EXARGEN

AI that reachesproduction.

We’re a small crew of senior engineers who embed inside your operation and ship AI systems into your live environment — sovereign, on-prem, and end-to-end owned by the team that built them.

Rapid Diagnostic

Two weeks from first conversation to a written deployment plan.

Exargen

Fast to Production

Systems live in your environment within ninety days, not quarters.

Exargen

Sovereign by Design

Every deployment runs inside your own infrastructure, end to end.

Exargen
§ 01 · The GapWhy enterprise AI stalls before it ships

The model isn’t the hard part. Everything around it is.

The data is spread across seventeen systems. Compliance shapes every design decision. The legacy integration nobody documented. The change management deciding whether anyone actually uses what you build.

Models keep getting sharper, but the distance between a working demo and a working system stays about the same. Closing it is engineering — done inside your environment, alongside the people who’ll run the system every day.

“

That’s the work we do.

§ 02 · The ModelOne process · four phases

How we work.

Predictable from day one. Every phase produces something you can hold in your hand — a plan, a design, a system, a hand-off.

011–2 weeks

Diagnostic

One senior engineer, embedded inside your environment. We map the workflow and identify the highest-leverage place to start.

OutcomeDeployment plan
024–8 weeks

Embed

A small crew designs the system in your reality: your data, your security model, your tools.

OutcomeSystem design
034–12 weeks

Ship

We build inside your security perimeter. The goal is production, not pilot — live in your environment.

OutcomeLive in prod
042–4 weeks

Hand off

We document, we train, we transfer. Your team takes the wheel — we stay close until it sticks.

OutcomeYou own it
§ 03 · CapabilitiesEngineering categories, not menus

What we deploy.

Not a service menu. Each one is a way we ship — engineered to your environment, sovereign to your data.

01 / 05

Sovereign & On-Prem AI

Regulated · Data-sensitive

AI systems that run inside your firewall, on your hardware, under your control. Air-gapped deployments, on-prem inference, sovereign clouds, bring-your-own-compute architectures.

Deployment
Air-gapped
Data egress
Zero
§ 04 · PrinciplesThree convictions we hold to

Why this works.

The reason our engagements land — three ways we differ from a consultancy or a staffing shop.

01

The engineer who scopes ships.

The person in your kickoff meeting is the same person writing the production code. No handoff from strategy to design to delivery. Context stays close to the people accountable for the outcome.

02

We go where the data lives.

On-prem, on the edge, inside your firewall, inside your air-gapped network. Your environment is the deployment target. Sovereignty is a feature, not a friction.

03

We compile what we learn.

Every engagement teaches us something — we turn those lessons into tools, frameworks, and reusable systems. Our work compounds, and so does yours.

§ 05 · Who This Is ForFit, in plain terms

Built for operators. Built for production.

Direct on both sides. If we’re a fit we’ll say so. If we’re not, we’ll point you somewhere better.

Strong fit
01

Operators who own a P&L.

You have a workflow that matters and you want AI inside it — not next to it.

02

Tech leaders who've been through AI cycles.

You've seen what works. You want a partner who shares that perspective.

03

Regulated environments.

Healthcare. Defense. Finance. Government. The cases where the constraints are real.

04

Founders building serious products.

You need senior engineering judgment — end to end.

Probably not a fit
—

The primary goal is a launch announcement, not a working system.

—

You need a large, hourly-billed team. We work in small, senior engagements.

—

You want complete vendor ownership without your team's involvement.

We’re happy to point you toward firms that do this well. Different tools, different jobs.

§ 06 · EngagementsPick the shape that fits

Three ways to work with us.

One workflow, one embed, or one team. If you’re unsure which fits, we’ll help you pick.

Discovery Sprint

2 weeks · fixed price

One senior engineer, embedded for two weeks. You walk away with a written deployment plan and a confident go / no-go.

Best for

Organizations that know there's an AI opportunity and want a builder's view of where to start.

Start here
Most common

Embedded Build

8–16 weeks

Our core engagement. Two to four Forward Deployed Engineers, scoped to one workflow that matters, ending live in your production environment.

Best for

Organizations with a defined problem and the operational readiness to put a system into production.

Start here

Embedded Team

Ongoing · quarterly

A dedicated team of three to six engineers as an extension of your in-house function. Quarterly outcomes, not staffing hours.

Best for

Organizations building AI as a core capability and looking for senior depth alongside their own team.

Start here
§ 08 · The VisionWhere this goes

Hybrid intelligence enters the enterprise not as a product, but as a practice. We build it, embed it, and make it yours.

Innovate

Explore what's possible inside your data, your constraints, your reality.

Execute

Ship inside your environment, on your infrastructure — not a sandbox.

Scale

Compound what works into the next workflow, the next engagement.

§ 07 · FAQQuestions worth answering up front

Straight answers, up front.

Anything not covered here — email presales@exargen.com.

§ 09 · StartTwo weeks to a plan you can act on

Start a project.

Tell us about the workflow you want to put AI inside. If we’re a good fit, we’ll say so. If we’re not, we’ll point you toward someone who is.

No sales team · No CRM spam · Real human reply

What happens next

01We respond within one business day.
02We schedule a 45-min scoping call.
03If it's a fit, we kick off Discovery.
04You receive a written plan in two weeks.
You’re in production