F // FOREMETRIC.AI
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Ecosystem Features

80% TO YOU

$HSIG MINING

During active foreground sessions (15–30 min/day) and background activity recognition, your phone captures verified behavioral signals. Companies pay for access. You automatically receive 80% of NET revenue from every payment (after infrastructure costs) in $HSIG tokens.

Avg. $15–30 / month per active user
YOU CONTROL

SIGNAL PASSPORT

Share your behavioral profile on your exact terms. Set how many times it can be accessed (1 to 9,999), which data sectors are visible, and revoke access anytime instantly on-chain. Every access = $HSIG earned.

1 query = instant $HSIG payment

ORACLE

Personal AI analyst. Predictive insights about your state and productivity, based on real behavioral patterns.

Referral Earnings Calculator

See how much you can earn from referred devices in ForeMetric Protocol.

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Your referral income:

$10/ Month

Earnings are estimates only. Network bonus applies to direct referrals (1 level). This is not a multi-level marketing program.

Income comparison

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Native TON

Login with Tonkeeper. Zero registration. Instant payments.

Hardware-Attested Privacy

Phase 1: disclosed trusted-operator key custody. Phase 2 target: AMD SEV-SNP + COCOON TDX (Phase 2, Q1 2027) attested processing. Raw vectors released only to approved enclaves.

BUSINESS MISSIONS

Complete real tasks from companies directly. Visit a location, test an app, verify a listing. Instant $HSIG payment after on-chain verification.

B2B ANALYTICS ORACLE

For businesses: verified behavioral cohort insights without personal data. Precision targeting at a depth no cookie ever could.

// B2B PREDICTIVE ANALYTICS API

What a B2B predictive analytics API is — and how ForeMetric delivers one without personal data

A B2B predictive analytics API is an endpoint that returns forecasts about audience behaviour — churn probability, lifetime value, next best action, cohort intent — instead of raw event logs. Your team sends a question; the API answers with a score, a confidence level and the factors behind it. ForeMetric provides that layer on top of consented behavioural signals from real, verified people, processed inside hardware enclaves so no personally identifiable information ever reaches the buyer.

How the ForeMetric predictive API works

Signals are captured on the user's own device, stripped of identifiers locally, and encrypted before they leave the phone. Computation happens inside isolated Trusted Execution Environments (ARM TrustZone and Apple Secure Enclave on-device; disclosed trusted-operator key custody in Phase 1 and AMD SEV-SNP + COCOON TDX (Phase 2, Q1 2027) attested enclaves in Phase 2 on the server side). A query never touches raw logs — it touches vectors that only exist inside the enclave.

The response you receive is deliberately narrow: an aggregated cohort prediction plus a cryptographic attestation proving the computation ran inside a genuine enclave on genuine, Proof-of-Behavior-verified signals. Buyers cannot reconstruct an individual from an answer, which is exactly what makes the data legally durable.

  • Cohort predictions: churn probability, LTV estimation, next best action.
  • Audience Radar profiles: aggregated behavioural patterns with no PII.
  • Attestation: proof the computation ran inside a secure TEE (Phase 2, Q1 2027) on verified signals.
  • Settlement: every query is metered and paid on the TON blockchain.

Why this is different from cookies, panels and data brokers

Third-party cookie pools and broker databases degrade fast: consent is questionable, identity graphs drift, and a growing share of the traffic behind them is synthetic. Survey panels are cleaner but tiny and self-reported. ForeMetric sits in a third category — continuous, cross-context behavioural signal, contributed knowingly by the person it describes.

Every signal is filtered through Proof-of-Behavior, a consensus layer combining cryptographic validity, interaction micro-timing biometrics and cross-stream verification, with a target bot-filtering accuracy of 93–97%. You are not paying for bot traffic, and you are not inheriting somebody else's consent problem.

Where teams use it

The API is built for questions that traditional analytics answers late or not at all — the ones where behaviour outside your own product is the missing variable.

