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Actualyze and Cloudflare AI Gateway

Actualyze. Keep Cloudflare AI Gateway, and give every AI dollar an owner from day one.

Cloudflare AI Gateway is an AI gateway that also sells inference, and Actualyze is the enterprise AI gateway and AI governance platform that can keep Cloudflare as one source. Actualyze adds a month finance can close and personal data masked from the first request.

Competitor facts checked against Cloudflare AI Gateway's documentation on .

In short

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each gateway's governance

Actualyze

Your organization

policy from Team Owners and Budget Managers

Inference

  • public APIs
  • brokers
  • GPU clouds
  • Cloudflare AI Gateway
  • your own servers

Cloudflare AI Gateway

Traffic through the gateway

policy from gateway settings

Inference

  • Unified Billing models
  • your provider keys
  • custom HTTPS endpoints

Side by side

Cloudflare AI Gateway is Cloudflare's hosted AI gateway, sitting between applications and model providers. Calls run on your own provider keys or, through Cloudflare's Unified Billing, on Cloudflare-managed credentials paid for with prepaid Cloudflare credits.

Actualyze and Cloudflare AI Gateway, side by side
ActualyzeCloudflare AI Gateway
Pricing and routing
Where cost figures come from

Priced per model and provider. Unknown cost is never $0

Cloudflare accepts custom rates on each request

Rates sent in a request header override the default or public model costs.

One model, many providers

One model through any provider the caller can use

Cloudflare's dynamic routes call models with fallbacks

Each model node names a provider and a model.

Routing across models

Sizes each request, picks the cheapest model strong enough

A Virtual Model, one name over several models, picks only among models the caller can already use.

Auto Router weighs task difficulty, quality, and cost

Cloudflare ranks eligible models and tries the next one if a provider cannot serve the request.

Provider prompt caches

Stays on the cached model unless moving saves money

Auto Router weighs cache loss before changing models

Auto Router keeps one model per turn when the request carries a session ID.

Access and spend
Who approves access and spend

Each model names its own approver. Budget Managers own spend

AI Gateway Write covers authentication and spend limits

The gateway update API accepts both settings under that one permission.

Budgets and limits

Budgets nest. A call past the limit is rejected

Spend limit rules cover Unified Billing and BYOK

Rules scope by model, provider, or metadata, for models with known pricing.

Chargeback and the month

Finance closes the month on one statement

User Insights reports spend by attributed identity

Requests without an identity or custom metadata share one anonymous identifier.

Protection
On from the first request

Personal data masked from the first request

The default guardrail masks personal data in prompts and responses, and nobody can delete it.

DLP flags or blocks once it is enabled on a gateway

A policy picks profiles and scans requests, responses, or both.

Weakening protection

Protection can't be quietly switched off

AI Gateway Write holders edit or disable DLP policies

Records and reach
Audit record

Each routed call records which model answered and why

The record can't be edited, and it names the model the app asked for.

Audit logs record gateway creation, updates, and deletion

What the controls reach

Any LLM, anywhere, behind an OpenAI- or Anthropic-style API

Your own servers too, through a relay you run that only connects outward.

Custom providers add any HTTPS API endpoint

Bringing a model online

Each model goes live only after its own approval

A custom provider takes requests once it is enabled

A new custom provider is inactive until its enable setting is turned on.

Deployment
Deployment

Hosted today. On-prem deployment coming in 2027

Hosted by Cloudflare, called through its HTTP API

Spend

Actualyze. Finance closes the month on AI spend.

Actualyze

October statement

  1. draft
  2. reviewed
  3. settled
budgetcost centeramount
SupportCC-4410$3,120
SearchCC-4412$8,940
AssistantsCC-4415$1,380

total$13,440

Finance closes the month on one Actualyze statement.

Cloudflare AI Gateway

Cost by team metadata

Query with GraphQL
  • Support$3,120
  • Search$8,940
  • Assistants$1,380

cost per model, provider, or metadata value

Cloudflare charts spend by model, provider, or metadata.

Actualyze binds every call to a team and a budget before it runs.

An Actualyze API key names one team and one budget when it is created, and no request can change them. Each budget has a Budget Manager, the person who decides who may charge it, and team budgets nest inside their department's budget. When the month ends, finance settles a single statement that lists every budget beside its cost-center code.

Cloudflare AI Gateway sets spend limits by model, provider, or request metadata.

A Cloudflare rule can split its budget by a metadata value, such as a team or user ID the application attaches to each request. Behind Cloudflare Access, the verified user ID is added automatically. Cloudflare's dashboard reports that spend over a chosen time range.

Protection

Actualyze. Personal data is masked from the first request.

Actualyze

  1. workspace createdthe default guardrail is already on

first request

Reply to [REDACTED:EMAIL_ADDRESSES]

Actualyze masks the email from the first request.

Cloudflare AI Gateway

  1. DLP switched on for the gatewayin the gateway's Firewall tab
  2. a DLP policy savedits profiles, Flag or Block, and what to scan

each request after that

flagged or blocked when a profile matches

Cloudflare flags or blocks a match once DLP is set up.

