Private AI Infrastructure for DDIL Environments · Now on GSA through Carahsoft

Sovereignty isn't a setting. It's the architecture.

Gridlight is the private AI control plane for defense and public sector organizations where data can't leave the building and downtime isn't an option — delivering cloud-like AI outcomes on infrastructure your agency already owns, from garrison to the tactical edge.

Request a Briefing See the 90-Day Pilot Path

Carahsoft Technology Corp. is Gridlight's public sector distributor

Bringing private, on-premises AI infrastructure to Federal, Defense, State & Local, and Education customers — mission capable from garrison networks to disconnected, tactical edge deployments

Available Through Carahsoft

Private AI infrastructure, built for the mission — not the cloud

Gridlight is the abstraction layer between your agency and your AI — a private inference platform that runs on hardware you control, routes every request to the right model for the workload, and keeps your data exactly where it belongs: inside your perimeter.

Through Carahsoft's reseller network and contract vehicles, Federal civilian, Defense, Intelligence Community, State & Local, and Education customers can now deploy Gridlight without a single byte of mission data leaving their environment — including sites with no internet connection at all.

Genuinely on-premises

Not a private cloud tenancy. Runs with the network cable unplugged.

Hardware-agnostic

Deploys on the mixed, aging fleet your program already owns.

Live in 30 days

Deploy, prove, and expand on a scoped pilot — no 18-month IT program.


The Problem With Cloud AI in Government

Built for where cloud AI can't go

Three structural barriers stand between the public sector and commercial AI. Gridlight was architected to remove all three — not paper over them with a policy.

BARRIER 01

Data can't leave — and the network can't be trusted to

CUI, ITAR, classified, and mission-critical data have to stay inside the perimeter. And in DDIL environments — denied, disrupted, intermittent, limited — there may be no path out at all. Cloud AI, public or "in-tenant," was never built for either boundary.

BARRIER 02

Costs are unpredictable

Per-token billing turns adoption into a compounding, unbudgetable line item. Fixed appropriations need fixed, known costs — not a meter that runs with usage.

BARRIER 03

Every program rebuilds

N contractors, N tools, N compliance packages, N ATOs. Gridlight is the shared control plane every program and every use case runs on.


What That Means in Practice

Your perimeter, always

Six architectural facts — not policy promises — that make Gridlight deployable where cloud AI is a non-starter.

Built for DDIL

Denied, disrupted, intermittent, limited connectivity isn't a degraded mode here — it's the baseline design assumption. An air-gapped site. A ship. A forward operating base. A factory floor. No connection required, ever.

Your data stays yours

Nothing is uploaded, nothing trains anyone else's model, nothing crosses your firewall. This is architectural, not a policy promise.

It answers from your material

Not from what a model read on the internet years ago. Every answer cites the document and section it came from.

It uses hardware you already own

Mixed, aging, non-uniform hardware is normal and expected — not a problem to solve before you start.

One platform, many capabilities

Text, images, video, 3D, and audio in one system with one set of controls — not six vendors and six ATOs.

Costs are fixed and known

Licensed by the compute capacity you run, not by usage. Costs do not rise as adoption does.


The Platform

One platform. A full set of mission capabilities.

Gridlight shares the same security model, the same controls, and the same interface across every capability below — deployed once, governed once.

Retrieval

Ask questions of your own material

Point Gridlight at contracts, policies, manuals, drawings, or recordings. Ask in plain language. Get an answer that cites where it came from.

Search

Search that understands meaning

Matches meaning, not just words — "staff leave entitlement" finds the holiday policy even when the document never uses those words.

Vision & Speech

Understand pictures and speech

Hand it a photograph, a diagram, or a scanned form and ask about it. Hand it a recording and get an accurate transcription — on the same in-house infrastructure.

Generation

Create

Image generation from a description. Video. 3D models with mesh processing for engineering and simulation. Music, sound effects, and natural-sounding voice output.

Fine-Tuning

Specialize it to your mission

Produces a small adapter that teaches the system your terminology and domain — without retraining from scratch, and without a document ever leaving your network.

Simulation

Model what happens next

Takes a described situation and projects likely outcomes — for planning and decision support, not prediction.

