WE HAVE HELPED ORGANIZATIONS AT EVERY STAGE OF THE INTELLIGENCE JOURNEY
FROM FIRST STEPS, TO OPTIMIZATION AT SCALE, AS WELL AS THOSE MANAGING PORTFOLIOS ACROSS THEM
Tech initiatives fail when you skip the intelligence foundations.
AI, automation, and operational intelligence all depend on the same thing: data infrastructure that actually works.
Fragmented
Critical data is spread across dozens of systems with no unified view. Your AI sees pieces, not the picture.
Ungoverned
No lineage, no quality controls, no clear ownership. Every AI output inherits the uncertainty of its inputs.
Not AI-Ready
Data built for reports and dashboards doesn't serve ML pipelines. The shape is wrong, the semantics are missing, and the freshness isn't there.
From data foundations to AI in production.
A platform approach to tech enablement — not a one-off consulting engagement.
Assess
Rapid diagnostic of data maturity across your organization. Where are the gaps, what's the cost of inaction, and where does AI create the most value fastest?
Architect
Design the data and AI infrastructure each organization company needs — governance, pipelines, semantic layers, and the integration patterns that make AI workloads production-grade.
Accelerate
Deploy AI, build internal capability, and get out of the way. Your teams own the systems we build — our success metric is that you don't need us anymore.
Built for organization-scale impact
Three models for getting AI into your organization. Only one leaves you independent.
Big consulting
- —Six-figure SOWs per organization company
- —Junior associates executing senior decks
- —Knowledge walks out when the engagement ends
- —Months to first measurable outcome
Mega-scale AI vendors
- —Optimized to sell API seats, not your outcomes
- —Your data flows through their infrastructure
- —Vendor lock-in by design — switching costs compound
- —No help with the data foundations AI requires
The sorqua model
- Open-weight models on your cloud or on-prem infra
- Your data never leaves your environment
- Reusable patterns that compound across the organization
- Your teams end up tech-enabled, not dependent on ours
The tech enablement gap
73%
of enterprise AI projects never make it to production
Gartner 2024
5×
more time spent preparing data than building models
Anaconda State of DS 2024
$12.9M
annual cost to organizations from poor data quality
Gartner
82%
of PE firms say data and AI are top value creation priorities
Bain PE Report 2024