Stigg vs Schematic: Which Is Better for AI Products?

A model request hits your API while the customer is close to a usage cap. That same account also has an enterprise override and credits shared across several agents. Which rule gets the final say before the model call runs?

That’s where the Stigg vs Schematic comparison gets interesting. Both can manage entitlements, usage, credits, and limits in production. Stigg puts more weight on the live usage path. Schematic wraps those controls into a broader billing and packaging system.

Stigg vs Schematic: What’s the difference?

Stigg is a usage runtime for AI products. It keeps entitlements, credits, usage limits, and spend controls close to the request that needs them.

Schematic combines usage-based billing with entitlements and runtime controls. Plans, features, credits, usage limits, invoices, and customer-facing billing tools can all live in the same platform. 

Choose Stigg if your hardest problem is deciding what a user or agent can consume before another model call, workflow, or job runs.

Choose Schematic if you want those checks tightly connected to billing, packaging, custom plans, and customer-facing usage controls.

They’re comparable, though they draw the product boundary differently. Stigg specializes more heavily in the runtime layer, while Schematic owns more of what sits around it.

Stigg: Features & highlights

Stigg is built for situations where pricing rules have started affecting live product behavior.

A request can check feature access, current usage, credit balance, and applicable limits before expensive work starts.

Five capabilities stand out:

• Entitlements for feature access, configuration values, metered allowances, and credits
• AI credits with expiry, cost basis, paid and promotional grants, burn priority, and ledger-backed history
• Usage metering across customers, users, agents, products, and custom units
• Stigg Sidecar for request-time checks with local caching, Edge fallback, and configurable timeout
• BYOC and BYODB for private infrastructure and high-volume workloads

What stood out most here is how much context Stigg can feed into one decision.

A plan, add-on, customer override, current usage level, and credit balance can all influence what the application allows next.

Credits get similar treatment. Each grant can carry its own expiration, cost basis, category, and priority, while transactions are written to a ledger.

That gives the hot path a local option without pretending every request magically has zero latency.

Schematic: Features & highlights

Schematic takes a broader approach. Entitlements and feature checks sit alongside pricing configuration, billing, credits, custom plans, customer usage views, and embedded components.

Again, there are five capabilities to pay attention to:

• Smart Flags combining feature access, usage, traits, and plan rules
• Plans and entitlements with versioning, overrides, add-ons, trials, and custom packages
• Usage metering and credits with burn rates, rollover, top-ups, and wallet visibility
• Usage controls including hard caps, warnings, and per-user or per-agent limits
• Billing and embedded UI for usage, wallets, invoices, and plan management

Schematic’s Smart Flags are the most interesting part for engineering.

They make feature checks feel familiar if your application already uses flag-style logic. A decision can incorporate plan state, customer traits, usage, and billing information before returning access.

Schematic also publishes sub-50ms flag evaluation, plus Redis support, local evaluation, offline behavior, and an Enterprise Replicator that keeps flag data inside your infrastructure.

That makes this a much closer runtime comparison than the category labels initially suggest.

Stigg vs Schematic: At a glance

Disclaimer: Prices are subject to change without notice. Always visit the official company websites for the most up-to-date pricing information.

The features overlap quite a bit. The bigger difference is how much of your billing and monetization stack you want one platform to handle.

Stigg vs Schematic: Feature-by-feature comparison

The feature lists only get you part of the way. I found it more useful to follow one entitlement from configuration to the point where a live request needs an answer.

1. Entitlements and feature gating

Schematic has a capable entitlement system, but Stigg gets the edge because its entitlement model covers more than feature access.

Stigg supports four broad entitlement types:

• Boolean access
• Configuration values
• Metered limits
• Credit-backed usage

That means the same entitlement layer can answer questions like:

“Can this customer use the premium model?”

“How many concurrent agents can they run?”

“How much of this allowance remains?”

“Which credits can fund the next request?”

Stigg can also resolve rules from plans, add-ons, customer overrides, and other active package state.

Versioning is another strong point. Plans can evolve while older customers remain on grandfathered configurations, with migration and lineage kept explicit.

Schematic, on the other hand, takes a more feature-centric path.

Features connect to plans and limits, then Smart Flags become the check used inside the application. Those checks can incorporate customer traits, usage, and billing state.

Schematic also handles custom plans, trials, overrides, and legacy packages. The difference is small, but useful.

Schematic gives you a strong entitlement-aware flag system, whereas Stigg gives you a broader entitlement model that also covers configuration, credits, and metered usage.

Winner: Stigg, narrowly.

2. Real-time enforcement and reliability

This is where the comparison gets close. Both products treat entitlement checks like production infrastructure. If a feature check sits in front of an AI request, latency and failure behavior become part of the application itself.

Schematic pre-calculates and caches flag state. Its Smart Flags page advertises evaluation below 50ms, with support for local evaluation, Redis, and offline operation.

Enterprise customers can also use its Replicator, which keeps flag data inside their own infrastructure.

