Sift alternatives
Five alternatives to Sift, compared on pricing and coverage. Including the case where the right answer is a vendor category we don't compete in.
The short version
Updated August 2026
- Teams outgrow Sift over the buying, not the ML: quote-only sales, a median contract of $150,000 a year per Vendr, 3 to 7% annual escalators, and overage fees 20 to 50% above base rates.
- Rupt is our own product and it's listed first, so read the entries with that in mind. Every claim below is sourced from public pricing pages and reviews.
- The list covers the whole spread: a full fraud engine, a digital footprint platform, developer risk APIs, a no-code trust and safety console, and a raw identification layer.
Why teams go looking.
Sift earned its position. Its focus on payment and transaction fraud is deep. The console gives fraud operations teams real case review tooling. Nothing on this page argues the ML is bad.
The complaints are about everything around it. Vendr's data puts the median at $150,000 a year with a floor around $29,600. Contracts commonly carry 3 to 7% annual escalation clauses, overage fees run 20 to 50% above base per-event rates, and implementation often adds $5,000 to $20,000 in professional services. On G2, reviewers report false positives that create manual review workload, and describe the integration as slow and configuration-heavy.
One structural gap matters more than any of that: Sift does not absorb chargeback liability, and neither does anything below. The guarantee model, where the vendor eats the fraud losses on approved orders, is a separate category (Signifyd and Riskified are its best-known names) that we haven't deep-reviewed here. The list below is for the other case: you need account defense, device intelligence, or fraud scoring, and a six-figure quote-based contract is the wrong shape for it.
The alternatives.
Pricing pulled from public pages, August 2026. Sift has no public pricing, so its numbers come from Vendr's recorded contract data, and we say so.
1. Rupt That's us
A full fraud engine built around your product. One evaluation returns the fingerprint, 60+ signals, scored risks, and an allow / challenge / block / add-to-list verdict. Rupt hosts the challenge if one is needed.
Focus:Product-level fraud and abuse: detection, rules, and enforcement in one engine.
Pricing:$99/month with 20,000 evaluations included, then $0.005 each, and the price goes down with volume. Challenges $0.10 only when delivered.
Strengths
- +Rules engine and challenge engine included in the base plan.
- +AI agent monitors new patterns and investigates cases marked for manual review.
- +People detection estimates how many humans share an account rather than how many browsers appear on it.
- +Cross-browser device linking, plus email, IP, and phone intelligence in the same call.
- +Unified user view for AI agents and humans to make informed decisions.
Keep in mind
- -No Flutter SDK today.
- -Fast-paced startup; the product evolves quickly.
2. SEON
A payment fraud platform: digital footprint enrichment on emails and phones, ML scoring trained on historical transactions, and AML screening. Transactions run through the whole product.
Focus:Payment fraud and identity context from digital footprints.
Pricing:Starter at $699/month for 2,500 API calls, about $0.28 each. Premium is quote-based.
Strengths
- +Strong focus and data around risky transaction/payment activity.
- +AML screening in the same platform.
Keep in mind
- -Transaction-shaped API with fixed verdicts; the ML improves through a separate Label API you wire up.
- -Its docs put the lowest supported lookup timeout at 1.5 seconds.
- -Non-payment abuse means molding your events into a transaction shape, then building enforcement yourself.
3. Castle
Developer risk APIs for account fraud on authenticated apps: device, email, and IP intelligence with policy rules and public unit pricing.
Focus:Risk scores and policy verdicts for login and signup abuse on authenticated apps.
Pricing:Free tier with a $5 monthly credit, Pro at $200/month including 40,000 risk requests ($0.005 each after), Enterprise from $4,000/month. Vendr pegs the median enterprise contract at $119,500/year.
Strengths
- +Rules, lists, and a mature decisioning layer.
- +Good rules engine and data organization.
Keep in mind
- -No challenge engine included so that still needs to be built by you.
- -Setup and integration support is Enterprise-only, per its own pricing FAQ.
- -Developer experience is good, but can be difficult to customize if flexibility is important to you.
4. Verisoul
All-in-one fake account and fraud detection with a no-code decision layer, plus step-up verification like face match and ID checks as paid add-ons.
Focus:Dashboard-first fake account detection with a no-code decision layer.
Pricing:Starter $99/month (dashboard only, no API), Professional around $189 to $199/month for 5,000 MAUs at $0.02 per MAU. Face match and ID checks billed per use.
Strengths
- +No-code rules a non-engineer can actually operate.
- +Built-in face match and ID verification.
Keep in mind
- -No challenge engine included, so you have to build that yourself.
- -Small surface area when it comes to fraud/abuse cases. Most of the focus is on fake accounts.
- -Not easy to modify/customize to your specific workflows.
5. Fingerprint
The identification layer: a visitor ID with a claimed 99.5% accuracy plus 20+ Smart Signals. You bring the decisioning, the rules, and the interventions.
Focus:Visitor identification and raw device signals; the decisioning layer stays in-house.
Pricing:$99/month for 20,000 API calls, then $4 per 1,000 additional. Free tier of 1,000 calls per month.
Strengths
- +Identification accuracy and SDK breadth lead the category, with 11 client platforms.
- +Excellent docs and developer experience.
- +Cheap way to add device signals to a decisioning stack you already run.
Keep in mind
- -Signals only: rules, case review, challenges, and email checks are all yours to build.
- -Not a Sift replacement by itself; it is the main ingredient of one.
- -G2 reviewers call it pricey for smaller companies once volume grows.
Rupt vs Sift, quickly.
The short version. The full comparison covers signals, migration, and where Sift wins.
Frequently asked questions.
Why choose Rupt.
Account-centric by design
Every device, IP, and action rolls up to the user behind it. You investigate accounts, not anonymous requests, and the full history is already assembled when you get there.
Continuous monitoring
Every signup, login, and sensitive action is evaluated, so an account's risk is tracked across its lifetime and new patterns surface as they form, not after the damage.
Automated challenges
Risky actions trigger hosted email or SMS challenges automatically. Legitimate users clear them in seconds, attackers don't, and nobody on your team had to send anything.
A force multiplier for risk teams
Detection, decisioning, and enforcement run continuously without headcount. A team of one gets real coverage, and an established team spends its hours on judgment calls instead of triage.
AI-driven investigations
The AI agent digs into flagged accounts and watches for emerging abuse patterns around the clock, so your team reviews conclusions instead of assembling evidence.
Coverage across the whole journey
Evaluations are priced to run everywhere, from signup to checkout to content access, so you see the account's behavior end to end instead of a snapshot at the login gate.
Support that isn't gated behind Enterprise
Integration setup help, developer meetings, and direct Slack and email access with replies in hours come with every plan. Most vendors reserve that level of support for their top tier; with Rupt it's just how support works.
Single-vendor pricing
Fingerprinting, email and phone intelligence, rules, and challenges usually mean a vendor and an invoice each. Because Rupt ships them together, the bundle costs less than the sum of the point tools.
See Rupt on your traffic.
Book a demo and we'll walk through your use case, show you the signals on real evaluations, and price out your volume.
- A walkthrough tailored to your use case.
- How detection, the rules engine, and challenges fit your stack.
- Pricing and a rollout plan for your volume.