 

Deploys On What You Already Own

From a single laptop to a multi-site grid

Gridlight is deliberately hardware-agnostic — built for the reality that agencies own a mixture of equipment bought at different times, from different manufacturers, for different reasons. NVIDIA servers, Apple desktops, and Intel laptops can run in the same grid — and so can ruggedized, transit-case compute built for expeditionary and tactical environments. Edge NPUs and TPUs handle lightweight work — search, classification, transcription — on a fraction of the power a GPU draws, which is exactly what a remote site, a vehicle, or a battery-powered deployment needs.

multi-site grid thumbnail

Production-Ready, Not a Prototype

What clears ATO review

Everything above is what Gridlight does. This is what an AO, an ISSM, and a SOC actually need to see before they'll sign off.

checkmark

SSO through what you already run

Active Directory, SAML, or OIDC — no separate user list to maintain.

checkmark

Certificate-based machine trust

Traffic encrypted; machines in the grid authenticate to each other with certificates, not shared passwords.

checkmark

Tamper-evident audit trail

Every action logged and exportable into whatever SIEM your SOC already runs.

checkmark

Role-based access, per-document tiers

Sensitive material is visible only to those entitled to it — enforced on every single query.

checkmark

Enforced tenancy

One directorate cannot retrieve another's material. Routing rules can require regulated workloads to run only on hardware carrying the right approvals.

checkmark

No single point of failure

Coordinators elect a leader automatically. A failed machine reroutes work without the user seeing an error — reduced capacity, never an outage.


What Makes It Different

Three things, stated plainly

01

It is genuinely on-premises

Not "private cloud." Not "your tenancy in our data center." The software runs on hardware you control and works with the network cable unplugged — usually the deciding factor for defense, regulated industries, and anyone with a data-residency obligation.

02

It treats mixed hardware as normal

Most platforms assume a uniform fleet of identical, current-generation accelerators. Gridlight measures what each machine can actually do and places work accordingly — deploy onto what you already own.

03

It is one platform, not six

Text, search, vision, speech, image, video, 3D, and audio share one deployment, one security boundary, one set of controls. That matters less on day one than in year two — the alternative is six vendors, six audits, six renewals.


Built for Every Stakeholder in the Program

One platform, a message for every seat at the table

Stakeholder
Key Message
Program / CIO
Governance across every AI workload, on infrastructure you already control — one control plane, one audit log, one integration into your existing architecture.
Budget / Comptroller
Turns unpredictable cloud AI spend into a fixed, appropriable cost — fits a procurement line instead of an open-ended O&M draw. See the 36-month comparison.
CISO / AO
Data sovereignty isn't a setting — it's the architecture. Every prompt and byte stays inside your perimeter, with a full audit log of every inference event.
IT / Architect
One integration, every model, hot-swappable. Policy-driven routing on hardware you already run. Deploy in under two weeks.
Contracting / KO
One vendor, one contract, through Carahsoft's existing vehicles — zero new data processor agreements, no N-vendor AI sprawl.

How Programs Get Started

A scoped, outcome-defined pilot

No 18-month integration program. Gridlight stands up inside your environment on a defined timeline, proves the outcome, and expands from there.

DAYS 0–30

Deploy

Gridlight stands up inside your environment; the first use case is scoped against your mission priorities.

DAYS 31–60

Prove

First workflow goes live. Baseline versus result is captured against the metric you define.

DAYS 61–90

Expand

More use cases land on the same platform, the same ATO, the same controls. Costs stay flat.


"You define the success metric — hours saved, response time, accuracy, cost. We measure it against your baseline and report the number in 30 days. Your data never leaves the building."

Frequently Asked

What agencies ask first

No. There is no outbound path for your content. Gridlight is designed to run with no internet connection at all.

Yes — denied, disrupted, intermittent, and limited connectivity is the baseline design assumption, not an edge case. A site or platform that goes fully dark keeps running at full capability; there is no "call home" the system depends on.

A single, reasonably modern computer. A graphics card makes it faster but isn't required — most evaluations begin on hardware the organization already has.

Yes — a strong fit for remote or power-constrained sites, handling search, classification, and transcription efficiently. Pair with a GPU or a well-specified CPU machine for large-model workloads at that site.

Work moves to another machine automatically. In a grid, losing one node reduces capacity — it doesn't cause an outage.

Yes, through fine-tuning, which produces a small adapter reflecting your domain and terminology — trained on your material, inside your network.

By the compute capacity you run, not by usage. Costs do not rise as adoption does — an appropriations-friendly model built for fixed budgets.