That’s a meaningful design choice because the application can keep making decisions without depending on a fresh remote lookup every time.

Stigg solves the same problem through the Sidecar.

A normal cached request looks like:

Request → Sidecar → local state → decision

A miss becomes:

Request → Sidecar → Edge API → cache update → decision

Cache hits resolve immediately, and cache misses go to the Edge API in around 100ms, with a configurable timeout.

The other piece I’d pay attention to is failure behavior. Cached Redis state can remain available during upstream connectivity problems, giving the application a defined path when dependencies fail.

Stigg extends that model further with BYOC, where the runtime itself can operate inside your VPC.

Schematic is solid here. Its Replicator, which automatically replicates flag data into your infrastructure, is a strong point.

Winner: Stigg, mainly because local enforcement, usage state, credits, and private deployment are treated as parts of the same runtime architecture.

3. AI credits and usage controls

Both platforms can run a real credit system. The difference shows up once the balance needs rules attached to it.

Schematic supports:

• Credit grants
• Configurable burn rates
• Rollover
• Promotional credits
• Top-ups
• Customer wallets
• Warning thresholds
• Per-user and per-agent caps

That covers a lot of what an AI product needs when several users or agents share a common allowance.

Stigg goes deeper into how each block of credits behaves.

A grant can carry:

• Effective date
• Expiration
• Cost basis
• Paid or promotional category
• Consumption priority

The burn engine can decide which grants go first, while the ledger records each change to the balance.

Hard and soft depletion also connect directly to what the product does when credits run out.

That level of detail becomes useful once credits stop being a number in the UI and start controlling concurrent, expensive workloads across per-agent, per-team, per-user, and per-department enforcement.

Winner: Stigg.

4. Metering, pricing, and billing

This is where Schematic pulls ahead, since it covers much more of the path surrounding the entitlement check.

Its platform supports pricing patterns including:

• Credit-based usage
• Pay as you go
• Tiered overage
• Pay in advance
• Seat pricing
• Hybrid models
• Custom enterprise packages

It also covers invoices, payment terms, customer-specific plans, and embedded components for usage and wallets.

Schematic now describes itself as a usage-based billing platform with usage transparency and governance built in.

Stigg draws the boundary earlier. Its runtime can connect to billing providers while keeping entitlement and credit decisions separate from the payment layer.

Stigg also offers invoicing options, but the product still centers on what the application can access and consume while it runs. That separation can be useful if you already like your billing stack.

Schematic is more attractive if you want plans, entitlements, usage, invoicing, and customer billing experiences in a single platform.

Winner: Schematic.

5. Developer experience and deployment

Both products give engineers several integration paths, though the mental model is different.

Schematic exposes entitlement logic through Smart Flags.

That can feel natural if your code already thinks in terms of:

Feature → flag check → access decision

Its SDK coverage includes Node.js, Next.js, Go, Python, Java, JavaScript, React, and C#, along with OpenFeature support.

Local evaluation, Redis support, and the Enterprise Replicator give you more control over where those checks happen.

Stigg exposes SDKs, APIs, MCP, CLI, and the Sidecar. The Sidecar adds a language-neutral gRPC path, and it can run beside the application in the same Kubernetes environment.

The deployment options go further, too. BYOC, BYODB, and air-gapped deployment are available for workloads with stricter infrastructure requirements.

Schematic gives you local entitlement state, and Stigg lets you move more of the usage runtime itself into your environment.

Winner: Stigg for deployment flexibility.

Stigg vs Schematic pricing

The monthly starting prices are almost identical, which makes the pricing model around them more useful than the headline number.

Stigg pricing

Stigg currently lists:

• Build: Free
• Pro: $499/month or $399/month when billed annually
• Scale: Custom
• BYOC: Custom

Build includes 10,000 managed entities, 5 million monthly usage events, and access to the credits and entitlement engines. Pro increases the included event allowance and throughput.

Stigg pricing revolves around managed entities and usage events, while BYOC changes the infrastructure model by running usage processing inside the customer's environment.

Schematic pricing

Schematic currently lists:

• Starter: Free
• Growth: $400/month, or $3,840.00/year
• Enterprise: Custom

Starter includes the platform up to $5,000 in monthly billing volume and allows two custom plans.

Growth raises those caps to 15 custom plans and 20 company overrides, and adds a dedicated billing engineer in a private Slack channel, while Enterprise adds controls such as longer audit retention, RBAC, more environments, and SLAs. 

Schematic bases pricing more heavily on monthly billing volume.

Winner: Tie.

The one-dollar difference between Pro and Growth is meaningless compared with how differently the products meter usage and what you expect each one to own.

What their customers are doing with them

For this comparison, the useful customer evidence comes directly from each company's own case studies.

Stigg

One of Stigg's stronger AI examples is Miro.

Stigg says Miro moved from having no AI credits to a working hybrid model with enforcement, resets, and usage visibility in under six weeks.

Webflow is another useful example because the problem was less about credits and more about pricing logic living too close to engineering.

