From raw data to decisions — end to end.
We design, build, and operate the full data platform stack: Lakehouse architecture on Databricks, ETL and real-time pipelines, customer data platforms, AI-powered analytics with Databricks Genie, and production AI workflows — all on infrastructure your team controls.
Built for real clients. Shipped to production.
This isn't a reference architecture. Every capability on this page shipped for a paying client — and most of it is live today.
AiMediaGroup
One of the largest digital marketing agencies in the US. We designed and built their entire data and AI platform from the ground up on Databricks — including a custom CDP with IPv6 identity resolution, a proprietary multi-touch attribution engine running across 10+ ad platforms, Genie-powered analytics, and two-way on-prem sync.
Healthcare Policy Intelligence Platform
Dual-agent RAG platform that unified thousands of payor documents into a citation-grade knowledge graph on Databricks. Compliance teams get instant, provenance-verified answers to complex policy questions — with 100% source traceability on every response.
Credit-Risk Intelligence Pipeline
Automated editorial pipeline for a weekly credit-risk newsletter. Replaces hours of analyst research per issue with a structured, sourced pipeline — SEC EDGAR-validated, template-rendered, and Outlook-ready. Built on Databricks with configurable research depth per topic.
A complete, layered data platform.
Enterprise data platforms fail when layers are stitched together ad hoc. We architect each layer with the next in mind — so data flows cleanly from source systems all the way to the executive dashboard and the AI model.
We connect every source your business runs on — including on-premises databases, CRMs, ERPs, ad platforms, and third-party SaaS — and deliver them reliably into a unified landing zone. On-prem systems stay exactly where they are; we build two-way sync so Databricks always has a current, accurate copy without disrupting the systems your operations depend on.
All data — structured, semi-structured, and unstructured — lands in a Delta Lake-backed Lakehouse on Azure Databricks. Delta tables give you ACID transactions, schema evolution, and time-travel auditing out of the box. Unity Catalog enforces access control and data lineage across every table and notebook in the platform.
Raw data is only valuable once it's clean, modeled, and trustworthy. We build transformation pipelines using Delta Live Tables for declarative, self-healing ETL, and dbt for SQL-native transformation with automatic dependency resolution and testing. Every pipeline is observable, tested, and documented before it touches production.
Clean, curated data surfaces through Databricks SQL for high-performance analytics queries, DBSQL Dashboards for operational and executive reporting, and embedded BI for customer-facing analytics. We design the data models and semantic layer so your dashboards answer the right business questions — not just the ones that were easy to build.
The same platform that stores and transforms your data also trains, tracks, and serves your ML models — no separate MLOps infrastructure to maintain. MLflow handles experiment tracking and model registry. Mosaic AI serves models at scale. Feature Store ensures training and serving features stay in sync. Databricks Genie puts conversational AI directly over your data warehouse.
Seven capability areas, fully staffed.
Each engagement draws on the capabilities your situation needs — from a focused pipeline build to a full data platform with custom attribution and AI on top.
Lakehouse Design & Architecture
We design scalable, governed Lakehouse architectures on Azure Databricks — from initial platform setup and storage account design to medallion architecture, access control, and cost optimization. Built for the workloads you have today and the AI workloads coming next quarter.
Data Ingestion & ETL Pipelines
We build reliable, observable data pipelines that bring every source system into your Lakehouse — and keep them current. Whether that's Fivetran-managed connectors for SaaS sources, Delta Live Tables for declarative streaming ETL, or custom Spark jobs for complex transformations, we build pipelines your team can own and monitor.
Dashboards & Business Intelligence
We turn clean Lakehouse data into executive dashboards, operational reports, and self-serve analytics that business users actually use. We design the semantic layer and KPI definitions first — then build the dashboards around them, not the other way around. Outputs work in Databricks SQL Dashboards, Power BI, Tableau, or embedded directly in your product.
Databricks Genie & AI/BI
Databricks Genie lets business users ask natural-language questions directly against your Lakehouse data and get accurate, sourced answers — no SQL required. We configure and tune Genie Spaces against your certified data assets, define trusted metrics, and wire up the guardrails that keep it on-model. The result is a self-service analytics layer your whole organization can use.
