Engagement
Three ways to engage.
From a paid proof of value to a multi-year build, each step deepens the commitment and the access to Plexus™ and the team behind it. Whichever one you choose, you decide how much autonomy your agents run with.
§ 01
Proof of Value
Prove it on your own workload.
A paid, fixed-fee engagement on a fixed scope. We stand Plexus up against one real workload of yours and deliver the evidence it produces, so the decision to go further is made on results, not a pitch.
Fixed fee, fixed scope
§ 02
Guided Onboarding
Get your teams running on Plexus.
A one-month cooperative engagement. We install Plexus on-prem and connect it to the agent tools your team already runs, such as Claude Code and OpenAI Codex. Then an AI engineer trains your people, from GRC and security operations to the AI team, IT, and finance, on how to read the dashboard, act on it, and integrate it into how they already work.
One month, with an AI engineer
§ 03
Design Partner
Build Plexus with us.
A three-year program with a dedicated AI engineer on site. Everything in Guided Onboarding, plus our harness, which carries your audited agents onto real applications and desktops, and your own on-prem pipeline to train or augment a local model on your business's work. You shape the roadmap, on preferential terms.
Three-year program, engineer on site
In every one, you choose the autonomy tier. Your agents run exactly as supervised or as independent as you decide, from every action approved before it runs to fully air-gapped.
See the autonomy tiers →Design Partner exclusive
Your agents get smarter on your work. Privately.
As a Design Partner, your agents do not just run on Plexus. They improve on your work, without any of it leaving your environment.
Fully on-prem, fully private
The pipeline runs entirely in your environment. Your data, your agent trajectories, and your proprietary workflows never leave your infrastructure or touch a shared model. The model trained on your work is yours alone, never used to serve another customer.
Learns from real work
Plexus already records every agent episode. The pipeline curates and outcome-scores the best of them, trains or augments a local model on your own trajectories, and deploys the result back to your agents.
Better and cheaper on your tasks
A small model specialized on your workloads can match a large general one on the work you actually do, and run faster and cheaper doing it.
How it works
- 1
Capture
Plexus records every agent episode as it happens: the traces, the outcomes, the artifacts.
- 2
Curate & score
The pipeline selects the strongest episodes and scores them by outcome.
- 3
Train the adapter
It fine-tunes or augments a local model on your own trajectories, on your hardware.
- 4
Deploy
The specialized model goes back to your agents, better on the work you actually do.
Built on our own distillation workbench and a local-GPU training stack, deployable on your hardware.
Find the right way in.
Tell us how you run agents today and what you need to prove, and we will point you at the step that fits.