AI Built Right

Building with AI is easier than ever. Building something that solves the right problem and holds up in production still takes experience.

How we put AI to work

Build

01

AI features that earn their place

We design and build AI into products where it earns its place. That means knowing when AI is the right tool, integrating it cleanly with your existing systems, and building it so your users trust it and use it.

02

Proof of concepts before you commit

When the path forward isn't clear, rapid proof of concepts pressure-test the business case and surface data gaps early. On IoT projects, hardware simulators keep development moving and generate the data you need before the hardware arrives.

Advise

03

An AI roadmap built on your operations

Some clients are still figuring out where AI fits, and we meet you there. We assess where AI can automate business processes, reduce manual overhead, and create operational leverage, then give you a prioritized roadmap.

04

AI in your development lifecycle

We help your technical teams work out where AI fits in their own software development lifecycle and how to adopt it.

05

Policy and governance

We help you set up a policy and governance framework so AI adoption inside your organization is responsible by default.

06

Leadership workshops

For leadership teams getting their bearings, our workshops cut through the hype and build working knowledge of what AI can do for your business.

deliver

07

AI across the product lifecycle

Every Red Foundry engagement benefits from AI, whether or not AI is the focus. We use it for requirements, user flows, test scripts, proofs of concept, assisted coding, PR reviews, automated testing, and agentic checks throughout the build.

08

Our people stay in charge

Our product managers, architects, designers, and engineers guide, review, and direct everything AI touches. AI makes our work more thorough. The judgment stays ours.

09

Legacy systems, finally documented

We use AI to reverse document systems that were never properly documented, so your team gets a clear picture of what you're working with. That alone can restart modernization efforts that have been stuck for years.

10

Budgets that go further

We spend human effort where it matters most, and AI helps us catch more, test more, and think more completely. You get a more capable team without paying for a bigger one.

If you can describe the problem, we've likely solved something like it.

An operations manager's plain-language question on the left, and the sourced Power BI answer on the right, showing on-time delivery at 94.2 percent with a four-quarter bar chart. Illustrative data.

Answers you can trust

Our client's engineers had already connected Claude to Power BI and Microsoft 365. We audited what they built and closed the gaps in their MCP servers. By handoff, they had access controls, a shared definition of a good answer, and usage telemetry across every team.

Laptop showing a sample security incident report. On the left, an officer's narrative has names, locations, a badge number, and a license plate marked for removal. On the right, an AI summary describes the incident in four short sentences, with tags confirming the personal details were removed and the weapon reference was kept.

Safer incident reports

We added incident summarization to a large enterprise property platform. Built on Azure OpenAI, it turns a security officer's narrative into a short synopsis with names, locations, and identifying details removed. About 2,000 dispatchers and officers use it today.

Laptop running an IoT hub emulator beside a phone simulator. The emulator shows live readings for simulated RV devices, and the phone app's hub dashboard shows WiFi connected, main door closed, battery at 13.4 volts, and the AC soft start running.

Virtual Testing

Our client's firmware and our engineering teams needed to test against devices they rarely had on hand. We used Claude Code to build a virtual wireless bench that simulates realistic device conditions. Anyone on the team can now drive a test in plain English.

Responsible AI, by design

We build on proven platforms using frontier models, governed by a formal acceptable use policy that protects security, data integrity, and client trust. We evaluate every AI integration for risk and test it for reliability before it ships. As an employee-owned firm, we build things that work.

Laptop running an IoT hub emulator beside a phone simulator. The emulator shows live readings for simulated RV devices, and the phone app's hub dashboard shows WiFi connected, main door closed, battery at 13.4 volts, and the AC soft start running.

Ready to get started?

We see our clients as our partners and are invested in their success. We ensure what we build for our clients will have a positive ROI. We never build anything just for the sake of it.