Strategy. Architecture. Execution. With one accountable team.
Most data infrastructure consulting ends with a slide deck and an invoice. Logiciel's consulting practice goes further - strategy, architecture, and execution - with named US-aligned leads who own the outcome end-to-end.
Common patterns:
CTOs evaluating us typically need:
Strategy grounded in your actual stack, team, and budget. Strategy grounded in actual stack, team, and budget reality is the structural difference between consulting that produces decks and consulting that produces outcomes.
Architecture that's executable - not just defensible. Architecture you can run requires capacity, cost, and migration plans grounded in the engineering team's actual capability and bandwidth.
Consulting that hands off cleanly into implementation, with the same team. Same-team handoff into implementation eliminates the typical 'consultants leave, implementation team starts from scratch' tax.
Consulting that ends with a working stack, not a deck.
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.
Multi-year data infrastructure strategy aligned to outcomes.
Workload-grounded TCO across Snowflake/Databricks/BigQuery/Redshift.
DataOps maturity, mesh readiness, team structure.
Current state assessment, gap analysis, target architecture.
Phased migration plans with parity validation.
Framework gap analysis (SOC 2, HIPAA, SOX, GDPR, EU AI Act).
Logiciel is a data infrastructure company; consulting is one of our delivery models, not our entire business. We can implement what we recommend - most clients hire us for that combination. Pure consulting firms produce decks; pure tool vendors hand you software and walk away. We deliberately span both because data infrastructure work succeeds when strategy, architecture, and execution are owned by the same team. About 40% of our revenue is consulting (advisory, strategy, architecture); 60% is implementation, platform, and managed operations. Customers often start with consulting (strategy, diagnostic, target architecture) and grow into implementation as the right partner becomes obvious through execution.
Fixed-fee for time-bound diagnostics and roadmaps; T&M or retainer for open-ended advisory; fixed-fee per workshop for targeted engagements. Diagnostic engagements run $200K-400K (8-12 weeks). Strategy engagements run $400K-1M (12-20 weeks). Workshops run $50K-150K (1-3 days delivered). Retainer advisory runs $20K-80K monthly depending on hours and seniority. Pricing is transparent and benchmarked against equivalent SI pricing at evaluation. Fixed-fee structure aligns incentives with delivery; we don't bill hours that don't translate to outcomes. Most customers prefer fixed-fee diagnostics for predictable budget defense.
8-week diagnostic, fixed-fee at $200K-400K, that produces a costed remediation plan defensible to your CFO and board. Output includes: current-state map of your data infrastructure (often more sprawl than leaders realize), top 3-5 cost or risk gaps with quantified impact, target-state architecture with capacity and TCO models, phased migration plan with milestone-by-milestone cost, and TCO comparison across realistic vendor scenarios. About 60% of diagnostic customers continue into implementation; the other 40% take the plan in-house or to a different SI - which is fine, the diagnostic stands alone as a deliverable. Diagnostic credit applies if you proceed with implementation within 90 days.
PropTech, FinTech, B2B SaaS, Healthcare/Life Sciences, eCommerce, and Construction Tech - references under NDA available during late-stage evaluation. We can typically provide 3-5 closely-matched references (industry, scale, regulatory profile, technology stack) before contract signing. References include both happy-path success stories and recovery scenarios (customers who came to us after failed engagements with other vendors) so you get realistic context. For US Federal customers, separate cleared-engagement references at appropriate clearance levels. For Fortune 500 customers, references at equivalent scale; for high-growth scale-ups, references at appropriate stage and growth pattern.
Named US-based principals - the same lead from strategy through implementation. No bait-and-switch where the senior partner sells the engagement and junior consultants execute. Principal architects average 15+ years in data infrastructure (formerly at Snowflake, Databricks, AWS, Google, Microsoft, top-tier SI firms); customer success leads average 10+ years in client-facing roles. Sprint ceremonies, executive QBRs, and architectural reviews all run with US-based principals during US business hours. For customers with US-citizen requirements, we maintain US-only principal pools. Continuity of leadership is a structural advantage versus large SIs where staffing changes break trust over the engagement lifecycle.
Yes - co-delivered with Accenture, Deloitte, Wipro, TCS, Infosys, Slalom, West Monroe, Booz Allen, and others. Common patterns: SI owns business analysis and change management while Logiciel owns data engineering and platform; SI handles broad transformation and Logiciel runs the data infrastructure workstream as a sub-program. We sign mutual reference agreements and protocols up front to avoid 'two vendors fighting' antipatterns. About 30% of our enterprise engagements involve other delivery partners - and we have explicit playbooks for co-delivery hygiene including escalation paths, decision rights, IP sharing, and risk allocation. We don't displace SI partners; we complement their breadth with our depth in data infrastructure.
Yes - fractional VP-Data and architecture-on-retainer arrangements. Fractional VP-Data: 20-40 hours/month with a US-based senior leader providing strategic guidance, executive presence at QBRs, and oversight on critical decisions; typically $20K-40K monthly. Architecture-on-retainer: 10-30 hours/month with a US-based principal architect providing design reviews, vendor assessment, and tactical guidance; typically $15K-30K monthly. Both arrangements work alongside in-house teams to extend leadership capacity without full-time hire. For US scale-ups in growth mode (Series B-D), the fractional model is often the right pattern before committing to a full-time data leader hire.
60 minutes with a Logiciel principal. Bring your top 3 data infrastructure questions. Leave with concrete next steps and a clear sense of whether we're the right partner.