Don't Take Our Word for It. Test It on Your Own Data.

A structured engagement that benchmarks Falcon against your actual production workloads — on your data, in your architecture, before any commercial commitment.

A test flight is a structured engagement where Haevek's customer engineering team configures Falcon against your actual production workloads, collects empirical benchmarks, and delivers a value assessment covering speed, cost, and infrastructure reduction on your specific architecture. The engineering work takes up to two weeks. The total engagement runs two to eight weeks depending on your organization's complexity. The test flight costs you nothing. If Falcon meets the agreed benchmarks, both parties move directly into commercial negotiations.

The benchmarks Haevek has published on this site came from real production deployments and will hold up to independent scrutiny. The business case for adopting Falcon should rest on your data, your architecture, and your infrastructure cost profile. A test flight produces that.

Is this the right next step?

A test flight runs against a subset of your pipelines, not your full stack. The goal is to generate a validated proof point on your specific architecture: empirical data that tells you whether the performance and cost improvement is real enough to justify rolling Falcon out across the rest of your workloads.

The workloads worth choosing for the test are the ones representative of your broader job portfolio. A batch ETL pipeline, a streaming workload, and an analytics or inference job cover the patterns most teams run. A result on those three gives you a credible basis for estimating what the full program looks like.

If you can recognize your situation in any of the use case results published here, the test flight is how you find out whether those numbers hold on your data.

What you bring

Two things are required from you: a defined use case with the pipelines you want to test, and reference data plus a current benchmark.

The use case definition does not have to be elaborate. A concrete pipeline description is enough: an upstream data source, the transformations applied, and the downstream destination. A batch ingest or ETL workload, a batch analytics or AI inference workload, and a streaming ETL workload represent the three most common starting configurations, and any combination of up to three pipelines works. If you have source code, bring it. Source code makes the validation process clean: Haevek's team can confirm the Falcon implementation performs exactly the same transformations at every step. Pseudocode and detailed process descriptions work as well and require additional validation effort to confirm equivalence.

For the benchmark, bring whatever measurement you have. How long does the pipeline run, on what infrastructure, at what cost? Many teams do not track this precisely for batch jobs that run overnight. If you do not have it measured, collecting a clean baseline becomes part of week one. The before/after comparison is the centerpiece of the case study report, so the baseline gets measured properly regardless of whether it arrives at kickoff or gets established during setup.

Haevek can run the test in its own environment or in yours depending on your data sensitivity and deployment requirements. The engagement is designed to run largely on Haevek's side. Your team joins for kickoff, provides access to data and the current benchmark, and checks in at agreed points. The lift is light.

How the engagement runs

Week one is setup. Haevek's team runs technical interchange meetings to understand the current state of your workloads, produces design documentation covering what functional equivalence looks like for each pipeline, and deploys into your environment if your security requirements call for it. Any compliance or security accreditation processes that need to run alongside the technical work start here, so there is no delay between the end of the test flight and a production deployment.

The following weeks are configuration and evaluation running in parallel. Haevek builds three variants of each workload. The first wraps your existing logic and runs it through Falcon's orchestration layer. The second pulls specific transformations into Rust using more of the Falcon standard library. The third is a full refactor of the pipeline built natively on Falcon.

Those three variants show you the performance improvement available at different levels of migration investment. Minimal adoption produces a meaningful result. Full adoption produces the headline performance numbers from the use case benchmarks.

Having all three data points lets you estimate the migration effort for your team and what you get back at each stage.

Training is available throughout the engagement: your engineers can go through structured sessions on how to deploy, manage, and build new workloads on the Falcon Compute Platform. Teams that want to co-develop the refactored variants alongside Haevek's engineers can do that too.

What you get

The engagement closes with a case study report covering performance characteristics, scaling criteria, known limitations, and a value assessment of the configured Falcon workloads. Depending on what is most actionable for your team, that takes the form of a written report, a slide deck, or a working session.

Haevek's standard test flight measures against three success criteria, with additional metrics established per the specific use case and customer environment:

• Performance improvement: a demonstrable improvement in end-to-end software runtime on equivalent or lower-cost infrastructure, benchmarked against your prior environment.
• TCO reduction: a material reduction in total cost of ownership (software licensing, compute infrastructure, maintenance, and support) over a twelve-month post-implementation period, aligned to outcomes agreed at the start of the engagement and benchmarked against the prior environment.
• Scalability: maintained or improved performance and cost efficiency as workload size or concurrency increases, demonstrated through multi-executor or multi-node scaling tests.

Haevek's customer engineering team has met all three criteria in every test flight completed to date. When the results come in, you have empirical data on your own workloads. If the criteria are met, the path to production is immediate. Haevek's security and compliance processes run in parallel from week one, so there is no gap between the end of the test flight and a production deployment. The team can move straight to making impact.