Custom-Built CDP
We don't resell Segment or Tealium — we build your CDP from scratch on Databricks, purpose-built for your data model and activation needs. The identity graph resolves every visitor across IPv4, IPv6, phone number, ZIP code, and geo-location signals into a single deterministic profile — including anonymous visitors that packaged CDPs can't stitch. Your data stays in your infrastructure, fully owned, fully portable.
Production ML & AI Workflows
We build, deploy, and govern ML models and AI workflows directly on the Databricks platform — using MLflow for experiment tracking and model registry, Feature Store for consistent feature serving, and Mosaic AI for scalable inference. For agentic AI workflows, we connect Databricks to LangGraph orchestration and frontier models via FastAPI service layers.
Custom Multi-Touch Attribution Engine
We built our own attribution engine from the ground up — not a packaged model, not platform-reported numbers. It ingests every touchpoint across every paid and offline channel, then scores conversions across configurable lookback windows and attribution models so you finally know what's actually driving results.
Why Databricks is our data platform of choice.
We've worked with every major data platform. Databricks is where we land for enterprise clients who need a unified environment for data engineering, analytics, and AI — without maintaining three separate tool stacks.
One platform, every workload
Data engineering, SQL analytics, ML training, and AI serving — all in a single governed platform. Your data team stops context-switching between tools and starts shipping faster.
Enterprise governance with Unity Catalog
Centralized access control, data lineage, and audit logging across all your data assets. Compliance and security teams get the visibility they need; engineers stay out of manual access management.
Reliable pipelines with Delta Live Tables
Declarative ETL with built-in data quality expectations, automatic error handling, and full lineage tracking. Pipelines that were brittle become self-healing — and new engineers can read what a pipeline does without reverse-engineering it.
AI where your data already lives
Databricks Genie, Mosaic AI, and MLflow run natively inside the same platform as your data — no data movement, no separate ML infrastructure, no drift between training features and serving features.
Ask your data a question. Get a real answer.
Databricks Genie is an AI-powered analytics layer that lets business users — executives, operations managers, marketers — query your Lakehouse in plain English and get back accurate, sourced results. No SQL. No waiting for an analyst. No hallucinated numbers.
Natural-language queries over live data
Users type a question in plain English. Genie translates it to SQL against your certified Gold-layer tables and returns the answer — with the underlying query visible for verification.
Grounded in your trusted metrics
We configure Genie Spaces against your semantic layer — so "revenue" means what your CFO says it means, not whatever the model guesses. Answers are reproducible, auditable, and consistent across teams.
Guardrails and access control
Unity Catalog enforces who can see what. Genie respects those same permissions — users only get answers from data they're authorized to access. No leakage of sensitive records through a chat interface.
Auto-generated charts and summaries
Results surface as tables, charts, or executive summaries — formatted for the context. A sales leader asking about pipeline velocity gets a chart. A finance analyst asking about variance gets a table with drill-down.
A CDP we built. Not one we resell.
Packaged CDPs like Segment and Tealium give every client the same identity model, the same schema constraints, and the same activation limits. We build yours from scratch on Databricks — designed around your data model, your channel mix, and your activation requirements. Every user profile, every conversion signal, every audience segment is yours to own, query, and extend without a vendor in the middle.
Deep Identity Resolution
We build every user profile from the ground up — resolving identity across IPv4 and IPv6 addresses, phone numbers, ZIP codes, and geographic coordinates. IPv6 resolution in particular lets us stitch anonymous visitors that most off-the-shelf CDPs miss entirely, extending match rates well beyond what cookie-based identity graphs can achieve.
Cross-Channel Visit & Event Pipeline
Every visit, click, form fill, call, and offline transaction flows into a unified behavioral timeline on Delta Lake. Visit synchronization pipelines keep the profile current across web sessions, mobile events, CRM updates, and ad platform signals — with full lineage on every event so you know exactly where each data point came from.
Segmentation & Lookalike Modeling
Build audiences against any combination of profile attributes, behavioral history, conversion data, and predictive scores. Lookalike models trained on your best converters extend reach to net-new prospects with matching behavioral fingerprints. Segments sync to Google, Meta, Microsoft, LinkedIn, and The Trade Desk on a defined cadence.
