CloudSense AI
Semantic Execution Layer for Enterprise AI.
Enterprise AI that doesn’t hallucinate. One typed semantic graph. Governed SQL at compile time.
CloudSense encodes your business meaning — metric definitions, entity relationships, governance scopes — and emits deterministic, auditable SQL. No hallucination. No unauthorized queries reaching the warehouse.
The cloud backbone every edge decision depends on.
The problem
Every enterprise has this. No one planned it.
5 disconnected implementations · 3 incompatible auth models · 0 shared governance · Every new use case starts from scratch.
NL2SQL POC sprawl
Three teams built NL2SQL on the same warehouse. Different revenue definitions. Different auth. None share governance. A fourth team is starting another one.
The MCP Server trap
"Just register more MCP servers" is the advice. But who joins results across servers? Not the LLM — token cost is unbounded, joins can't be audited, and your raw data crosses a third-party inference API.
Advisory governance fails
Unauthorized queries reach the warehouse — filtered after the fact. AI agents bypass rules by rephrasing. Governance failures show up in logs after the damage is done.
31% NL2SQL accuracy
Raw NL2SQL on Spider 2.0 benchmarks at 31%. Without a semantic layer encoding business meaning, models invent metric definitions, join wrong tables, and return confidently wrong results.
These aren’t model problems. They’re semantic execution problems.
Vendor clarity
Everyone claims a semantic layer. Most don’t have one.
Your data warehouse added metadata tags. Your catalog added AI search. Neither executes governed queries.
| Data Warehouse | Data Catalog | CloudSense | |
|---|---|---|---|
| Job | Store & process data at scale | Index & document data assets | → Encode meaning + emit governed SQL |
| Query execution | Yes — direct SQL | No — documentation only | → Emits governed SQL to warehouse |
| Governance | Advisory / post-execution | Metadata tags & lineage | → Compile-time RBAC/ABAC |
| Semantic layer? | ❌ Metadata tags ≠ governed SQL | ❌ Lineage graphs ≠ governed SQL | → ✅ Single definition per metric |
| AI-ready? | ⚠ Adds NL2SQL on top — still 31% | ⚠ Context but no execution | → ✅ 98–100% on covered questions |
How it works
One semantic graph. Every consumer. Zero hallucination.
Introspect all connected sources — schemas, columns, relationships
Encode business meaning: metric formulas, entity definitions, governance scopes
Ground every query term in the semantic graph — no invented definitions
Emit native SQL with RBAC/ABAC injected — deterministic, auditable
Why it works
Compile-time governance. Not advisory. Enforced.
⚠ Advisory governance — every POC today
✅ Compile-time governance — CloudSense
EdgeSense AI
The semantic layer. To the last mile.
CloudSense governs the cloud. EdgeSense extends the semantic graph to field devices, factories, and air-gapped environments.
How semantics travel to the edge
CloudSense
Full semantic graph
All enterprise entities, metric definitions, governance scopes, and relationships
scoped slice
signed + encrypted
EdgeSense
Local semantic graph
Role-scoped slice in sqlite — only the entities and rules this device and role need
escalate
if needed
On-device SLM
Grounded inference
Model resolves against local graph first — escalates to CloudSense only when confidence demands it
CRDT sync keeps the local graph current when connectivity returns. Outcomes feed back to CloudSense to strengthen the shared semantic graph.
No connectivity
Field tech offline — NL2SQL POC returns 503. Technician uses a PDF manual. 45 minutes of search.
✓EdgeSense answers from local sqlite semantic graph in < 2s
Latency
Cloud round-trip: 3–8s per query. Line runs faster than AI responds. $2.4M system, unused.
✓SLM inference local — sub-second on covered questions
Data sovereignty
SCADA telemetry is CIP-classified. Cloud LLM cannot see it. Every query sanitised by hand.
✓CIP-tagged data stays on device. Only non-classified content reaches cloud.
EdgeSense stack
Stop building POCs. Start shipping governed AI.
Thinking Sense · CloudSense AI · Early access 2026
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