P34 API Platform Beta

Send the deals.
Get back the plan.

P34 is a pre-trained economic decision model behind one REST API. Post the options in front of you — hundreds to thousands of candidate deals — with the history of what happened before. It returns a quantity for every option, zero meaning pass, and the predicted profit of the plan as a whole.

  • Pay as you go: $1 per token
  • No subscription
  • Validation and input tests are free
  • Async REST · JSON or Parquet
three calls
# 1 · validate: free, no key
curl -s -X POST https://api.hyperc.com/v1/validate \
  -H "Content-Type: application/json" --data @request.json

# 2 · fit: returns a session id in seconds
curl -s -X POST https://api.hyperc.com/v1/fit \
  -H "Authorization: Bearer $P34_API_KEY" \
  -H "Content-Type: application/json" --data @request.json

# 3 · poll: minutes later, the plan
curl -s https://api.hyperc.com/v1/result/$SESSION_ID \
  -H "Authorization: Bearer $P34_API_KEY"
The whole loop, step by step: Quickstart →
done · recorded run · unlisted keys = pass
{"status": "done", "model": "rc012.2", "n_selected": 10,
 "predicted_profit_sum": 59.82,
 "menu": [{"key": "h10-1519-1055", "qty": 2.0, "profit": 9.19},
          {"key": "h10-1519-1056", "qty": 2.0, "profit": 4.26}, …]}
The model

One decision, made across the whole list

Most models score rows one at a time. P34 answers the question a buyer actually faces: given everything on offer right now, which options to take, how many, and what profit to expect from the set. It is trained against realized economic outcomes, not text, and it calibrates to your market from your own history before it answers.

You send

menus
Every option on the table now, and at past decision moments — including the ones nobody took.
sales
What happened to the options that were taken: the money tape.
business_description
How your unit economics work, in plain words: fees, holding costs, write-offs.

You get back

qty
A size for every option. 0 means pass — and most options come back 0. Refusing is the product.
profit
The predicted profit of each option at that size.
predicted_profit_sum
The plan's predicted total, calibrated as a sum.
confidence_sweep
How the plan changes if you ask for more or less certainty — without paying for another fit.
Pre-trained

You do not train a model. Each fit calibrates P34 to your market from the history you send, then decides today's menu.

Minutes, not milliseconds

A fit is an asynchronous job that takes minutes. P34 is built for purchasing-style decisions, not high-frequency trading.

Your code decides

P34 places no orders. It returns a plan; your application, or a person, decides what to buy.

A real result

1,200 offers in, 10 purchases out

Recorded run · model rc012.2 · 26 September 2026 · t5market simulated market
1,200
offers on the menu
46,800
quantity options (39 sizes each)
10
selected · 21 units · pass 1,190
$59.82
predicted profit on $593.14 committed

Session 9e6c8df2. The simulator's outcome for the same quantities was $66.98. Recorded run, not generated now: a simulator outcome is a counterfactual for the quantities shown, not an executed trade, a customer result or evidence of live-market profitability. Download the full result (JSON).

Try it now

Validate a request before you sign up

POST /validate checks a request's structure, columns, menu rules and volume floors. It needs no key, queues nothing and charges nothing.

Run it on our sample request — 300 generated offers from a made-up reseller — then on your own data. When it passes, an input test ("mock": true) runs every check a real fit runs, still free.

Follow the quickstart

validate
# the sample request: 300 generated offers from a made-up reseller
curl -sO https://hyperc.com/lp/sample/p34-sample-request-v1.json

# validate it: free, no key, nothing queued or charged
curl -s -X POST https://api.hyperc.com/v1/validate \
  -H "Content-Type: application/json" \
  --data @p34-sample-request-v1.json
response (abridged)
{
  "ok": true,
  "errors": [],
  "counts": {
    "menus_rows": 1800, "menus_keys": 300, "t0_rows": 900,
    "history_rows": 900, "menus": 13, "sales_rows": 450
  },
  "estimate": {
    "pricing_mode": "runtime",
    "note": "an estimate from row counts alone; …"
  },
  "checked": "structure, columns, menu-0/T=0 rules, volume floors. …"
}
The platform

Built like a platform, priced like a utility

Async jobs

POST /fit answers in seconds with a session_id. Poll GET /result/{id}; cancel with DELETE /session/{id}.

Free until you fit

Validation needs no key. Input tests return placeholders in the real result shape, clearly marked, on every key.

Economics in plain words

Describe fees, holding costs and write-offs in a paragraph. P34 compiles it into the code that values your history — and reuses it while the description and schema stay the same.

Versioned models

Pin model for reproducible results or follow default. The version that ran is echoed back.

Tunable selectivity

confidence_correction trades fewer, surer picks against more. The sweep in every result shows the trade-off without another fit.

Big menus

Up to 100,000 menu rows per request, as JSON records or base64 Parquet.

Itemized billing

Every fit reports what it charged. GET /account/ledger lists every movement. Failures on our side are not charged.

Agent-ready

Four open agent skills, llms.txt and a paste-in instruction for Claude Code, Codex or your IDE agent.

Where it pays

Long menus, real money, most deals refused

P34 earns its cost where every decision faces hundreds to thousands of candidate deals and most of them should be turned down. If a menu holds a handful of options, the market, the collection or the plan is wrong.

