Foundry solutions architect
Foundry Expertise You Can Count On
AI agents are only as good as the data you aim them at, and that is the part most vendors skate past. Microsoft Foundry, the platform that used to be called Azure AI Foundry, is where those agents get built. Allston Yale is the Microsoft data consultancy that gets the groundwork right first, for $50M to $100M companies across Texas and the USA whose lean IT teams want AI that holds up rather than another pilot that stalls.
01
Custom-Fit Foundry Solutions
The playbooks for Foundry and AI agents are written for outfits with AI engineers to spare, which is not the mid-market. The teams we partner with are already spread across five roles, so we begin somewhere else entirely: get the data into shape, then take on Foundry at a pace and scope a small team can sustain. Success here is something shipped and used, not a proof of concept that never leaves the lab.
02
What Microsoft Foundry Consulting Actually Involves
Foundry is where AI applications and agents get designed, tuned, and run. For a mid-market business, though, the platform is rarely the hard part. Upstream is: can an agent trust the data it is about to reason over? Aim one at scattered, ungoverned data and it will hand you confident, wrong answers, which is worse than no answer at all.
So most of our work happens before a single agent goes live. We take stock of how ready your data really is, organize it in OneLake where Foundry can reach it, help you choose the one or two use cases to start with, and wrap Foundry's consumption billing in guardrails and cost controls. The adoption is deliberate, never a land grab.
We will be straight with you on scope. Getting you Foundry-ready and steering the rollout is squarely our lane, grounded in the Microsoft data platform we know cold. Building deep, bespoke agents beyond that is a different craft, and when a project needs it, we will say so and bring in a build partner rather than improvise past our depth.
03
Built for Lean Teams, Not Big Departments
A mid-market rollout lives or dies on restraint. No one here needs a fleet of agents or an AI stack they cannot keep alive six months on. We settle on a single use case that clearly earns its place, prove it against data you already trust, and document all of it so your team holds the reins once we step off.
Nothing we leave behind is a black box. The data connections, the agent, the guardrails, every piece arrives with an explanation and a handover. An AI setup only we can run is a liability wearing the costume of innovation, and it is the exact opposite of what we set out to give you.
04
Microsoft Foundry Implementation and Ongoing Support
Nearly every Foundry engagement opens on readiness rather than a model. We look hard at your data and your candidate use cases, repair the foundation, then build a first agent or application over it, confirming it behaves and stays anchored to trustworthy data before it goes anywhere near real work.
From there, the depth of involvement is yours. Fully managed, the occasional review, or a line to call when the team strays into new territory, all of them work. Whichever you pick, we keep an owner on every critical piece.
05
Industry Experience
The industries we know best are the ones powering the Texas economy and beyond: oil and gas, energy and utilities, manufacturing, and healthcare. Each carries questions an agent could take off your plate, though a good question in a field report bears little resemblance to a good one in a claims queue.
An agent flagging emerging plant issues for a manufacturer has little in common with one triaging an insurer's claims or tracking project risk for a builder. We show up with patterns shaped by your sector rather than a single template stretched to fit, since that gap is usually where these projects are won or lost.
06
Foundry and Fabric, Together
Microsoft frames this cleanly. Your data lives in Fabric; the agents that use it are built in Foundry. Foundry reaches directly into OneLake to ground what it says, so the two were meant as one continuous arc, not a pair of disconnected tools. That seam is exactly where we work.
What we bring is the foundation that makes Foundry pay off. An agent you can trust needs clean, governed, well-connected data underneath it, and standing that up in Fabric and Power BI is our strongest ground. Get it right and Foundry has solid footing to reason from. Skip it, and even a first-rate agent simply inherits whatever mess it was aimed at.
Unsure how the pieces fit, or whether the data foundation ought to come before any of this? Our Microsoft Fabric consulting page covers the platform Foundry is built on, and we are glad to think through where AI belongs before you commit to anything.
What working with Us Looks like
The people who reach us are usually worn down by AI demos that dazzle in the room and then never ship, or agents nobody trusts because nobody trusts the numbers under them. Their request is refreshingly plain: AI that runs on data they believe, without a running battle to get there. What we leave in place is built to be dependable and useful in the day-to-day, not a highlight reel for a slide.
32%
INCREASE IN DECISION SPEED
27%
REDUCTION IN OPERATIONAL COSTS
2.4x
INCREASE DATA UTILIZATION
96%
DATA ACCURACY IMPROVEMENT
Data-Driven Demand Forecasting with Analytics Data Platform
Analytics Data Platform Facilitating a Greener Future
Common Questions
How much does Microsoft Foundry cost to run?
There is no separate license for Foundry; it runs on Azure’s consumption model, so you pay for the models, compute, and services your agents actually use. Left unwatched, that figure can climb quickly, which is why we scope use cases tightly and set limits from the start. As with any Azure spend, we model the numbers with you before you commit.
How long before we have a working Foundry use case?
With the data foundation already in place, a focused first use case, one agent or app grounded in data we have made ready, usually takes weeks rather than quarters. You widen out in stages after that, so users see something real early instead of waiting on one big reveal.
Is our data ready for AI agents?
For plenty of teams the answer is not yet, and it is the first thing to check. Agents built on messy, ungoverned data return answers that are confident and wrong. We work out where your data actually stands, close the gaps in Fabric and OneLake, and bring it to the point where an agent’s output can be relied on. That groundwork is where most of the value hides.
Do we need Foundry, or is Copilot enough?
Depends on the job in front of you. Microsoft 365 Copilot handles broad productivity help with nothing to build, while Foundry is for custom agents that reason over your own data and rules. If you need a tailored agent working your business logic, that is Foundry’s ground; if a ready-made assistant would serve, we will tell you before you spend on anything custom.
Talk to a Foundry Consultant
If Foundry is on your radar, or you have already started and want a second opinion, a short call will tell you more than any vendor deck. Book a time, and we will walk through where you stand and whether Foundry earns its place for you.
