Don't just move data. Architect the intelligence.
You’re collecting the data. You’re paying for the storage. But your dashboards are lagging, your CRM is out of sync, and your AI is hallucinating. We fix them.
You Have a Data Graveyard, Not a Data Strategy.
Most companies have data debt: expensive, unorganized information that costs more to store than the value it provides.
Of enterprise data is dark data, unstructured, unmanaged, and invisible to decision-makers.
Average annual loss for mid-market firms due to poor data quality and data rot.
Of AI initiatives stall because the underlying data wasn't built for Retrieval Augmented Generation (RAG).
The infrastructure isn't the problem. The blueprint is.
Source: Harvard Business Review, Gartner Data Integrity Report 2025
5 Ways Your Data Stack is Silently Stalling Your ROI
These aren't platform limitations. They are architectural gaps we fix.
// 01 — Broken Lakehouse
The Data Swamp
You have a data lake, but it's unmanaged. No schemas, no governance, and no "Gold" layer. Without a proper lakehouse architecture, your data is just an expensive liability sitting in storage.
// 02 — No Trust Layer
The Compliance Shadow
You want to innovate, but legal won't let you touch the data. Without a data governance & security layer (Unity Catalog), you have no lineage, no masking, and no path to safe AI.
// 03 — Missing Reverse ETL
The Last-Mile Leak
Your data scientists found the "Propensity to Buy" score, but your sales team in HubSpot can't see it. Without Reverse ETL, your intelligence is trapped in a database instead of driving deals in your CRM.
// 04 — Fragile Pipelines
Brittle Data Pipelines
One API change in Salesforce, and your entire ELT process collapses. If your modern data pipelines aren't self-healing and version-controlled, your Ops team will spend 40 hours a week just fixing the sync.
// 05 — Weak RAG
The Hallucination Gap
You want an AI Agent that answers customer queries. But without a governed Retrieval Augmented Generation pipeline, your AI is guessing. If your knowledge vault is a mess of PDFs, your AI will scale the chaos.
From Raw Data to Agentic Intelligence
We build the foundation that allows your business to act, not just report.
Lakehouse Architecture (Databricks)
Unify every silo into a single home for BI and AI. We implement Bronze → Silver → Gold so your data is always production-ready.
Modern Data Pipelines (ELT/ETL)
Your data's nervous system. Self-healing pipelines from any source, CRM, ERP, or API, without breakage.
The Trust Layer (Governance & Security)
Data you can actually use: governance, privacy masking, and security for GDPR, CCPA, HIPAA, and APP.
Architecture Diagram
Let’s Fix the Foundation
Tell us where your data is stuck. We’ll tell you how we’d move it.
The Ecosystem We Architect. The Tools You Trust.
We don't play favourites with vendors; we play favourites with results.
Foundation
Lakehouse & Warehouse
Nervous System
Modern Data Pipelines
Intelligence Layer
AI & RAG
Action Layer
Reverse ETL
Your Data Should Answer Questions and Trigger Actions
AI is only as smart as the context you give it. We don't just build chatbots. We build Knowledge Vaults and wire them back into the tools your team lives in.
Work With Us the Way Your Business Actually Needs
Not every data problem needs the same engagement. Pick the model that fits your team's maturity and your board's timeline.
BOT Model
We build the architecture. Run it while your team learns. We hand it over with docs your team can use.
Projects
Best for defined outcomes. Databricks migration, RAG pipeline build, Reverse ETL setup.
Managed
Best for ongoing performance. Your fractional Data Ops team. Pipelines running 24/7.
Turn Your Data into an Asset.
No 40-slide decks. No generic sales pitches. Just a 30-minute deep dive with an architect who has built at scale before.
Questions We Hear from Every CDO
-
Centralize structured records and unstructured docs in a Lakehouse. Clean raw data for the gold layer logic. Use RAG to give agents the context needed to avoid hallucinations. We build all three layers.
-
Bronze (Raw) → Silver (Clean) → Gold (Business-ready). If you want your AI to be reliable, it should learn only from Gold-tier data. Without this structure, you're feeding your AI from the raw dump.
-
A warehouse handles structured reports. A Lakehouse handles everything AI needs: PDFs, logs, and unstructured data in one system. Cheaper (one bill, not two). Faster (AI searches once, not twice).
-
Your best leads are in your warehouse. Your team lives in HubSpot. Reverse ETL pushes hot-lead alerts and health scores directly into their CRM. Right context, right moment.
-
Yes. We build the Trust Layer first. The AI reads a document to answer a question, but never retains or trains on it. Your IP stays inside your walls.
-
Data residency is a Trust Layer priority. We configure your environment to keep customer data within APP and GDPR boundaries while enabling global AI orchestration.
-
Knowledge transfer is a contractual deliverable, not a footnote. Our BOT model: we build it, run it, and hand it over with docs your team can actually use. We measure success by whether your team can operate without us.
-
It is the brain for both. Workato moves the data; HubSpot holds the relationships, but Databricks calculates the intelligence. We connect them so your automation is actually smart.