verified Live simulation results
KLAVE doesn't just
negotiate better.
It negotiates differently.
The simulation you just ran is not a demo of clever software. It's a demonstration of an architectural principle: the party that conceals their limit wins.
Your Simulation Results
You Paid (Manual)
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Budget exposed: 82%
KLAVE Advantage
—
—
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KLAVE Paid
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Budget exposed: 0%
Your Rounds
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KLAVE Rounds
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Probes Run
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Leaks Found
0
The math
Why human negotiators always overpay
Every offer you make is a data point. Two offers and a competent seller can bracket your ceiling. It's not a flaw in the person — it's a flaw in the protocol.
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The Leakage Problem
How manual offers expose your ceiling
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Round 1 offer ($3.80): Seller now knows your ceiling is above $3.80. Leak: ~30%.
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Round 2 offer ($4.00): Seller now knows you'll pay more. Jump size reveals urgency. Leak: ~60%.
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Pattern analysis: Two offers produce a concession curve. Statistical inference brackets your ceiling within ±8%. Leak: 82%.
Result
Seller adjusts counter-offers to extract maximum value from your inferred ceiling. You systematically overpay.
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The KLAVE Protocol
Why zero leakage is architecturally guaranteed
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Floor committed to ZK circuit: Before negotiation starts, the floor price is cryptographically committed. It cannot be revealed, even by the system operator.
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Offer function is blinded: The Rubinstein concession curve runs inside an encrypted session. No offer reveals the ceiling to any external observer.
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Mechanical enforcement: Every API response is grep-tested at build time. Floor price and buyer ceiling field variants are mechanically blocked — not by policy, by code.
Result
Seller has no side-channel data. Negotiation proceeds to the actual overlap between seller's floor and buyer's ceiling. Both parties get a fair deal.
At scale — what this means per transaction
Budget Leaked
Human: 82% · KLAVE: 0%
Price Distance from Floor
Lower is better
Human: —
KLAVE: —
Rounds to Settlement
Fewer = more efficient
Human: —
KLAVE: —
The bigger picture
The agentic economy is already here. The negotiation layer isn't.
Every major payment network is building rails for how AI agents execute transactions. Mastercard Agent Pay. Visa Intelligent Commerce. Stripe Agentic Commerce Protocol. They are all solving the same problem: how do agents pay?
The missing layer
None of them are building
what KLAVE builds.
what KLAVE builds.
They build how agents pay. KLAVE builds what price they should pay. These are not the same problem. Payment rails assume a price has already been agreed. KLAVE is what happens before any payment rail is touched.
Payment infrastructure
Mastercard Agent Pay
Visa Intelligent Commerce
Stripe ACP
Visa Intelligent Commerce
Stripe ACP
Solves: how agents execute payments at a given price. Prerequisite: a price must exist.
Negotiation infrastructure
KLAVE
Solves: what price agents should agree to, without either party revealing their financial limit. The price that the payment rails then execute.
$3–5T
Projected agentic commerce
McKinsey estimates by 2030. Every dollar of that commerce requires a negotiated price. Most will be fully automated.
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Deployed negotiation protocols
As of today, no commercially deployed bilateral autonomous negotiation engine exists with cryptographic floor price privacy. KLAVE is first.
100%
Adoption is forced
When your competitors' agents negotiate autonomously while yours negotiate manually, the price difference compounds every transaction.
Why you can't keep up manually
schedule
Speed asymmetry
An AI agent completes a full negotiation in under 12 seconds. A human negotiation averages 23 minutes. At scale, agents run thousands of negotiations per hour.
psychology
Cognitive limits
Humans anchor, fatigue, and anchor again. Agents don't. Your buyer agent running KLAVE has perfect recall of every prior settlement at this seller. You don't.
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Information leakage compounds
One leaked ceiling means higher prices at that seller forever. Sellers share intelligence. Manual negotiation history propagates across networks.
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The compounding effect
The simulation showed ~7% better outcome per transaction. Weekly groceries. Monthly contracts. Annual procurement. The gap doesn't stay small.
The architecture
Four independent layers of privacy. Each one would be sufficient. All four together are non-negotiable.
code
Layer 1: Mechanical grep test
Every build runs a test that searches the entire codebase for floor_price, floorPrice, floor, buyerCeiling — and 12 other field name variants. If any appear in an API response, the build fails. Not a code review. A machine check.
memory
Layer 2: Session-scoped decrypt-and-overwrite
Floor price is AES-256-GCM encrypted in the database. It is decrypted into memory only for the duration of a negotiation session. On every exit path — settled, failed, timed out, or error — it is immediately overwritten. Zero persistence in plaintext.
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Layer 3: ZK proof of negotiation integrity
At settlement, a Groth16 zero-knowledge proof is generated. Any third party can verify that the negotiation was conducted honestly — without learning the floor price or buyer ceiling. You saw this proof verified live in the simulation.
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Layer 4: Injection defense + AgentScope
Every listing description is screened before the floor price is encrypted into it. Agent authorization is HMAC-signed and validated before any negotiation begins. An adversarial agent cannot escalate its own privileges or extract pricing through crafted inputs.
Use cases
Any market. Any price. Zero leakage.
If a buyer has a ceiling and a seller has a floor, KLAVE can negotiate the gap — without either side revealing their limit.
storefront
Local food sourcing
A restaurant's procurement agent negotiates weekly produce prices with farm suppliers. Neither reveals their budget or floor. Deals clear at the true market rate — not the inflated one a human would accept under time pressure.
inventory_2
B2B wholesale procurement
An AI purchasing agent replenishes inventory across dozens of suppliers simultaneously. Each negotiation is bilateral and private — no supplier learns your volume ceiling or how urgently you need the stock.
code
Freelance rate negotiation
A client's agent and a contractor's agent negotiate project rate and scope without exposing either party's walk-away number. The settlement is cryptographically verified — no human posturing required.
restaurant
Surplus food redistribution
Restaurants with end-of-day surplus connect with food rescue buyers. Dynamic pricing negotiated autonomously — sellers recover value, buyers pay fair rates, and no one overpays because they revealed urgency.
precision_manufacturing
Industrial supply chains
Manufacturing agents negotiate parts pricing across supplier networks at machine speed. Every deal leaves a ZK-verified audit trail — provable fair price, no human bottleneck, no leaked procurement budget.
apartment
Real estate & commercial leasing
Tenant and landlord agents negotiate lease terms without signaling desperation or ceiling budget. The protocol enforces convergence — deals that work for both sides, settled faster than any human back-and-forth.
rocket_launch Early access
Get ahead of the protocol shift.
KLAVE works in any market where buyers and sellers meet without knowing each other's limits. The question isn't whether autonomous negotiation becomes standard — it's whether you're using it before your competitors are.
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