Data & AI Strategy
Turn AI ambition into a board-ready roadmap: where data and AI create measurable ROI, sequenced by value and grounded in what the data can actually support, on a clear path to the agentic enterprise.
Invest with confidence and know exactly what to build next. Our data and AI strategy services turn "we need an AI strategy" into a costed, sequenced roadmap: we work with CEOs and CTOs to ground every use case in what the data can actually support today, and to prioritize the ones with the clearest measurable return.
What we deliver
What our data and AI strategy services deliver
Strategy here is not a slide deck. Every data and AI strategy engagement produces decisions you can fund and a plan your team can execute:
An AI readiness assessment
An honest read of data quality, governance, and architecture against the use cases you want to ship, so investment lands where the gaps actually are.
A board-ready AI roadmap for the enterprise
Use cases sequenced by ROI and data readiness, each one costed, owned, and tied to a business metric rather than a technology wish list.
A data strategy anchored in a governed foundation
The target state on Snowflake that the roadmap depends on: governed, trusted data feeding real decisions, with Horizon Catalog and Semantic Views giving every team and every agent one business context. We design it hand in hand with our cloud architecture and data foundation work.
A clear path to the agentic enterprise
Where Cortex Analyst, Cortex Agents, and Snowflake CoWork earn a place on the roadmap, and where they do not yet. As an Anthropic partner we default to Claude for agentic work; see how agentic AI runs inside and outside Snowflake.
An operating model your team keeps
Roles, governance, and a capability plan so both practices, data and AI, run on your payroll and keep improving after we step back.
In practice
What it looks like in your stack
A closer look at what we stand up and how it lands where your team already works.
- An AI readiness assessment
- A board-ready AI roadmap for the enterprise
- A data strategy anchored in a governed foundation
How we work
How a strategy engagement runs
A fixed cadence that puts working software in front of you fast and makes each decision on evidence, not a deck.
- 01
Discovery
A short, focused engagement that fixes scope and surfaces the real state of your data.
- 02
Use-case sprints
Working increments ship into your environment, one decision-ready slice at a time.
- 03
Proof before scale
Each slice proves out in production before anyone commits to the next.
- 04
A practice you keep
Your team builds alongside ours, so the capability stays after we step back.
Defined builds are priced to the outcome rather than the hours, and we compress the distance between strategy and production. A short discovery fixes scope and surfaces the real state of your data. Use-case sprints then ship working increments, and proof comes before scale: the decision to invest further is made on evidence, not a deck. That mechanism is why first value lands in 8 to 16 weeks instead of at the end of a programme.
The advice stays concrete because the same team delivers on it: SnowPro-certified engineers, a Snowflake Premier Partner and Snowflake CoCo Preferred Partner, with leadership carrying 15+ years of data experience. The roadmap also stays honest about sequencing. If a legacy warehouse stands between you and the first use case, migration to Snowflake is planned into the sequence, not discovered later. You can see how that sequencing plays out across industries in our case studies.
What engagements deliver
Nearshore delivery
Strategy built in live working sessions, in your time zone
Monterrey, MX · Austin, TX · US time zones
An AI roadmap is shaped in the room, in workshops where your executives argue priorities and trade-offs with ours. That collaboration does not survive an overnight async gap, which is why our senior strategists work nearshore from Monterrey and Austin, in US time zones, serving clients across the Americas. Strategy workshops, working sessions, and steering meetings happen live, the same day the question comes up.
The result is a roadmap your leadership pressure-tests in the same meeting it is drafted, not a deliverable that arrives by email for comments. See how the nearshore model works.
FAQ
Frequently asked questions
How do I know if my company is ready for AI?
Readiness is measurable, not a feeling. We assess data quality, governance, architecture, and team skills against the specific use cases you want to ship, and score each gap by the effort to close it. Most organizations turn out readier than they feared in some areas and less ready than they assumed in others, which is exactly what the roadmap needs to reflect.
What should an AI roadmap include?
Four things at minimum: use cases prioritized by business value and feasibility, the data foundations each one depends on, costs and owners per initiative, and the operating model that keeps it running. A roadmap missing any of these is a vision statement, not a plan.
How long does a data and AI strategy engagement take?
The readiness assessment and roadmap take shape during discovery in the opening weeks, and the first use-case sprint ships a working increment against real data soon after, so first value lands in 8–16 weeks with proof before scale. Strategy and delivery are not separate phases; the roadmap earns trust by shipping against it.
Proof
See it running in production
Real, anonymized engagements with measured outcomes, from a Snowflake Premier Partner delivering nearshore across the Americas.
Explore the case studiesRather just ask someone?
Book 30 minutes with the person who would own the work. No deck, no obligation, and a straight answer on whether we are the right fit.
Where this leads
All 6 services