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Test RooGenAI. Decide later.

Validate CB LLMs using your model, your workload, and the accelerator baseline your team already trusts.

Discuss a Pilot Pilot Overview

Pilot overview

Goal: Prove value before changing production.

Typical Scope

  1. One customer-selected model

    Start with a model that matters to your team.

  2. One representative workload

    Freeze a repeatable evaluation case.

  3. Your current accelerator baseline

    Compare results under matched conditions.

  4. RooGenAI evaluation support

    Work together through setup and measurement.

Define the finish line before the test begins.

Acceptance briefCustomer-defined requirements, agreed before testing
  • Baseline model and representative workload
  • Measures, thresholds, and quality guardrails
  • Integration constraints and evaluation access
  • Decision owner and review point
01

Measurable improvement

Improve the selected energy, throughput, latency, or cost measure against the existing baseline.

02

Quality retained

No meaningful degradation on the quality checks agreed upon for the workload.

03

Integration accepted

Meet the customer’s practical requirements for evaluation and any next step.

Fully reversibleNo lock-in from the evaluation. No initial migrationProduction remains unchanged during testing. Evidence firstAdopt only after requirements are met.

Built for teams with a workload worth proving.

A strong pilot starts with operational control, repeatable demand, and measurable outcomes.

01Controls or self-hosts LLM inference
02Has meaningful GPU spend or inference volume
03Runs a repeatable, representative workload
04Tracks performance and quality KPIs

Pilot request

Tell us about your workload.

No files are uploaded. Formspree processes and stores your submission and emails it to RooGenAI. RooGenAI uses the requested information only to evaluate the pilot fit. Do not include credentials, model files, proprietary prompts, customer data, or other confidential information. Review our Privacy Notice and Pilot Data Handling before submitting.

Include architecture, checkpoint family, and parameter size when possible.
GPU model, serving runtime, and deployment environment.

Submitted information is sent to RooGenAI for pilot-fit review.