After moving to Stigg, add-on rollouts dropped from months to about four hours of product-team configuration, and Webflow shipped Localization Add-ons, Bandwidth Add-ons, Webflow Optimize, and Webflow Analyze on the same infrastructure.

Pricing changes now push to millions of customers with a single click, and routine packaging work no longer needs engineering in the loop.

Those examples reflect where Stigg is strongest: commercial rules that need to become reliable product behavior.

Schematic

Schematic highlights Plotly as one of its AI pricing examples.

According to Schematic, Plotly implemented the platform in three weeks and launched two AI products using credit-based pricing in half the time it had budgeted.

Plotly kept Stripe Billing underneath while Schematic handled more of the pricing, entitlement, and usage layer.

Schematic also documents Zep going live in production on day four while continuing to use Stripe for invoicing.

That shows Schematic can sit between product and billing too, even though its product now covers more of the billing lifecycle itself.

How to choose between Stigg or Schematic

The quickest test is to ask what needs to be known before your next expensive request runs.

If that answer involves several types of entitlement state, shared credits, limits, account hierarchy, and fallback behavior, Stigg has the stronger fit.

If you also want the same system to manage billing, plans, invoices, and customer usage experiences, Schematic becomes more attractive.

Stigg is better for

Stigg makes more sense when you need:

• Several entitlement types beyond feature access
• Detailed credit rules and ledger-backed balances
• Shared allowances across users, agents, products, and accounts
• Local request-time checks
• Defined fallback behavior
• High-volume metering
• BYOC or BYODB
• A runtime layer that stays independent from billing
• Adopting one component at a time (credits, entitlements, or metering) without committing to the full stack.

You also don't need to adopt everything at once.

Credits, entitlements, and metering can each be adopted independently, and an early integration can begin with one SDK before more of the runtime moves over.

That makes Stigg useful when one part of your current usage infrastructure has become painful while the rest still works fine.

Schematic is better for

Schematic fits better when you want more of the commercial stack in one system.

It’s particularly well suited to:

• Plans, trials, add-ons, and custom deals
• Feature flags tied directly to entitlements
• Usage-aware access checks
• Credits, top-ups, and rollover
• Embedded wallet and usage components
• Billing and invoice workflows
• Pricing changes controlled through configuration
• Local entitlement evaluation

If Stripe stays underneath and you want one layer to handle much of what sits between billing and product behavior, Schematic is a compelling setup.

Verdict

The Stigg vs Schematic decision becomes much easier once you follow a request through production.

If that request has to resolve feature access, credit state, usage limits, plan inheritance, overrides, and tenant-level rules before it runs, Stigg has the stronger architecture.

Its Sidecar is a big part of that. Cached decisions stay close to the application, while misses and upstream failures follow explicit paths. BYOC gives you another option when those checks need to stay inside your own infrastructure.

Schematic is strong in a different way. Its runtime controls are credible, and Smart Flags plus Replicator give engineers local evaluation and resilience.

Schematic wants to own more of that stack in one place. Stigg lets you adopt the credits engine, entitlements, or metering independently, so you can add the layer your billing was never designed to be without a rip-and-replace.

Choose Stigg for a dedicated usage runtime. Choose Schematic when you want entitlement enforcement bundled with more of the billing stack.

Look at what your hot path needs

A feature checklist won't tell you whether the architecture fits your application.

The better question is what information has to be available when the next AI request arrives, and what should happen if part of that infrastructure is unavailable.

The Stigg docs show how credits, entitlements, metering, and Sidecar checks fit into a dedicated usage runtime when those decisions have become part of production infrastructure.

FAQs

1. What is the main difference between Stigg and Schematic?

The main difference between Stigg and Schematic is scope.

Stigg specializes in the usage runtime, with entitlements, credits, limits, metering, and request-time enforcement. Schematic combines those controls with a broader billing, pricing, and customer-lifecycle layer.

2. Does Schematic support real-time entitlement enforcement?

Yes. Schematic supports runtime feature and entitlement checks, along with caching, local evaluation, Redis, and offline behavior. Its Smart Flags page advertises flag evaluation below 50ms, while Enterprise Replicator can keep flag state inside your infrastructure.

3. Which is better for AI credits, Stigg or Schematic?

Stigg has the stronger dedicated credit architecture when credits need detailed grant state, configurable consumption rules, ledger history, and direct connection to request-time entitlement decisions.

Schematic remains a good fit for credit-based pricing, rollover, top-ups, and shared usage controls.

4. Can Stigg and Schematic work with Stripe?

Yes. Stigg and Schematic can work with Stripe. Stigg sits above Stripe as the control plane. Stripe handles payments, Stigg decides what's allowed before the request runs. Schematic uses Stripe underneath and layers pricing, usage, and customer-facing billing on top

5. Which is cheaper, Stigg or Schematic?

Their published paid entry prices are almost identical. Stigg Pro starts at $499/month when billed monthly, while Schematic Growth starts at $400/month. Their pricing units and included usage differ enough that the monthly sticker price shouldn't drive the decision.