Actualyze masks personal data from the moment a workspace exists, with nothing to set up.

An Actualyze workspace's default guardrail is enforcing before anyone writes a policy, on prompts and on responses. A customer's email in the first prompt reaches the provider as a placeholder, and the answer still comes back. No one can remove that guardrail, and pausing it takes a written justification and alerts every Workspace Admin.

Cloudflare AI Gateway DLP flags or blocks sensitive data once it is enabled on a gateway.

A Cloudflare DLP policy selects detection profiles, an action of Flag or Block, and whether to scan requests, responses, or both. Policies are set on each gateway, while the profiles they use are shared across the Cloudflare account.

Approvals

Actualyze. The leading delegation and approval system for AI spend.

With Actualyze, model access and spending have separate owners, the separation of duties auditors ask for.

Each model names its own approver, usually a lead of the asking team (its Team Owner), and an approval covers that one model. Spending goes through Budget Managers, who decide who may charge each budget. Neither authority can override the other, so a request for a model and a request for money land with different people.

Cloudflare AI Gateway puts a gateway's authentication setting and its spend limits under one permission, AI Gateway Write.

A gateway's DLP policies sit under the same permission. Cloudflare Access policies, set up through Cloudflare Access, decide which authenticated users can call the gateway.

Pricing

Actualyze. Priced at what you really pay, down to the call.

Actualyze prices every call at the rate your company confirmed, with no header to send.

A route is one model through one provider, and each route carries its own price. Confirm your negotiated rate for a route once, and every call through it is booked at that rate, whichever app sends it. Until then the list price applies. An unknown cost is never $0, so finance sees the exposure rather than a gap.

Cloudflare AI Gateway takes negotiated rates in a header on each request.

A Cloudflare custom-cost header sets the input and output rates that override the default or public model costs for that request. Cloudflare calls its cost tracking a best-effort estimate and points to each provider's dashboard for exact billing.

Evaluate

Six questions every AI gateway should answer live

If your AI gateway can't tell you who approved a model or what last month cost each team, it's just moving traffic. Put these questions to every vendor on your list, and ask to see each answer working in the product. Actualyze answers every one today, and each comes with a check you can run in your own trial.

  1. Who approves a team's access to each model?

    The leading delegation and approval system for AI spend starts here. In Actualyze, each model names its own approver.

    Request a model that needs approval as a team member, and check who receives the request and where the decision is recorded.

  2. What decides which model answers each request?

    In Actualyze, a routing model we train sizes each request and picks the cheapest model strong enough, the best model routing in the field.

    Send an easy question and a hard one to one Virtual Model, then see which model each was routed to, and why.

  3. What happens to a call when its budget runs out?

    Actualyze rejects it before any model is contacted, so a budget is a real limit and never a surprise on the bill.

    Set a small test budget and confirm the next request is rejected once it reaches its limit.

  4. Does an unknown cost ever show up as $0?

    An unknown cost is never $0 in Actualyze, which marks it unpriced and flags it for FinOps, so no spend hides behind a zero.

    Connect a third-party endpoint with no catalog price, call it, and check the call reads unpriced, not $0.

  5. What is protected before anyone writes a policy?

    Personal data is masked from the first request in Actualyze, in prompts and responses, by a default guardrail nobody can delete.

    Open a new workspace's guardrails before writing any policy, and confirm the default guardrail is already enforcing.

  6. Can finance close the month on AI spend?

    Finance closes the month on AI spend with one Actualyze statement, a row for each budget, reviewed and then settled.

    Generate a statement for a month with traffic, then move it from draft to reviewed to settled.

Common questions

Can we keep Cloudflare AI Gateway behind Actualyze?
Yes, and the inference you buy through Cloudflare keeps flowing under your organization's rules. Cloudflare AI Gateway offers an OpenAI-compatible endpoint, and Actualyze connects OpenAI-compatible endpoints as sources, so Cloudflare becomes one source beside your direct providers. Your apps call Actualyze, and every call is charged to a budget, checked by your guardrails, and written to the audit trail.
What is the difference between Actualyze and Cloudflare AI Gateway?
The difference between Actualyze and Cloudflare AI Gateway is who sets the rules. Actualyze sends each access request to that model's own approver, most often a Team Owner, and each budget's Budget Manager controls who spends from it. Cloudflare AI Gateway's rules live in each gateway's settings, beside the Cloudflare Access policies that decide who can call it.
Can Actualyze route between Cloudflare AI Gateway and our direct providers?
Yes, and the best model routing in the field works across Cloudflare and every other source you connect. An Actualyze Virtual Model, one name your apps call, can hold models from Cloudflare, your direct providers, and the servers in your network, and a routing model Actualyze trains hands each request to the least expensive model that can do the job.

Sources

22 pages, checked

Cloudflare, Cloudflare AI Gateway, and other product names mentioned here are trademarks of their respective owners. Actualyze is not affiliated with or endorsed by them.

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Give every model an approver and every call a budget.

Connect the providers you already use and test every claim on this page against your own traffic. Or book a demo. We'll walk you through it, and send the Virtual Model engine whitepaper if routing is on your list.

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