Predictive Scores Built In
Propensity to convert, churn risk, and lifetime value models train directly on the unified profile inside Databricks — no data export, no separate ML infrastructure. Feature Store keeps training features and serving features consistent, so scores in the CDP match what the model was trained on.
Omnichannel Activation — Inbound & Outbound
Inbound: offline conversion data from S3, call outcomes from Invoca, and CRM records from Salesforce and HubSpot enrich the profile continuously. Outbound: CDP audience segments activate to Google Customer Match, Meta Custom Audiences, LinkedIn Matched Audiences, Microsoft Customer Match, and The Trade Desk first-party data marketplace — all on automated sync schedules with data quality checks at every sink.
Attribution built from the source — not borrowed from the platform.
Every ad platform reports its own conversions using its own rules. Google takes credit. Meta takes credit. The Trade Desk takes credit. The numbers never reconcile, and no one can tell you what actually drove the sale. We solve this by building a single attribution engine that ingests every touchpoint from every channel, applies consistent logic, and produces one version of the truth — owned entirely by you.
Configurable Lookback Windows
Attribution runs across 30-day, 60-day, and 90-day lookback windows — configurable per client, per campaign type, or per conversion goal. Longer windows catch the slow-burn channels (programmatic, connected TV, display) that first-touch-only models systematically undervalue. Shorter windows isolate high-intent, close-in conversion events.
Multiple Attribution Models, Side by Side
First touch, last touch, and linear (equal-weight) models run in parallel so you can compare how each channel performs under different credit assumptions — without re-running the pipeline. The model your CFO trusts and the model your media buyer trusts can both be right simultaneously.
Order ID–Level Conversion Tracking
Conversions are tracked at the order ID level — not just at the session or cookie level. This means every conversion is deduplicable, auditable, and joinable to your CRM or ERP revenue records. No double-counting between platforms. No mystery revenue that only appears in one dashboard.
Direct, Indirect & Assisted Conversions
The engine distinguishes direct conversions (the attributed channel drove the final click), indirect conversions (the channel influenced the path but wasn't last touch), and assisted conversions (the channel appeared in the journey but didn't close it). Each type rolls up independently so upper-funnel channels get the credit they actually deserve.
Your on-prem systems stay. Your data becomes cloud-ready.
Most businesses have critical data locked in on-premises infrastructure — ERP systems, legacy databases, manufacturing systems, billing platforms — that can't be moved to the cloud without disrupting daily operations. We don't ask you to move them. We build two-way sync between your data center and Databricks so both environments stay current, consistent, and useful.
On-prem systems keep running. Nothing changes for your operations team.
Your ERP, billing platform, or legacy database continues to operate exactly as it does today. We sync data out of it — never through it — so there's no risk to the systems your business depends on and no re-training your staff on new tools.
Databricks decisions write back to on-prem where it matters.
Two-way means both directions. AI-generated scores, enriched customer records, updated attribution data, and processed analytics results can write back to your on-prem systems automatically — so field teams and operational software see the same picture as the analytics layer, without anyone exporting spreadsheets.
Sensitive data stays on-premises if it needs to.
Regulated data — healthcare records, financial transactions, PII — can remain in your data center under your governance policies. We sync only what's approved to move, with encryption in transit and Unity Catalog controlling access on the Databricks side. Compliance and cloud benefits coexist.
Cloud analytics on top of on-prem data — without the migration project.
You get dashboards, AI models, attribution reporting, and Genie natural-language queries running against your most current on-prem data — without a multi-year migration program. This is how clients get cloud value on a 90-day timeline instead of a multi-year one.
The tools we connect — and how.
We're not a systems integrator that connects anything to anything. These are the integrations we've built in production, for the business use cases we're hired for most.