Wholesale & lot buying

This week's supplier offers, each at several order sizes: what to buy, and how many.

menu = offers × order sizes

Marketplace resale

Listings across marketplaces, priced against what similar items sold for: which to flip.

menu = listings × quantities

Virtual goods & game items

The fastest loop to prove: trades resolve in days, so history and results arrive quickly.

menu = items on the market now

Domain drops

Thousands of names expire every day: which to back-order, with what you know about resale.

menu = today's drop list

Freight loads

Loads on the board, lane by lane: which to accept with the trucks you have.

menu = loads × lanes

Auctions & liquidation lots

Pallets, equipment and returns lots: which to pursue, against your resale history.

menu = lots closing this week

Not a fit: decisions needed in under a second; a handful of options you could score by hand; trading regulated securities, derivatives or prediction markets, which sit outside the self-serve terms. Browse the computable-markets catalogue for more.

Pricing

Pay for fits. Everything before a fit is free.

Free
Shape and test your integration
$0
No account needed to validate.
  • POST /validate — no key, no account
  • Input tests with "mock": true
  • Sample request, quickstart and pytest workflow
  • Agent skills and the full reference
Try it — no key
Enterprise
P34 across a company
Let's talk
Governed rollout with your team.
  • Shadow test on your own data
  • Capped pilot, then scale with controls
  • Technical discovery and integration
Enterprise rollout

What a fit costs

WhatWhenCost
Validate a requestPOST /validate, no key or accountFree
Input test"mock": true — every input check, placeholder resultFree
Groundingyour business description or data schema is newtypically 17–20 tokens
Grounding, repeatedidentical description and schema: the compiled code is reusedreplay metered as compute
Model fitcompute time: 0.25 tokens per CPU core-hour, 5–10 per GPU-hour, at least 0.25 per calculationtypically 3–10 tokens
A failure on our sidegrounding or the fit fails for a reason that is oursNot charged

1 token = US$1. Typical figures are from recent fits (early October 2026); yours follow the size of your history and menus. Every charge is itemized: /fit reports what it charged and each ledger entry spells out its arithmetic. A grounding stopped by a problem in your input is charged for the work done, and its diagnosis says what to change. Prices exclude taxes; tokens are not refundable. Want an always-on workspace for your agent, with data tools and weekly plan credits? That is the membership, a separate offer.

Get started

From zero to your first plan

  1. Create your account

    Register free in the console and choose the pay-as-you-go API. Your key is ready the moment the account exists; keep it in an environment variable, never in code.

    Get API key →
  2. Validate and test, free

    Shape your data, run POST /validate until it passes, then an input test with "mock": true.

    Test without spending →
  3. Add tokens and fit

    Buy tokens from $15, submit an actual fit, poll the result and review the plan before anything is bought.

    Your first purchase plan →
Straight answers

Questions developers ask first

Do I need a subscription?

No. Register free, buy tokens from US$15 and spend them on fits; nothing renews. The membership ($200 a month) is a separate offer that adds a managed agent workspace, data tools and weekly plan credits.

How much does a fit cost?

Typically 20–30 tokens (US$20–30) for the first fit on new data: grounding your economics (17–20) plus compute (3–10). Repeat fits with the same description and schema reuse the compiled economics. Cost follows the size of your history and menus; the pricing page has the rates.

How is this different from a decision or classification API?

Those pick one answer from a list you define, in milliseconds, one item at a time. P34 decides a whole menu at once: it calibrates to your history and your costs, then returns a size for every option and the predicted profit of the plan. That takes minutes, and it is built for buying decisions where most options should be refused.

Can I try it before paying?

Yes. POST /validate needs no key and no account, and input tests with "mock": true are free on every key. Only actual fits spend tokens.

What happens when my balance runs out?

Calls that need tokens are refused with HTTP 429, and nothing is queued or charged for a refused call. Validation and input tests keep working. Buy tokens in the console and resubmit.

Do tokens expire?

No. Tokens you buy stay on your balance and never expire. They are not refundable.

How fast is it?

A fit takes minutes: it grounds your history, calibrates the model and decides the whole menu. It is built for purchasing-style decisions, not sub-second ones.

What data do I need?

Menus of candidate deals — hundreds at least on the current one — with past menus that include the options nobody took, a sales log of what happened, and a paragraph on your unit economics. No trading record? A history assembled from market research is accepted. See Prepare your data.

Is there an SDK?

It is plain HTTPS and JSON, so any HTTP client works. We publish a standard-library Python quickstart, a sample client and a pytest workflow in P34-API-DOCS, plus four agent skills.

What if my key leaks?

Revoke it in the console (API keys → revoke) and create a new one; a revoked key stops working at once. Keep keys in environment variables, one per application or agent, never in code, logs or URLs.

What happens to my data?

It is used to compute your fits. You can cancel a running fit and discard the session with DELETE /session/{id}. Data handling is governed by the API Terms of Use and our privacy policy.

Ship an economic decision inside your software.

Beta. P34 returns quantities and predicted profit; it places no orders and does not promise profit. You own the decisions, the capital and the results. Use of the API is governed by the API Terms of Use, presented in the console.