See every pipeline. Catch every break. Ship reliable data - before anyone notices.
Most US data teams don't have an infrastructure problem. They have a visibility problem. Logiciel's data infrastructure management software gives engineering leads a single, real-time view across pipelines, warehouses, and clusters - so issues get caught before dashboards lie, costs creep, or revenue gets reported wrong.
If any of these feel familiar, your stack is costing you more than it should:
You're here because something specific is broken. We've seen it 100 times:
A managed control plane that gives your team back its weekends.
Unified visibility across every pipeline, every warehouse, every transformation — no swivel-chair monitoring. One pane of glass replaces the four-tab investigation that defines most pipeline incidents today, dropping mean-time-to-detect from hours to minutes.
Real-time alerts on freshness, schema drift, and SLA breaches before downstream consumers notice. Anomaly-aware alerts route to upstream owners and downstream consumers simultaneously, so the first conversation about the issue includes everyone who needs to act.
Cost intelligence that maps spend to teams, models, and queries — so FinOps stops being a quarterly fight. Per-team and per-model cost attribution turns FinOps from a quarterly fire drill into a weekly hygiene routine that engineering and finance can both defend.
Battle-tested integrations with Snowflake, Databricks, Redshift, BigQuery, Airflow, dbt, Kafka, and 200+ sources. Battle-tested integrations mean adoption doesn't require swapping the warehouse, BI tools, or orchestrators your team already knows.
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.
Sub-minute detection on freshness, volume anomalies, and schema drift across every pipeline.
Per-team, per-model, per-query attribution — automated chargeback ready.
Auto-discovered, queryable lineage from source to dashboard.
Define data SLAs, route incidents, prove uptime to stakeholders.
AWS, Azure, GCP — manage them in one place without re-platforming.
SOC 2, HIPAA, GDPR-ready audit trails on every data movement.
Datadog, New Relic, and most APM tools watch infrastructure — CPU, memory, network, container health. They tell you the box is up. Logiciel watches the data itself: freshness, accuracy, schema, lineage, and cost across the path from ingestion to BI dashboard. When your CMO opens a dashboard with stale numbers, the box was up — but the data wasn't fresh, and APM never told you. Logiciel detects that scenario in minutes, routes the alert to the team that owns the upstream pipeline, and shows the downstream dashboards affected. APM and data infrastructure management are complementary, not substitutes; most US data teams run both.
Per-pipeline tier with unlimited users — no per-seat penalties when your team grows from 5 to 50. Pricing scales with the number of active pipelines and total data volume monitored, not with the number of dashboards or analysts who consume the insights. For US mid-market customers, typical engagements start at $30K-60K annually; enterprise tiers with dedicated TAM, advanced governance, and 24/7 incident coverage scale from there. Pricing is transparent and contractually capped — no surprise overage bills when your data volume spikes during a marketing push or fiscal close.
Yes. We have customers running fully cloud (AWS, Azure, GCP), fully on-prem (legacy Hadoop, Teradata, Oracle), and hybrid configurations — common in financial services, healthcare, and government-adjacent US enterprises. Logiciel deploys as a managed SaaS, in your VPC, or fully air-gapped on-prem when compliance requires it. Hybrid customers typically run our control plane in the cloud while data planes execute in-region or in-DC, so sensitive data never leaves your perimeter. We've supported FedRAMP-aligned and HIPAA-aligned hybrid deployments at Fortune 500 scale.
We have engineers and customer-facing leads based in the US, plus extended engineering teams across global time zones — meaning incidents get worked 24/7 without you paying for three shifts. Your account is staffed with a US-based principal architect, a US-based customer success lead, and a global engineering pod aligned to your sprint cadence. All escalations route to a US-based on-call rotation during US business hours. For customers with strict residency or citizenship requirements (US Federal, regulated finance), we can configure US-only or US-cleared engineering teams.
No. Logiciel is designed to layer on top of your current Snowflake, Databricks, Redshift, BigQuery, Airflow, dbt, or Kafka setup — not replace them. Most teams are live in 2-3 weeks because we connect via metadata APIs and query logs rather than requiring re-ingestion. Over time, customers often consolidate point tools (separate observability, catalog, and cost dashboards) onto Logiciel because the unified view eliminates swivel-chair monitoring, but that's a phased decision driven by your team, not a forced migration. We provide migration playbooks if and when you choose to consolidate.
Both, and that's deliberate. You get the data infrastructure management platform plus a US-time-zone implementation team that gets you to value within your first 30 days. The platform alone is powerful but takes months to extract full value when teams are already firefighting. Our implementation engineers map your stack, prioritize the top 3-5 risk areas (usually pipeline reliability, cost attribution, and lineage gaps), and embed alongside your team for the first 30-90 days. After that, you can run it solo, retain advisory hours, or move to managed operations — your choice.
Customers report 30-50% reduction in pipeline incidents and 20-35% reduction in cloud spend within the first quarter, plus a measurable lift in stakeholder trust (fewer 'is this number right?' Slack threads). The ROI math usually pencils out from two effects: engineers spend less time on reactive firefighting (regaining 8-12 hours per engineer per week), and FinOps gains attribution that surfaces 15-25% of compute as right-sizable. We benchmark each customer's baseline in week one, so the ROI is measured against your actual numbers — not a generic case study from someone else's industry.
Book a 30-minute working session with a Logiciel data infrastructure architect. We'll map your current stack, identify your top 3 risk areas, and show you exactly what unified management would look like for your team.