  • Retention teams: flag accounts crossing a churn-risk threshold before the cancellation, not after it.
  • Growth and AdTech: target verified behavioural cohorts instead of decaying cookie segments.
  • AI labs: source verified, consented human signal for training and evaluation.
  • Fintech, DeFi and Insurtech: enrich risk models with cross-context activity patterns.

Want to see the exact query format, cohort output and attestation payload? The whitepaper documents the API surface, the tokenomics behind query settlement, and the enclave architecture in full.

Read the whitepaper →
B2B Metrics

5 Gold Standard Metrics

High-precision predictive metrics for AI labs, hedge funds, retail and insurance companies.

CPI
Cognitive Persistence Index
Cognitive persistence
IAP
Intent-to-Action Probability
Conversion probability
BDM
Behavioral Drift Momentum
Behavioral drift
ASR
Authentic Signal Ratio
Signal authenticity
SFT
Saturation & Fatigue Threshold
Cognitive endurance
Insights-as-a-Service

Insights-as-a-Service for Business

[AI LABS]

Verified behavioral datasets with ASR > 0.9. Solution to Model Collapse for training and RLHF.

Premium pricing: 10–20× vs synthetic data
[HEDGE FUNDS]

Behavioral Futures: Consumer Stress Index, Job Displacement Anxiety Score.

Alternative data with 26.5% CAGR
[ADTECH & RETAIL]

CPM premium 3–5× for high-IAP users. Ad fraud elimination via Proof-of-Behavior.

GDPR compliant by design
[INSURERS & FINTECH]

Personal pricing via Signal Passport. Up to 30% discount for stable profiles.

Compliance cost reduction 40–60%
B2B API

B2B API Response Example

JSON response with verified cohort metrics — no raw data exposed.

GET /v1/cohorts/insight200 OK
{
  "cohort_id": "crypto_traders_moscow",
  "metrics": {
    "authentic_signal_ratio": 0.96,
    "cognitive_persistence_avg": 0.74,
    "intent_to_action_probability": 0.81,
    "behavioral_drift_momentum": 0.45
  },
  "insight": "High conversion vector expected within 48h"
}

Behavioral Analytics FAQ

Direct answers about churn prediction, zero-party data monetization, and ForeMetric behavioral analytics API integration. Written for people, structured for AI assistants.

Predicting churn based on behavioral data consists of four steps:

  1. Signal Aggregation: Aggregating activity patterns such as session cadence, intervals between actions, feature adoption depth, and attention retention.
  2. Vector Formation: Creating anonymized behavioral profiles based on activity over the last 30–90 days.
  3. Predictive Analysis: Processing vectors through specialized ML models. ForeMetric's predictive analytics API returns specific churn probabilities (0 to 1) and key risk factors rather than raw logs.
  4. Action: Automatically triggering retention campaigns for users crossing a critical risk threshold (e.g., 0.65+).

Because ForeMetric verifies every signal at the protocol level via the Proof-of-Behavior algorithm, prediction models are fully protected against distortions caused by bot traffic and simulations.

A B2B predictive analytics API allows product teams and marketers to receive ready-made predictions regarding audience behavior without needing to build their own expensive internal Data Science stack.

The ForeMetric API operates within a decentralized infrastructure: encrypted behavioral signals are processed strictly inside isolated server-side TEE enclaves (Confidential Computing) (Phase 2, Q1 2027). The buyer sends a query and receives:

  • Cohort Predictions: Churn probability, LTV estimation, and Next Best Action.
  • Audience Radar Profiles: Aggregated behavioral audience patterns without exposing any personally identifiable information (PII).
  • Cryptographic Attestation: Verification proof that the computation was executed inside a secure TEE (Phase 2, Q1 2027) environment and the data is genuine.

All API queries are validated and settled in the protocol's utility tokens on the TON blockchain.

Zero-party data is information that a user owns and intentionally permits to be used for commercial or analytical purposes. This differs from first-party data (metrics within a single app) and third-party data (hidden databases bought from data brokers).

