence Generation)
RAG pipeline with retrieval, reranking, and LLM generation. Grounded responses — no hallucination from general training data.
[3.4]
Heat Management (Guardrails)
Response validation against accuracy and policy standards. PII masking. Governance rules enforced before output delivery.
[6.1]
FADEC · Engine Monitoring
Real-time telemetry across all stages: integration throughput, process SLAs, API latency, AI query performance.
[6.2]
FADEC · Anomaly Detection
Statistical and ML-based anomaly detection across every metric. Alert routing by severity, team, and escalation path.
[6.3]
FADEC · Natural Language Control
Ask the engine anything: “What caused the spike in integration errors yesterday?” — and get a governed answer from your own operational data.
WHAT IT REPLACES
The manual BI cycle.
Without AI Insight
User request → data analyst ticket → 3–5 day queue → SQL written → chart built → review → response (1 week later).
With AI Insight
User question in chat → governed answer in under 30 seconds.
ENTERPRISE GOVERNANCE
Five non-negotiable controls.
[✓]Row-level security (users see only their data)
[✓]Column-level masking (PII, sensitive fields auto-masked)
[✓]Query audit trail (who asked what, when)
[✓]Approved data sources only (no shadow IT)
[✓]Explainable AI — every answer includes source + reasoning
USE CASES
Where teams ask AI Insight to do the heavy lifting.
Energy regulatory reporting
“Show inspection completion rate by inspector for Q2.”
Financial operations
“Which accounts had unusual transaction velocity last week?”
Education analytics
“Compare school performance by district against national average.”
Join the AI Insight Beta List
Tell us your primary use case and the data sources you'd want to query. We'll set up a technical briefing.