A question worth asking.
Your knowledge of the problem matters. We begin with what you want to change, who it should help, and what a useful result would look like.
AN OPEN WORKSHOP FOR PEOPLE + AI
What could a small team build if it had a little more help thinking, exploring, and making?
Meet Proteus. Six AI roles, working together under your direction. Built to help turn ambitious questions into work you can use.
Step insideNo special vocabulary required. Just a question.
01 / THE POSSIBILITIES
You don’t need to know which model to use.
Start with something you would like to make possible.
Imagine a local repair shop that needs a clear, useful website. The team explores what customers need, plans the pages, designs the experience, builds it, and checks that the important parts work.
A working preview, the decisions behind it, and any issues still to resolve. You decide what goes live.
Each role passes an actual piece of work to the next: research, a plan, a design, then code. A separate reviewer checks the result. The handoff includes what is finished and what is still uncertain.
An explanation of the workflow, not an AI session running in your browser. Results depend on the models, setup, and human review.
02 / A WINDOW INTO THE WORK
Here is what coordination looks like behind the scenes. Work is divided, knowledge is carried forward, and results are checked before they reach you.
ILLUSTRATIVE REPLAY · narrative steps, not a live process
→ Intake: the Director receives your brief and clarifies the goal.
→ Frame: agree on the outcome, constraints, and review boundary.
→ Route: choose the specialist role the work actually needs.
→ Knowledge: load relevant decisions and the sources behind them.
→ Local helpers: Redact · Gist · Title; hold uncertain results.
→ Models: use local or hosted models to suit the task and setup.
→ Handoff: save the artifact, owner, verdict, and open questions.
→ Pipeline: frame → research → architect → design → build → verify → report.
$ python3 build/sweep-gate.py # kit assembly: check the sources
$ python3 build/review-gate.py # require the review record
$ python3 build/generate.py --params examples/demo-consulting.yaml --out /tmp/demo-team
→ Review: check the delivered result, not a claim that it worked.
→ Report: show what is ready, what is uncertain, and what comes next.
PROTEUS / 6 AGENTS · READY FOR HUMAN REVIEWReal build commands sit alongside explanatory steps.
Run the setup yourself
03 / THE HUMAN PART
AI can explore, draft, and build. It can also miss the point. That is why Proteus gives the work a structure, and keeps people in charge of its purpose.
Your knowledge of the problem matters. We begin with what you want to change, who it should help, and what a useful result would look like.
A researcher gathers evidence. An architect makes a plan. A designer shapes the experience. A builder makes it. Each leaves something the next can use.
A separate reviewer looks for mistakes. The director brings the results together. You see the evidence and decide whether the work is ready.
Six roles. One shared project. Human judgment at the beginning and the end.
04 / KEEP ASKING
Open a question. Follow it as far as you like.
Yes, with a compatible local model and enough memory to run it. Small specialist models can do narrow jobs, while larger models handle harder work. Hosted models are another option. The right mix depends on the task, hardware, and privacy needs.
Proteus documents optional local helpers: Redact flags sensitive text, Gist suggests a topic, and Title drafts a label. These helpers do not replace reasoning or human review. An uncertain redaction must be reviewed before text leaves the device.
Explore local preprocessingThink of a workshop notebook. Decisions, sources, and completed work are saved in files. When a new session begins, the team loads the relevant notes instead of relying on a conversation that may be gone.
This takes explicit recording and sensible retrieval. It is a way to preserve continuity, not a promise of perfect memory.
Read about durable stateThe work should stop at a check, return to the role responsible, and be corrected. If an agent stalls, bounded recovery rules limit retries and bring unresolved problems back to the person supervising.
Review reduces the chance of error. It does not eliminate it. Important decisions still need qualified human judgment.
See the working rulesThe open-source kit, templates, build gates, and generator are available now. You will need Hermes, Python, and some comfort with a terminal. Setup includes manual steps.
The conversational setup agent and a one-command installer are not shipped. The public kit has not yet been independently demonstrated to deliver a real product end to end. We keep that distinction visible.
Open the setup guide05 / PROTEUS AS A SERVICE
Proteus-kit is open source, released as an ASKA portfolio project. Running it for real, in your environment, with your data and your models, is professional work. That work is the ASKA Proteus service: setup, deployment, training, and the ongoing operation of a governed agent team. Two ways to engage, scoped to your environment during consultation.
ONE-TIME
$9,300 USD
One-time setup, local deployment & training, when the client provides the local hardware. Training is included.
ONGOING
$540 USD/month
Ongoing operation after deployment, scoped to your environment.
The kit can be deployed locally on suitable client hardware. If ASKA supplies the hardware instead, that is separate from the setup fee and is quoted according to the performance you need. Hardware scope is set by required performance, not a single published figure. Service scope is bounded by your deployment, hardware, provider access, security policy, and the agreed support terms. ASKA does not guarantee uptime, response times, savings, or model performance.
Start with a free consultation call and a Proteus product demo.
THE DOOR IS OPEN
Explore the kit yourself, or bring us a question.
You don’t need to have the whole answer yet.