FEATUREFLOW V2AI-native · MCP-enabled ·Only 5 spots left at 50% off:NEXT50claim →
Why Featureflow

Release governance without the enterprise contract

Every feature flag tool gives you flags. The differences that matter show up later — the first time you need to prove who turned something on, the first time a rollout skips a step because the person who knew about it was away, and the first time you read a pricing page and find that the controls keeping you safe live two tiers up.

The short version

Featureflow includes release pipelines, approval workflows, audit trails, role-based permissions and Google sign-in on every plan, including Free. These are the capabilities the rest of this market most commonly reserves for its top tier. Everything else on this page follows from taking that seriously.

The trade nobody should have to make

Look across feature flag pricing pages and a pattern repeats: flags, targeting and rollouts on the entry plan; approvals, audit trails and SSO further up. Read as a business decision that is perfectly rational — those are the features enterprise buyers will pay for. Read as a safety outcome it is backwards, because it prices release governance out of reach of exactly the teams with no platform team, no release manager and no second pair of eyes.

A team of eight is offered a choice between governance and budget, picks budget, and finds out what that cost during their first serious incident or their first enterprise security questionnaire. We do not offer that trade.

CapabilityFeatureflowCommonly elsewhere
Release pipelinesEvery plan, including FreeCommonly an enterprise-tier capability, where it exists at all
Approval workflowsEvery plan, enforced server-sideCommonly reserved for the top pricing tier
Audit trailEvery planOften gated, or retained only on higher tiers
Role-based write permissionsEvery plan, enforced server-sideFrequently a paid add-on
Google single sign-onEvery plan (SAML SSO on Enterprise)SSO is the classic enterprise-tier upsell
Reusable audiences & segmentsEvery planSegment counts often capped by tier
Scheduled & time-of-day targetingEvery plan, built into the SDKScheduling is frequently a premium add-on

Competitor tiering varies by vendor and changes over time — check the current pricing page of any tool you are comparing. The Featureflow column is what we commit to.

Where Featureflow is different

Governance is not a pricing tier

Release pipelines, approvals, the audit trail, role-based permissions and Google sign-in ship on every plan. A five-person team gets the same release controls as a large one, because the team with the least slack to absorb a bad release needs them most.

Approvals & audit

The rollout process is an object, not a document

Define your phases once — development, test, staging, production verification, go-live — and every feature advances through the same ones, each phase applying its own default targeting and its own approval gates. The process stops depending on who is driving it.

Release pipelines

Split evaluation: fast, private, and schedulable

Targeting evaluates on the server, so clients receive a CDN-cached, pre-evaluated result — your segment definitions and rollout plans never ship to the browser. Date and time-of-day conditions evaluate on the device, so scheduled releases and time-of-day targeting work on every plan without breaking the cache.

Remote config

Built for agent-assisted engineering

Featureflow publishes an MCP server on npm, so “roll new-checkout to 25% in production” is a sentence rather than a dashboard session. It runs through the same server-side permission model as the dashboard and the REST API — an assistant has exactly the access its token has.

MCP server on npm

Update mobile apps without a store release

Ship the binary once, then release features and update JSON configuration remotely — in apps your users already have installed. A kill switch reaches every version in the field, and a launch can go live across iOS, Android and web at the same moment.

Mobile releases

Support from the engineers who build it

Support questions go straight to the team that writes the product. A question about SDK behaviour or a targeting edge case is answered by someone who can read the implementation — not routed through a ticket tier.

Get in touch

Everything your release workflow uses, nothing it does not

Featureflow covers the full flag workflow your team touches every day: boolean and multivariate flags, targeting rules and reusable segments, percentage rollouts, environments, release pipelines, approvals, audit, per-variant statistics, a public REST API, and SDKs for Node.js, Java, Go, Python, Ruby, .NET, browser JavaScript, React and React Native.

For experimentation, Featureflow owns the half that has to be right — deterministic assignment, stable traffic splits and goal tracking — and feeds its events to the analytics platform your team already trusts. One system decides who sees what; your analytics stack measures what happened.

Where the work fits your stack

Flags reach further into a codebase than most tools, so the integrations are deliberately boring and useful: a Jira app that shows live flag status on the ticket, Slack notifications when a flag changes, personal access tokens for the REST API so CI can create and clean up flags, and an MCP server for the growing share of engineering work that happens through an assistant.

The problems teams bring us

Frequently asked questions

What actually makes Featureflow different?

One decision, applied consistently: the features that make feature flags safe to run - release pipelines, approval workflows, the audit trail, role-based permissions and Google sign-in - are part of the product on every plan, including Free. Across this market those are the capabilities most commonly reserved for the top pricing tier, which asks small teams to choose between release governance and their budget.

How does the client-side SDK differ from other tools?

Split evaluation. Targeting is evaluated on the server, so browsers and mobile apps receive a pre-evaluated result rather than your rule set - segment definitions, customer lists and rollout plans never reach the client. Date and time-of-day conditions are the deliberate exception: they evaluate on the device, which keeps every response identical and CDN-cacheable while still supporting scheduled releases and time-of-day targeting. Elsewhere, scheduled rollouts are often sold as a premium feature; here they are how the SDK works.

Can I run experiments with it?

Yes. Multivariate flags split traffic deterministically, every variant can carry a JSON payload, and a track() call records goal events per variant. For deep statistical analysis, Featureflow pairs cleanly with your analytics stack: it decides who is in which arm and emits the events; your analytics platform reads them.

Will upgrading break my integration?

Backwards compatibility is a commitment, not an accident. Older SDK versions continue to evaluate correctly against the current service, so long-lived server processes and mobile versions already in the field keep working without a forced upgrade cycle.

Who do I talk to when something goes wrong?

Engineers. Support questions go directly to the team that builds the product, so a question about SDK behaviour or a targeting edge case is answered by someone who can read the implementation - not routed through a tier-one script.

Can I manage flags from an AI assistant?

Yes. Featureflow publishes an MCP server on npm, so Claude or any MCP-capable assistant can create features, inspect targeting and change rollouts through the same permission model as everything else. Permissions are enforced server-side, so an assistant has exactly the access its token has.

See whether the difference holds up

Free forever tier with pipelines, approvals, audit and Google sign-in included, no credit card. Or read the LaunchDarkly comparison if you are switching.

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