In the ForeMetric ecosystem, behavioral signals turn into sovereign zero-party assets through the Signal Passport:

  1. Users utilize a sovereign interface to define their access boundaries: which signal categories, for which market sectors, and for what duration they are willing to open.
  2. B2B counterparties can execute predictive queries to the API only within the limitations set in the Signal Passport.
  3. Up to 80% of net B2B revenue from analytical queries is automatically distributed to the users whose signals participated in the calculations via the project's tokenomics on TON DEX.

  • Zero-party: Directly provided by the user | Explicit, conscious consent | High predictive value based on intent.
  • First-party: Observed within a single product | Implicit consent (T&C) | Limited to the platform's perimeter.
  • Third-party: Purchased from data brokers | Questionable/Absent consent | Low predictive value, degrades quickly.
  • Behavioral Signals (ForeMetric): Cross-context action stream | Cryptographic consent (Signal Passport) | Maximum predictive value via real-time models.

Yes, but only if the architecture completely excludes the centralized storage of raw personal data (PII). ForeMetric implements Privacy by Design (Article 25 GDPR) at the protocol level:

  • Raw behavioral logs are encrypted on the source side and distributed across decentralized storage.
  • All analytical computations and queries occur strictly within isolated server-side TEE enclaves (Phase 2, Q1 2027). The code inside the enclave is hardware-protected from third-party tampering (including node operators).
  • The API outputs exclusively high-level predictive metrics and scores — buyers cannot physically extract or reconstruct the raw data of a specific individual.
  • Revoking cryptographic permission in the Signal Passport instantly strips the network of the technical capability to decrypt associated signals for new queries, ensuring the "right to be forgotten."

The protocol integrates a multi-layered consensus called Proof-of-Behavior (PoB). This algorithm evaluates:

  1. Technical Validity: Verification of cryptographic signatures and signal immutability at the network node level.
  2. Behavioral Biometrics: Analyzing interaction micro-timings, context-switching patterns, and session dynamics that cannot be replicated by scripts.
  3. Cross-Verification: Cross-checking independent analytical streams.

Target bot-filtering accuracy is 93–97%. Only PoB-verified signals are allowed into TEE (Phase 2, Q1 2027) models, ensuring B2B clients get clean analytics without overpaying for synthetic traffic.

In order of analytical significance for predictive models:

  1. Session Cadence & Density (intervals, return regularity) — a core marker for predicting LTV and long-term churn.
  2. Feature Adoption Paths — a key signal for determining a client's readiness for a tariff upgrade (Upsell).
  3. Cross-Category Patterns (context switching dynamics) — signals new needs or competitor defection risks.
  4. Time Windows of Activity — optimizes targeting accuracy and trigger communications.

Amplitude, Mixpanel, and Segment are internal product analytics tools (First-Party Product Analytics). They collect and visualize historical events occurring strictly within your own app and require deploying a complex internal data stack.

ForeMetric is a decentralized protocol for behavioral intelligence:

  • Beyond a Single App: We aggregate cross-context behavioral trends with user consent via the Signal Passport.
  • Focus on Predictions, Not Charts: Instead of standard historical dashboards, the ForeMetric API delivers real-time probabilistic scores (churn, purchase intent, segmentation).
  • Confidential Computing: Data security is guaranteed by cryptography and TEE enclaves (Phase 2, Q1 2027) at the infrastructure level, not just legal terms.
  • Flexible Web3 Pricing: Payment is per specific analytical query in tokens on the TON blockchain, without rigid annual contracts based on Monthly Tracked Users (MTU).

We do not have fixed seat licenses or hidden storage fees. Pricing is fully transparent and tied to a utility Pay-per-Query model:

  • Settlements are made in tokens via the TON blockchain.
  • The cost of requested cohort models and Audience Radar reports depends on the computational complexity of the query and the required depth of historical data.
  • Up to 80% of the query cost (after network expenses) is directly converted into rewards for users providing data liquidity.