| Tool / Platform | Category | How we use it |
|---|---|---|
| Fivetran | Managed connectors for Salesforce, HubSpot, Google Ads, Facebook Ads, Stripe, databases, and 500+ SaaS sources. Zero-maintenance ingestion into Delta Lake landing zones — handles schema drift, retries, and incremental loads automatically. | |
| On-Prem ↔ Databricks Sync | We connect on-premises SQL Server, Oracle, MySQL, and legacy database environments to Azure Databricks using Change Data Capture (CDC) — so only changed records move, not full table copies, keeping bandwidth and latency low. The sync runs in both directions: operational data flows up to Databricks for analytics and AI; enriched records, scores, and processed results write back down to on-prem tables your existing software already reads. Your operations team sees no change. Your analytics team gets current data. No migration required. | |
| Azure Databricks | Our primary data and AI platform. Delta Lake for storage, Delta Live Tables for ETL, Databricks SQL for analytics, MLflow for model management, Mosaic AI for model serving, and Genie for AI-powered analytics. | |
| dbt | SQL-native data transformation with built-in testing, documentation, and dependency graphs. We use dbt Core on Databricks for Silver and Gold layer modeling — giving analysts and engineers a shared transformation layer with version control. | |
| Databricks Genie | Natural-language analytics for business users. We configure Genie Spaces against certified Gold-layer tables, define trusted metrics, and tune the semantic layer so answers are consistent, auditable, and scoped to each user's data access permissions. | |
| Power BI / Tableau | For clients with existing BI investments, we connect Power BI or Tableau directly to Databricks SQL endpoints — so your existing reports stay intact while the data underneath moves to the Lakehouse. | |
| Custom Attribution Engine | Proprietary multi-touch attribution engine built on Databricks — not a packaged tool. Ingests visit logs, conversion events, call records (Invoca), and offline conversions (S3) across all paid channels. Runs first-touch, last-touch, and linear models simultaneously across 30-, 60-, and 90-day lookback windows. Tracks conversions at the order ID level and distinguishes direct, indirect, and assisted conversion types — giving one deduplicated, auditable truth across every platform. | |
| Custom CDP (Identity Graph) | Custom-built customer data platform on Databricks — not Segment, Tealium, or any packaged vendor. Resolves visitor identity across IPv4, IPv6, phone number, ZIP code, and geographic coordinates. Visit synchronization pipelines keep profiles current across channels. Unified profiles feed segmentation, lookalike modeling, and all downstream activation platforms. | |
| Ad Platforms & DSPs | We integrate the full paid media ecosystem — every major platform, plus offline and call signals — into a unified Lakehouse attribution layer. Spend, impression, click, and conversion data flows in; CDP audience segments flow back out for activation. Paid Search & Social: Google Ads API, Meta Ads, Microsoft Advertising (Bing), LinkedIn Campaign Manager, Yahoo DSP. Programmatic: The Trade Desk (TTD) — campaigns, impression logs, and audience segments via API and S3 log delivery. Advanced contextual targeting signals ingested and mapped to customer profiles. Offline Conversions: S3-based offline conversion uploads to Google Enhanced Conversions, Meta Offline Events, and Microsoft Click ID matching — closing the loop between in-store, phone, and digital touchpoints. Call Intelligence: Invoca call tracking integration — call records, duration, outcome, and IVR disposition data ingested into the Lakehouse and mapped to originating ad campaigns for full call-attribution reporting. Outbound Activation: CDP audience segments pushed back to Google Customer Match, Meta Custom Audiences, LinkedIn Matched Audiences, and TTD first-party data marketplace on a defined sync cadence. | |
| Salesforce / HubSpot | Two-way integration: pull CRM data into the unified customer profile for enrichment and modeling; push scores (LTV, churn risk, lead grade) back into the CRM so sales reps work with AI-enriched records without leaving their tool. | |
| LangGraph + Claude API | When Genie's SQL-based reasoning isn't enough — for multi-step workflows, document analysis, or RAG over unstructured content — we connect LangGraph agents to Databricks Vector Search and the Claude API through FastAPI service layers. | |
| MLflow | Experiment tracking, model versioning, artifact storage, and production model registry — built into Databricks. Every model we train is logged, reproducible, and deployable from the same platform where its training data lives. | |
| Azure Key Vault + Entra ID | Secrets management and identity governance integrated with Databricks Unity Catalog and workspace access. Compliant with SOC 2, HIPAA, and financial services security controls out of the box. |
Start with a free Data Platform Assessment.
A 30-minute call with one of our data architects. We map your current state, identify where data is costing you decisions, and tell you honestly what the right starting point looks like — before any engagement begins.
Ready to build a data platform that actually scales?
Talk to our data architecture team. We'll map your current state, identify the highest-leverage starting point, and scope a delivery plan within a single working session.