# Gridlight

> Gridlight is private AI infrastructure: a purpose-built inference control plane that runs entirely inside your own environment — on hardware you own, in networks you control — so sensitive data never leaves the building. It gives organizations cloud-like AI functionality (local inference, model routing, capacity governance, continuous learning, and full audit) without sending data to a third-party cloud API.

Gridlight is the abstraction layer between an enterprise and its AI. It routes each workload to the right model, keeps data in place, and makes AI inference activity visible in the security and observability tooling teams already run. It is infrastructure, not a data processor: it holds no data, creates no new data-vendor relationships, and is hardware-agnostic across NVIDIA, AMD, and specialized AI accelerators.

Primary audience: CIOs, CISOs, data and platform leaders, and internal AI builders at regulated and sovereignty-conscious enterprises (financial services, healthcare, government, manufacturing, and other organizations with strict data-residency or compliance constraints).

Site: [www.gridlight.ai](https://www.gridlight.ai)

## What Gridlight is

- **Private AI control plane** — A single inference platform that runs on your hardware, routes to the right model for each workload, governs capacity, and keeps data in your environment by default.
- **Not a cloud API wrapper** — Inference happens locally. There is no round-trip to an external model endpoint, so there is no category of "data left the building" risk to mitigate.
- **Bring AI to the data** — Gridlight inverts the usual data-gravity problem: instead of moving data to a cloud inference endpoint, the inference capability moves to where the data already lives.
- **Integrates with what you have** — Adopts existing identity, observability/SIEM, and enterprise application standards rather than creating a parallel governance structure. Typical time from installation to first production inference in a standard enterprise environment is under two weeks, with a single integration point required in the application layer.

## Key pages

- [Home](https://www.gridlight.ai/): Overview — why running AI on borrowed cloud infrastructure is structurally broken, and what a private, owned alternative looks like.
- [Solutions / Integrations](https://www.gridlight.ai/solutions): How Gridlight fits an existing enterprise environment — identity, observability, SIEM (Splunk via HEC, Microsoft Sentinel, IBM QRadar), and enterprise application integration. Deployment philosophy: Gridlight adopts your standards, not the other way around.
- [Services](https://www.gridlight.ai/services): Forward Deployed Engineering services for deploying the Gridlight control plane, integrating the first private AI use case, measuring against your defined success metric, and expanding workflows inside your environment.
- [Security & Compliance](https://www.gridlight.ai/security-and-compliance): How the architecture eliminates the entire category of cloud-AI data-exposure risk — not through settings or vendor contracts, but by never sending data outside your environment in the first place.
- [Architecture](https://www.gridlight.ai/architecture): The technical inference control plane that runs inside your environment, on hardware you own, in networks you control.
- [Data Flow](https://www.gridlight.ai/data-flow): The data-gravity argument — bring AI to the data, not the data to the AI — and how Gridlight's data flow keeps information in place.
- [Cost Model](https://www.gridlight.ai/cost-model): The real cost of cloud AI at scale, modeled over 24 and 36 months, versus owned infrastructure.
- [Use Cases](https://www.gridlight.ai/use-cases): Scenarios for CIOs, CISOs, data leaders, internal AI builders, manufacturing teams, and technical partners.
- [Docs](https://www.gridlight.ai/docs): Implementation notes, API patterns, security posture, and deployment topology. Includes [Quick Start](https://www.gridlight.ai/docs/quickstart) and [Developer Docs](https://www.gridlight.ai/docs/developers).
- [Contact / Book a demo](https://www.gridlight.ai/contact): Request a private demo; scheduling via [Book a private demo](https://meetings-na2.hubspot.com/gabe-deale/demo).

## Core positioning

- The problem enterprises face with AI today is not a tools problem or a budget problem — it is an architecture problem that compounds with every deployment added on borrowed infrastructure.
- Fragmented tools, rising token bills, and sensitive data leaving the environment on someone else's terms are symptoms of running AI like an experiment rather than as owned infrastructure.
- The organizations winning with AI are building on infrastructure they own and control, not on a vendor's cloud.

## FAQ

**What is Gridlight?**
Gridlight is private AI infrastructure — a purpose-built inference control plane that runs entirely inside your own environment. It delivers cloud-like AI functionality (local inference, model routing, capacity governance, continuous learning, and audit) on hardware you own, without sending data to an external cloud API.

**How is Gridlight different from using a cloud AI API (e.g. a hosted LLM)?**
A cloud API requires sending your data to a third party's inference endpoint. Gridlight runs inference locally inside your environment, so data never leaves. It is not a wrapper around a cloud API; it is the control plane that runs the models where your data already is.

**Does Gridlight store or process my data as a vendor?**
No. Gridlight is infrastructure, not a data processor. It holds no data and requires no data processor agreement, and it creates zero new data-vendor relationships.

**What does "bring AI to the data" mean?**
Cloud AI suffers from data gravity: your data lives in your environment, and moving it to a cloud inference endpoint — even temporarily or encrypted — creates risk, latency, and liability. Gridlight inverts this by moving the inference capability to where the data already lives, instead of moving the data to the inference.

**Which hardware does Gridlight run on?**
Gridlight is hardware-agnostic. It supports any GPU vendor, including NVIDIA, AMD, and specialized AI accelerators. You run it on hardware you already own.

**How does Gridlight handle multiple models?**
Gridlight is a single control plane that routes each workload to the right model for that workload, while requiring only one integration point in your application layer regardless of how many models or use cases you deploy.

**How long does deployment take?**
In a standard enterprise environment, typical time from installation to first production inference is under two weeks.

**How does Gridlight address security and compliance?**
By architecture rather than configuration. Because data never leaves your environment, the entire category of cloud-AI data-exposure risk is eliminated at the source — not mitigated through settings, vendor contracts, or transit encryption. Inference activity, security events, and policy violations feed into your existing observability and SIEM tooling (e.g. Splunk via HEC, Microsoft Sentinel, IBM QRadar).

**Does Gridlight integrate with our existing identity, security, and observability stack?**
Yes. Gridlight is designed to adopt your existing standards — identity infrastructure, security tooling, governance frameworks, and SIEM/observability — rather than replacing them or creating a parallel governance structure.

**Who is Gridlight for?**
Regulated industries, sovereign enterprises, and organizations that need cloud-like AI functionality inside environments they control — CIOs, CISOs, data and platform leaders, internal AI builders, and manufacturing teams with strict data-residency or compliance requirements.

**What about cost?**
Cloud AI pricing feels affordable at pilot scale but changes dramatically as usage grows — and in enterprise environments usage always grows. Gridlight's cost model compares the real cost of cloud AI at scale against owned infrastructure over 24- and 36-month horizons.

**How do I get a demo or talk to Gridlight?**
Visit [Contact](https://www.gridlight.ai/contact) or schedule a private demo directly via [Book a private demo](https://meetings-na2.hubspot.com/gabe-deale/demo).

## Contact

- Website: [www.gridlight.ai](https://www.gridlight.ai)
- Book a private demo: [meetings-na2.hubspot.com/gabe-deale/demo](https://meetings-na2.hubspot.com/gabe-deale/demo)