THE PROBLEM

Your data is locked in systems
nobody can stitch together.

You have the data. It's just trapped in seventeen different systems that don't talk to each other. Your team spends more time moving data between tools than actually using it. AI could help—if only you could get all the data in one place.

THE LANDSCAPE

A tour of your data prison.

THE CRM GAP

The Sales-Marketing Silo

Sales doesn't see lead activity. Marketing doesn't see deal outcomes. AI can't predict either.

THE ERP BOX

The Operations Silo

Operations data is stuck in an on-prem system with no API. Manual CSV exports are the only bridge.

THE SUPPORT ISLAND

The Customer Silo

Customer tickets aren't linked to product usage. Support is reactive instead of predictive.

THE SAAS SPRAWL

The Shadow IT Silo

Departments bought their own SaaS tools. Data is fragmented across 40+ different silos.

THE COST

Silos are expensive.

12 hrs/week
Time spent by staff finding data
30%+
Data duplication rate in enterprise
$3.1T
Cost of bad data to US economy/year
$1.50
Average cost per manual data entry

Data silos don't just slow you down—they make AI nearly impossible. Machine learning needs connected data. Automation needs data that flows. When your data is fragmented, every AI project starts with months of "data preparation."

And that's assuming you can even find the data. Most organizations don't actually know what data they have, where it lives, or who owns it. They have data. They just can't use it.

OUR APPROACH

Break down the walls.

01

Unified Data Audit

We map every data source in your company. Not just the big ones—the spreadsheets and hidden tools too.

02

Strategic Plumbing

We build the connections that matter most. We don't move everything—just the data that drives ROI.

03

Automated Pipelines

Data moves itself. No more manual exports. No more reconciliations. Clean data flows into your AI systems.

04

One Version of Truth

We establish the source of truth for key metrics. AI models get reliable data, and leaders get reliable answers.

REALITY CHECK

You don't need a data lake.

Every vendor wants to sell you a massive data infrastructure project. A data warehouse. A data lake. A data lakehouse. (Yes, that's a real thing.)

Here's what they won't tell you: most AI use cases don't need unified data infrastructure. They need specific data, flowing through specific pipelines, solving specific problems.

Start with the business problem. Build just enough data infrastructure to solve it. Expand from there. That's how you avoid the three-year "foundation" project that never delivers value.

Unlock your data.
Without the mega-project.

The free AI Readiness Audit maps your data landscape and identifies the highest-value integration opportunities. Find out where to start without committing to a multi-year initiative.

START FREE AUDIT →