Tier 1Days 0-30
Deployment Sprint
Scope the first use case, install and connect the Gridlight control plane, and complete initial integration with auth, data sources, and monitoring.
Forward Deployed Engineering Services
Get private AIintoproduction.
Gridlight FDE services close the gap between a private AI use case and a working deployment on infrastructure you control. Certified engineers deploy the control plane, integrate the first workflow, and measure success against a defined baseline.
Every prompt and byte stays inside your perimeter. Sovereignty is the architecture.
Why services
Platform value compounds when the first use case is live.
Many regulated teams know which AI workflows matter, but the highest-value use cases often sit behind sensitive data, strict network boundaries, and existing enterprise systems. Gridlight's FDE model pairs the private inference platform with embedded engineering support so the first deployment is scoped, installed, integrated, and measured as one motion.
The engagement starts with a success metric, connects Gridlight to the systems named in scope, and produces a measured 30-day report instead of an open-ended implementation project.
Engagement paths
Pick an FDE path.
Tier 230-90+ days
Embedded Integration Engagement
Dedicated Forward Deployed Engineers build your workflows, agentic pipelines, model routing policy, and compliance or audit wiring.
Tier 3Monthly retainer
Ongoing Advisory / Fractional FDE
A part-time embedded engineer supports continued expansion: new use case scoping, model swaps, routing updates, and private AI architecture guidance.
Tier 460-90 days
Small Language Model Development
Fine-tune and package a small, task-specific language model on your own data, optimized to run on your Gridlight-deployed hardware.
Delivery model
Deploy, prove, and expand inside your environment.
Deploy
Stand up the private inference foundation.
Gridlight works inside your environment to connect hardware, identity, data sources, observability, and the first target workflow.
Prove
Measure against the baseline.
The success metric is defined up front, measured against baseline, and reported after the first 30 days so the engagement has a concrete outcome.
Expand
Turn the first use case into a shared platform.
Once the first workflow is live, the same control plane can support additional workflows, model routing policies, and team-specific governance.
Deliverables
Each engagement is anchored to practical outputs.
Gridlight control plane deployed and connected to hardware you own or designate.
First use case integrated with your authentication, data sources, and monitoring.
Baseline and 30-day success-metric report measured against the metric you define.
Documented deployment runbook for the installed environment.
For SLM engagements: fine-tuned model evaluation report and packaged model deployed to your hardware.
Scope boundary
Clear boundaries keep the engagement tied to private AI outcomes.
In scope
Architecture design and deployment of the Gridlight control plane.
Integration with your named systems, including authentication, data sources, monitoring, and observability.
Workflow and agentic pipeline engineering for the use case or use cases named in the engagement.
Scoped small language model fine-tuning and packaging when Tier 4 is selected.
Out of scope
General IT staff augmentation unrelated to Gridlight architecture or integration work.
Open-ended frontier-model research or training unconnected to a defined SLM deliverable.
Scope, timeline, or fee changes without a written amendment.
Your role
FDE work moves fastest when access, metrics, and decision rights are clear.
Name a sponsor with authority to define the success metric and approve scope.
Provide timely access to relevant systems, data sources, stakeholders, and environment details.
Confirm hardware and network prerequisites during kickoff.
For SLM work, provide representative training data and define evaluation criteria up front.
Next step