A specialist Data & AI firm
with a defined delivery lane.
Production is the starting brief. UK-led client engagement with senior engineering depth across India and Europe. One team, one delivery standard.
A specialist data and AI firm with a defined delivery lane.
A defined lane. Specialist data and AI engagements only. No generalist consulting footprint, no unrelated service lines, no platform reselling — one remit, executed at depth.
Every engagement is built for production from day one.
Production is the starting brief. Engagements are scoped against the integration, governance, and operational requirements a system needs to run live — not the acceptance criteria of a proof of concept.
UK-based client engagement with senior engineering depth across India and Europe.
Client-facing leads in the UK. Build and operate capacity through senior engineers across India and Europe. One team, one delivery standard.
Databricks delivery with the surrounding architecture and operational discipline it requires.
Lakehouse, Unity Catalog, and MLflow are table stakes. The integration, data contracts, and operations around them are what decide whether the platform holds up.
The team behind the work.
Senior practitioners from regulated industries, deployed directly on client engagements. No account managers, no bench risk.
Anchors firm strategy and long-range client relationships. Owns the standard that every engagement is held to, from scoping through production handover.
Runs the firm. Shapes the engagement model, the delivery standard, and the commercial discipline behind every scope IntelStack signs.
Finance, commercials, and engagement economics. Designs the pricing and contracting mechanics that make specialist delivery a sustainable model.
Owns the technical standard across the four capability areas. Steps into engagements where production-grade judgement is the thing that decides the outcome.
Runs delivery operations across EMEA. Owns the execution layer, client cadence, and the deployment model connecting UK leadership to in-region engineering.
Leads the data and AI engineering discipline. Owns lakehouse architecture, platform governance, and the applied AI layer from prototype through production.
Ready to build something
that actually works?
Whether you need capacity, talent, or a team to own the outcome — let's talk.