AI engineering firm · Washington, DC

AI built around your business.

We build AI systems inside your company, from the first assessment to working tools your own people run.

Engineering inside your business.

What holds a business up is underneath: its systems, its data, and the way work moves. That is where we build.

Skip to the two ways to begin
  1. 01

    AI agents and assistants

    Your team makes the same kinds of judgment calls over and over, working from documents, messages, or records.

    What you get
    You get
    An agent connected to your tools, with written permissions and tests built for the work it does.
    Controls
    Review points, action logs, and limits on what it can read or send.
  2. 02

    Workflow automation

    Work stalls at handoffs or depends on someone moving it between systems.

    What you get
    You get
    A running workflow, defined paths for exceptions, and a clear owner for each approval.
    Controls
    Rules for routine steps. A person for decisions that need judgment.
  3. 03

    Connected data and systems

    Teams rely on separate systems that hold conflicting versions of the same information.

    What you get
    You get
    Connected systems, records that agree across them, and a map of how information moves.
    Controls
    Access by role, checks on data as it moves between systems, and records of important changes.
  4. 04

    Reporting and decision support

    Decisions depend on reports that arrive late or cannot be traced to a source.

    What you get
    You get
    Reports drawn from your systems, with definitions and assumptions made visible.
    Controls
    Traceable sources, checks on data quality, and human judgment over the decision.
  5. 05

    Tools built for your business

    Nothing off the shelf fits the way your team needs to work.

    What you get
    You get
    Working software in your accounts, with the code, documentation, and handover.
    Controls
    Access suited to each role and acceptance tests agreed before the build.
  6. 06

    AI spend, access, and controls

    AI use is growing without a clear view of what it costs, who uses it, or what data it can reach.

    What you get
    You get
    Model and tool choices, a view of usage and cost, and configured spending controls.
    Controls
    Session rules, data permissions, and provider limits, as far as each platform allows.

Across industries

What we learn in one industry carries into the next. Each system is built around the way your business works.

Start where you are.

01 Find the priorities

We study how your business runs today, then plan what to build.

The diagnostic

Three weeks · Fixed fee

What you get
  • A map of where your records break down and where the time goes
  • A baseline to measure what changes
  • An inventory of the AI tools and integrations you pay for
  • A priced plan for the next phase

With read-only access, we sit with your team and follow one job from first contact to paid invoice, timing the waits as well as the work.

The diagnostic fee is credited in full against the next phase if you continue within 90 days.

Discuss the diagnostic

02 Start with the work

You know what needs to change. We scope it, then build it.

One defined problem

One problem · Fixed scope

What you get
  • A written answer to the problem
  • The approach, scope, and price agreed before work begins
  • A working tool, with its code and documentation

How long the work takes depends on the problem. If the fix is a short build, that is the whole engagement.

Bring the work that needs attention, such as a quoting process, a difficult handoff, or a report assembled by hand.

Describe the problem

Both lead to the same short form. No need to choose yet.

Independent judgment. Direct responsibility.

No model, platform, or referral fee to favor. We build the system we recommend, then hand it to you.

Judgment

The tool fits the job.

Every step goes to plain code, AI, or a person, whichever it needs.

How we choose

Plain code where a rule can decide. An AI model where no rule covers the case and there are past decisions to learn from. A person where a mistake would cost too much, with the evidence put in front of them first. We choose the model for the task and the budget: Claude, GPT, Gemini, or an open-weight model on hardware you own.

Ownership

Everything we build sits in accounts you own.

The custom code, the cloud accounts, and the documentation are yours. No subscription to us, and no fee per user.

The details

The accounts are in your name, and we write down what lives where and who can see it. You pay providers directly, and nothing gets bought that you can’t turn off. Ongoing help from us is optional.

Handover

Tested on live work.

Done means your people ran it on live work, without us in the room.

How it is handed over

That test is written into the statement of work. The people who will run it afterward get a short playbook and working sessions.

Fixed-price phases, one at a time.

  1. 01

    Scope

    The diagnostic follows one job from first contact to paid invoice and ends with a priced plan. A defined problem gets a written scope and price. Either way, you keep the plan.

  2. 02

    Foundations

    Optional · If needed

    We connect your systems and clean up your data, so every customer, job and invoice is recorded once and matches everywhere. If your records already agree, we skip this step.

  3. 03

    Guardrails and observability

    Before anything is built, we set the rules: what each AI system may read and send, and who approves what. Every action and every piece of data it touches is logged, so you can always see what it’s doing.

  4. 04

    Build

    We build the whole system, one piece at a time: the workflows and agents, the harnesses that run them, and the infrastructure underneath. Everything lives in accounts you own, and each piece is tested on live work.

  5. 05

    Handover

    Our hours taper off as your people take over. You keep plain, documented code and a playbook for each workflow. Ongoing help from us is optional, with a monthly cap on hours.

Every week
Working sessions with your team, and standing access to your systems.
Before a build
The scope, a fixed price, and how we will judge the result: turnaround, rework, or cost per job.
After any phase
You can stop, and keep what’s built.

We take on a limited number of engagements at a time, each on a set weekly schedule. When we follow up on your inquiry, we will tell you the earliest start we can offer.

AI should be within reach.

You shouldn’t need a large internal engineering team to get AI working in your business. We bring the engineering in and hand your people the tools and knowledge to run what we build.

Chad Wallace

Founder, Red Spruce Labs · Washington, DC

MBA, Georgetown University. Graduate study in data science, University of Virginia.

I founded Red Spruce Labs and lead every engagement, start to finish. I have run large-scale operations for major companies, I write production code, and I know what a model can and cannot be trusted with. Systems I have built are in use today at small businesses, Fortune 500 companies, defense firms, and federal agencies, run by the people who work there.

  1. U.S. Army

    Ten years

    Infantry officer, leading units and running operations at home and overseas.

  2. Blue Origin

    Technical operations lead, New Shepard Rocket Program

    Brought AI to the production floor of New Shepard, building it into the systems behind the crew capsule and the reusable booster that fly people to space.

  3. McChrystal Group

    AI architect

    Built the firm’s AI from the ground up, from its infrastructure and data layer to the agents and tools its teams use, and advised clients on putting AI to work.

  4. Washington, DC private equity firm

    Currently · Applied AI engineering

    Building AI products, data systems and infrastructure for the firm’s portfolio companies, and working on site with their teams to put them into everyday use.

  5. Red Spruce Labs

    Now

    Based in Washington, DC. Hands-on AI engineering for companies across industries and around the country.

    Why the name

    Red spruce grows on the high ridges of the Appalachians, in the shade of taller trees, and lives for centuries. It lays down rings so tight that its wood became the soundboard in some of the best guitars ever made. I named the company after it because that is the work: steady, careful building that has to hold up for years.

Tell us what you want to improve.

One short form. We review every inquiry and reply within two business days.

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