Cost. Performance. Governance. SLA. Across every warehouse you run.
The warehouse runs. That's not the same as it being managed. Logiciel's warehouse management software gives US data leaders unified cost, performance, governance, and SLA visibility across Snowflake, Databricks, BigQuery, and Redshift - without four different consoles.
Common patterns we see:
Teams here typically need:
Cost attribution at the team, model, and query level. Cost attribution at team, model, and query level is the structural foundation of FinOps maturity - without it, attribution is theater.
Workload management across users, models, and BI tools. Workload management across users, models, and BI tools requires platform support; ad-hoc queue assignment doesn't scale.
Governance - access, masking, retention - applied uniformly. Uniform governance applied across warehouses requires runtime enforcement, not warehouse-specific configuration.
Warehouse management as one product.
Trading data, risk models, regulatory reporting - sub-second SLAs and audit-ready governance.
Listing data, transaction pipelines, geospatial analytics - multi-source consolidation.
EHR integration, claims pipelines, clinical analytics - HIPAA-aware infrastructure.
Product analytics, customer 360, usage-based billing - embedded and operational data.
Inventory, pricing, order, and customer pipelines - real-time and high-throughput.
IoT, project, and supply-chain data - operational analytics on hybrid stacks.
| Dedicated Pod | Staff Augmentation | Project-Based Delivery |
|---|---|---|
| Embedded data engineering pod aligned to your sprint cadence - typically 3–6 engineers + a US lead. | Senior data engineers, architects, and SMEs slotted into your team to unblock specific work. | Fixed-scope, milestone-driven engagements with clear deliverables and outcomes. |
We map your stack, workloads, team, and constraints in a working session - not an RFP response.
Reference architecture grounded in your reality, with capacity, cost, and migration plans.
Iterative implementation with weekly demos, code reviews, and your team in the loop.
Managed operations or knowledge transfer - your choice. Both with US-aligned coverage.
Continuous tuning of cost, performance, and reliability against measurable SLAs.
Per-team, per-model, per-query; chargeback ready.
Query, materialization, partitioning recommendations.
Per-domain SLAs measured and reported.
Multi-tenant queueing, prioritization, autoscaling.
RBAC + masking + retention enforced at query time.
Snowflake, Databricks, BigQuery, Redshift unified.
No - we extend them. Native security (Snowflake's RBAC, Databricks Unity Catalog), native compute (warehouses, SQL endpoints), and native storage (Snowflake's micro-partitions, Databricks' Delta Lake) all remain as the underlying primitives. Logiciel adds the cross-warehouse layer: cost attribution at finer granularity than native tools provide, workload management across users and tools, governance enforced at runtime regardless of which warehouse, SLA tracking visible to business owners. For Snowflake-only customers, we complement Snowsight; for multi-warehouse customers, we provide the unified view native tools can't deliver. We don't replicate functionality the warehouses do well; we add the layer they don't.
Yes - customers run mixed Snowflake + Databricks + BigQuery + Redshift environments, often unified across business units, regions, or post-acquisition. Multi-warehouse management gives you one cost view, one governance plane, one observability dashboard, and one workload management console across all warehouses. For US enterprises with multi-warehouse footprints (typically post-acquisition or strategic), the unified view eliminates the typical 'three different consoles, three different cost stories' chaos. About 40% of our enterprise customers run multi-warehouse intentionally; another 20% have multi-warehouse from acquisitions and are consolidating over time with Logiciel as the management plane.
Per-team queues, prioritization, and queue-aware autoscaling. Define queues per business unit, per workload class (BI, ML, ingestion), or per priority level; the platform routes queries to appropriate compute resources and prioritizes based on business rules. Queue-aware autoscaling scales compute up when high-priority queues build up and down during low-utilization periods, capped to budget limits. For US customers running multi-tenant warehouses (often 10-50 teams sharing compute), queue management eliminates the typical 'whoever submits the heaviest query at 9am wins' antipattern. Queue management integrates with cost attribution so chargeback workflows reflect actual workload patterns.
First cost insights within 24 hours of connecting - typically including immediate identification of top cost drivers (specific queries, users, or workloads consuming disproportionate compute). Week 1 establishes baseline and surfaces quick wins (often 5-10% savings from query optimization recommendations); weeks 2-4 add governance and workload management; by day 30, most customers have eliminated 15-25% of warehouse spend through right-sizing, query optimization, and workload separation. ROI in the first quarter typically pays back the platform cost; subsequent quarters compound through governance and reliability improvements that don't show up in raw cost numbers but matter to the CFO over time.
20-40% in the first quarter - primarily from compute right-sizing (most warehouses are over-provisioned by 30-50% on day one), query optimization (the top 10 queries usually account for 40-60% of compute spend, and most can be optimized), and workload separation (BI vs ML vs ingestion on appropriately sized compute). Year-2 savings are smaller (5-15%) as the easy wins are captured, but governance and reliability improvements compound. We benchmark your baseline in week one and measure savings against your numbers, not industry averages - so the savings claim survives CFO scrutiny. Savings are net of Logiciel platform fees in our published TCO models.
Policy compiled to query rewrites and access checks applied at query time. When an analyst queries a table containing PII, the platform rewrites the query to apply masking policies based on the analyst's role and the data classification. Sub-millisecond enforcement overhead for most cases. The enforcement is cryptographically robust - policies live in the data plane, not the BI layer, so analysts can't bypass by using a different query tool. For US regulated customers (financial services, healthcare), runtime enforcement is structurally different from documented-but-not-enforced policy - and audit teams notice the difference. Policies are versioned in Git, code-reviewed in PRs, and audited continuously.
Per warehouse plus per active user - predictable at scale. Mid-market customers (1-3 warehouses, 10-50 users) typically pay $30-80K ARR. Enterprise tiers (multi-warehouse, 200+ users, advanced governance, dedicated TAM, US-citizen support) start at $200K ARR. Pricing is transparent with workload-grounded TCO comparisons available at evaluation. For customers comparing to native warehouse cost monitoring (Snowsight, Databricks system tables) plus separate governance and observability tools, Logiciel typically saves 30-50% at equivalent capability with unified UX. Pricing is contractually capped - no surprise overage bills when you onboard a new business unit.
We'll connect to your warehouse and produce a cost attribution and performance report within 7 days - defensible to the CFO and actionable for engineering.
