AI gives answers your teams can trust. Data is measured against the use case, with quality rules and a named owner for each.
Use Case First
We start with the data one priority application needs. Enterprise-wide cleanup can wait.
Data Readinessfor AI
Give AI the data it needs to deliver.
Trusted Data.
Clear Context.
Now AI-Ready
Most organizations already hold the data AI needs. It is scattered, inconsistent, and hard to interpret. SSI turns it into a dependable foundation.
We bring data quality, integration, and business context together around your priority use case. Your AI starts from information your teams can trust.
Our Capabilities
Four capability areas. Each one removes a data barrier between AI ambition and real results.
Data Quality & Governance
AI gives answers your teams can trust. Data is measured against the use case, with quality rules and a named owner for each.
Data Integration & Pipelines
Teams stop preparing data by hand. The right sources stay connected and current automatically.
Metadata & Semantic Modeling
AI reads your data the way your business does. Shared definitions, metrics, relationships, and lineage give BI and AI tools the same business context. Plain-language questions return fewer ambiguous answers.
Knowledge Preparation
Assistants retrieve only what each user is allowed to see. Documents are structured, enriched with metadata, and kept current for AI retrieval.
Data Quality & Governance
Data Integration & Pipelines
Teams stop preparing data by hand. The right sources stay connected and current automatically.
Metadata & Semantic Modeling
AI reads your data the way your business does. Shared definitions, metrics, relationships, and lineage give BI and AI tools the same business context. Plain-language questions return fewer ambiguous answers.
Knowledge Preparation
Assistants retrieve only what each user is allowed to see. Documents are structured, enriched with metadata, and kept current for AI retrieval.
Why SSI
Thirty years of enterprise delivery.
Applied to the data AI depends on.
Built on What You Have
We work with your existing systems, pipelines, and catalogs. New tools come in only where they earn their place.
Engineering, Not Just Assessment
We do not stop at a findings report. Our teams build the pipelines and controls that close the gaps.
Validated AI Readiness
We test data quality, business context, access controls, and AI outputs against real business scenarios. That evidence moves a pilot into dependable production.
Built to Deliver
A proof of concept answers one question. Will it work? When the answer is yes, the production build is scoped as a separate phase.
Delivery teams
Smart Pods
Senior teams. Embedded with yours. Accelerated by AI.
Each pod is a cross-functional team shaped around your outcome. Pods deliver with AI tooling from Anthropic, OpenAI, and Cursor.
Reusable platform
Momentum
The Momentum Enterprise AI Delivery Framework.
An enterprise delivery framework powered by AI. Every engagement starts from a proven foundation instead of a blank page.
Our Methodology
Five phases. Each one targets the data your next AI application depends on.
Define the Use Case
We agree on what the AI must do and what data it needs. Scope stays tied to that outcome.
Assess Readiness
We profile the relevant sources for quality, freshness, and access. You see which gaps actually matter.
Fix What Matters
We resolve the priority gaps first. Quality rules and owners are set as we go.
Connect and Document
Pipelines bring the sources together. The catalog records what each field means and where it came from.
Extend the Standard
Each new use case builds on the last. Standards carry forward instead of starting over.
Resources
What’s new at SSI, insights, news, blogs, whitepapers, and guides from our teams.
BLOG
The Data Layer as a Product in Asset Management
The future of asset management will be shaped not by models alone but by how intelligently firms structure their data. Treating the data layer as a product unlocks scalable AI and real-time investment intelligence.
BLOG
GraphRAG and the Shift from Document Retrieval to Relationship-Aware GenAI
As enterprise GenAI matures, document-based retrieval is no longer enough. GraphRAG extends traditional RAG by integrating knowledge graphs, enabling structured, relationship-aware reasoning designed for governance, accountability, and complex decision environments…
BLOG
Retrieval-Augmented Generation (RAG) in AI and Business Intelligence
RAG empowers businesses with the most relevant and current information, leading to more informed and effective decision-making
FAQs
Not finding what you are looking for? Talk directly to our data team.
Let’s build what moves forward
Tell us what you want AI to do and where the data lives. We will show you what stands in the way.
