ODSC AI & Chalk Meetup on Jan. 29 in SF

Trust every identity decision with real‑time fraud signals

Chalk computes and serves identity, device, behavioral, and KYC features in real time. Risk models can verify users, prevent account abuse, and stop synthetic identities in single-digit milliseconds.

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Trusted by risk and identity leaders worldwide

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Why Chalk for fraud and identity

Ship new risk signals fast

Define velocity checks, device fingerprints, behavioral features, and document validity directly in Python.

Unify identity data

Combine device, behavioral, onboarding, KYC, and third-party signals into a single, consistent feature set.

Debug high-stake decisions

Inspect every feature and execution path with Chalk’s query plan viewer.

Ship new risk signals fast

Define velocity checks, device fingerprints, behavioral features, and document validity directly in Python.

Unify identity data

Combine device, behavioral, onboarding, KYC, and third-party signals into a single, consistent feature set.

Debug high-stake decisions

Inspect every feature and execution path with Chalk’s query plan viewer.

Power real-time identity decisions

Eliminate latency and stale features. Power models with fresh signals like user actions, API responses at inference time.

Reduce risk without slowing growth

Use live identity context for better decisions while minimizing unnecessary step-ups and user drop-off.

Seamless compliance

Monitor outputs with full observability; built-in lineage, audit logs, and PII masking.

Behavioral abuse and account risk

Detect anomalous user behavior and activity velocity in real time.

Verisoul uses Chalk’s Python-native features and low-latency serving to update fraud detection logic 10× faster and stop attacks as they happen.

Account Takeover

Stop bots, fake accounts, and synthetic logins.

Customers use Chalk's feature platform to access real-time device and behavioral signals for blocking account abuse, served with single-digit millisecond latency.

Onboarding & KYC

Verify documents and identities with fresh, unified data.

Mission Lane cut feature deployment cycles from weeks to days by using Chalk to unify credit bureau and onboarding signals into consistent features.

Synthetic IDs & emerging fraud

Detect synthetic identities and adapt to emerging attack vectors

MoneyLion uses Chalk’s versioned features and backtesting to validate new fraud signals on historical data and ship updated logic to production in hours.

Real-time risk features in single-digit millisecond latency

from chalk import online

@online
def get_username(email: User.email) -> User.username:
    username = email.split("@")[0]
    if "gmail.com" in email:
        username = username.split("+")[0].replace(".", "")
    return username.lower()

@features
class Transaction:
    id: int
    amount: float
    user_id: "User.id"

Fetch device info, IP geolocation, velocity checks, and KYC scores at inference time. No batch lag, no stale features.

Fraud Detection Tutorial

Stopping faking accounts with fresh fraud features

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Verisoul uses Chalk to detect bots and coordinated fake accounts in real time. With Chalk they ship fraud features 10× faster, improve detection accuracy 4× with inference-time data, and maintain full auditability across their models.

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Additional resources

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7 Common MLOps Challenges (and How to Solve Them)

2026.01.05

customer story

Medely staffs critical healthcare in real-time with Chalk

2025.12.11

product

Quarterly Product Update: Fall

2025.11.10

event

Mission Lane demo: Scaling ML with thousands of features

2025.11.03

Build identity fraud systems powered by real-time data

Get started with Chalk today and build risk infrastructure that moves at the speed of your business.

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