Ask anything across your enterprise. Get one governed, auditable answer.
Your CFO asks why order-to-cash slipped from 12 to 19 days. thinking sense answers from SAP, Salesforce, and Slack — governed, with full lineage — without moving a byte. No ETL. No manual catalog. No waiting.
Meets your data where it lives.
60+ connectors — Confluence and Jira alongside SAP and Snowflake. Data never moves. Every backend speaks its native protocol.
VPC deployment available · data never crosses the perimeter
Zero data copies
Live federated execution — no new centralized data estate.
Up to 90% fewer frontier-model calls
Repeatable workflows distill into task-specific models.
TPC-H benchmark →From a business question to a verified execution.
thinking sense finds the right meaning and systems, compiles access policy into the plan, executes against live data, and preserves the evidence behind the answer.
“Why did our Order-to-Cash cycle increase from 12 to 19 days this quarter? Find the bottlenecks and tell me what to fix.”
Planned · 3 backends
Broke the question into steps: hold-rate by reason (SAP), exception approval status (Salesforce), release-latency conversations (Slack).
FROM sap_orders.credit_holds h
JOIN sap_orders.orders o ON o.order_id = h.order_id
GROUP BY h.reason ORDER BY holds DESC
Answer
62% of delayed orders carry a credit hold. 74% of those already have an approved commercial exception in Salesforce — Slack shows Sales re-asking Finance to manually release the same orders.
1,847
Unnecessary holds
3.6 days
Avg avoidable delay
$38M
Revenue delayed
412 hrs
Finance effort / mo
“Every project requires me to write an ETL pipeline and use a medallion architecture. What you’re showing is indeed radical.”
Head of Data & Analytics · Fortune 100 Specialty Retailer · more stories →
Enterprise intelligence, by function
The same ontology answers every leader’s question.
Expertise Packs combine domain knowledge with your enterprise data — so the CRO, the CFO, and the service leader can each ask their own question about the same customer, and get an answer grounded in the same facts.
CRO
“Which renewals are at risk because of repeated equipment failures?”
CFO
“Which customers are less profitable than the invoice makes them look?”
General Counsel
“Which contracts are blocking revenue right now?”
Enterprises buy these three separately.
An ontology tool. A fine-tuning platform. A governed AI platform. Three vendors, three budgets — none of them can answer your questions alone.
Palantir · dbt · Neo4j + SageMaker · Azure ML + Snowflake Cortex · Databricks
Together, they do what none could do alone.
Governed answers to every enterprise question — getting smarter with every verified interaction, through every system you already run.
The ontology knows what the data means. Fine-tuning learns how your enterprise uses it. Governed execution answers with full lineage. Intelligence compounds with every use — and that compound is the platform the next generation of enterprise applications is built on.
RLBUF · REINFORCEMENT LEARNING FROM BUSINESS USER FEEDBACK
What accumulates with every use: validated business definitions and source mappings · policies · execution history.
Every vendor wants to own your enterprise intelligence.
We built the layer that keeps it yours.
Model providers get better the more of your enterprise runs through their inference. Palantir’s ontology model requires your data inside their platform. Snowflake and Databricks earn on every workload that lands — and stays — in their estate. Every major model provider’s roadmap points toward being your default enterprise interface.
Each one’s business model depends on your enterprise intelligence living inside their platform. thinking sense is the opposite bet: keep every one of them optional, keep your data where it is, keep the intelligence yours.
| Palantir | Snowflake · Databricks | Model providers | thinking sense | |
|---|---|---|---|---|
| Where your data has to live | Inside their platform | Inside their estate | Wherever the model can reach | ✓Exactly where it is today |
| Who owns your semantic model | They do — the Palantir Ontology | Locked to their platform semantics | Rebuilt from scratch in every prompt | ✓You do — discovered from your systems |
| Cost to switch vendors | Ontology and workflows rebuilt | Full re-platforming | Re-tune everything from zero | ✓Nothing to rebuild — it's portable |
| Which AI models you can use | Multi-model, boxed inside AIP | Whatever the ecosystem ships | Only their own model | ✓Any model — swap anytime |
| When governance is enforced | After ingestion, inside the platform | After ingestion, inside the platform | After the model has already answered | ✓Before execution, every single time |
Every competitor wins by pulling your data and models inside their platform. thinking sense wins by leaving them exactly where they are.
Ready to see it on your own data?
Connect two backends and get your first governed answer in under 48 hours.