How connectivity layers unify fragmented operations data
When three systems hold three versions of the same trade or fee, control work gets expensive. A connectivity layer keeps core systems in place and unifies their data…
Analytics and AI are only as good as the data under them. We build one trusted foundation, from standard, reusable recipes, that serves reporting, analytics, machine learning and AI, with governance and quality built in from the start.
The challenge
Gartner expects organizations to abandon 60% of AI projects that aren’t supported by AI-ready data through 2026 (Gartner, February 2025). We start from a benchmarked maturity assessment, shape the strategy and target architecture, and stand up governed, self-serve data products the business can trust and reuse.
The opportunity
How we help
We benchmark your data and AI capabilities against peers, using industry-standard maturity models.
A business-aligned strategy, operating model and modern target architecture.
We profile your data against priority use cases to find feasible, high-value AI opportunities, with a business case and roadmap.
Trusted, reusable data products with quality, lineage and policy built in.
Governed self-serve, so domains move fast within enterprise standards.
Reusable building blocks (tools, configuration, steps, automation and controls) that standardize and speed up delivery.
What you get
Case study · A top-20 US regional bank
A regional bank with an established data platform asked us to refresh its data strategy for analytics and AI. We benchmarked its maturity against peers and designed the target architecture and operating model the bank adopted as its data roadmap.
Questions
A self-contained, reusable building block (tools, configuration, steps, automation and controls) that standardizes how data products and platform capabilities are built, so delivery is faster and more consistent.
No. We start where you are, assess maturity and modernize step by step on the stack you’ve chosen, such as Databricks, Snowflake or cloud-native services.
The metadata, quality, governance and context that AI needs, so the same trusted data products serve BI, machine learning and AI.
With a rapid maturity assessment and opportunity scan that produces a prioritized roadmap with a business case.
Governance and controls go into the foundation from day one, not afterwards. Our approach comes from years of work in regulated financial services, so we design for your security and compliance requirements from the start.
Our mind
When three systems hold three versions of the same trade or fee, control work gets expensive. A connectivity layer keeps core systems in place and unifies their data…
Data warehouses and lakes store records but not business meaning. A semantic layer translates tables, codes, and joins into shared business terms that AI can use with…
Grounding enterprise LLMs turns plausible text into verifiable answers. Retrieval supplies the evidence, and knowledge graphs show how it fits together, adding…
Next step
Someone senior reads every message and replies to set up a short call.