Customer intelligence first. Engineering underneath.
Most conversations start with a business question: who matters, what is drifting, what should we act on, and why can't the current systems answer it? Customer intelligence is the front door. Data modernization, AI analytics and platform engineering are the capabilities underneath when the problem needs them.
Customer Intelligence
Scattered customer data → unified history → usable audiences
Connect CRM, POS, ecommerce and engagement data; use loyalty when identification is the missing signal; resolve customer identity; compute RFM and behavioral segments; deliver audiences the business can actually use.
- →Unified customer master
- →Identity resolution and duplicate handling
- →First-party identity capture through loyalty when useful
- →RFM and behavioral segmentation
- →Campaign-ready audience outputs
Data Modernization
Legacy SQL Server/SSIS → Fabric medallion lakehouse
Modernize the data foundation when customer intelligence or analytics is being held back by slow, brittle, undocumented infrastructure.
- →Microsoft Fabric
- →SSIS → PySpark migration
- →Power BI Direct Lake semantic models
AI Analytics Layer
Existing warehouse → answerable in plain English
Add a governed intelligence interface to a warehouse that already works, so people can ask useful questions without turning every request into a reporting ticket.
- →Natural language query API
- →Daily briefing workflows
- →Anomaly detection feed
- →Works on Fabric and Postgres
Intelligence Platform Builds
Data estate → running intelligence product
When the need is broader than a customer model, I can scope the sources, build the data layer, add the intelligence interface and ship the production platform around it.
- →Production data pipelines
- →Bronze/Silver/Gold architecture
- →Intelligence and agent interfaces
- →Auth, billing and deployment when needed
Productized customer intelligence
Need more identified customer behavior before segmentation can do its job?
LucidLoyalty gives customers a reason to identify themselves, connects that identity to transactions and engagement, and turns the resulting first-party history into richer segments, targeted actions and measurable response data.
How we work
Most engagements are scoped projects — agreed deliverables, timeline and price before work starts. Ongoing work runs as a standing monthly scope.
Fractional means a standing monthly scope — not a seat in your calendar. Questions answered inside a business day, work delivered against the backlog rather than a clock.
THE LADDER
I meet you where you are on your data path.
- $2,500 · FIXED FEEAI Opportunity Audit
- FROM $4,500Customer Intelligence Build
- FROM $25,000 + MONTHLY PLATFORM FEEIntelligence Platform as a Service
Platform builds are structured as a one-time setup engagement and a monthly platform fee, scoped to your business.
Every engagement starts with a conversation.
Bring the messy version. I'll help separate the business problem from the technology underneath it.
Start the conversation →