Hypertune

Type-safe feature flags, A/B testing, analytics and app configuration, with Git-style version control and local, synchronous, in-memory flag evaluation

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Hypertune is the most flexible platform for feature flags, A/B testing, analytics and app configuration. Built with full end-to-end type-safety, Git-style version control and local, synchronous, in-memory flag evaluation.

Pricing of Hypertune

Free

0.00

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Key Features of Hypertune

Key Features:

AB Testing
Audience Targeting
Campaign Segmentation
Funnel Analysis
Multivariate Testing
Reporting/Analytics
Third Party Integrations
Drag & Drop
Behavior Tracking
Split Testing
Statistical Analysis
Version Control
Testing Management
Software Development
Graphical User Interface
Mobile Development
Debugging
Collaboration
Access Control
Visitor Segementation
A/B Testing
Content Management
Project Templates
Data Analysis
Dashboard
Ad hoc Reports
Ad hoc Query
Ad hoc Analysis

Key Specification

Other Categories:	AB Testing Software Machine Learning Software Application Development Software
Deployment:	Cloud Hosted,Hybrid,On Premise,Any
Customer Support:	Phone,Email,Live Chat
Customization:	Yes
Languages Support:	English

Who uses Hypertune

Personal

StartUps

SMEs

Agencies

Enterprises

Company Details

Company Name:	Hypertune
Headquarter:	london, London United Kingdom
Social Media:	Twitter LinkedIn

Hypertune Description

Hypertune is the most flexible platform for feature flags, A/B testing, analytics and app configuration.

- Static typing and code generation gives you full end-to-end type-safety across all your feature flags and inputs.
- Install 1 TypeScript SDK optimized for all JavaScript environments — browsers, servers, serverless, edge and mobile — with simple integrations for React and Next.js, compatible with Server Components and the App Router.
- Define type-safe, custom inputs like the current User, Organization, etc, and use them in feature flag rules to target exactly the users you want.
- Create variables like user segments that you can reuse across different feature flags, and instantly debug flags for each user.
- Git-style version history, diffs, branching and pull requests let you manage feature flags like you manage your code. Test and preview flag changes in isolated branches and safely approve them with pull requests. Avoid bad changes and see exactly what changed and when.
- A/B tests, percentage-based rollouts, multivariate tests and machine learning loops let you seamlessly rollout, test and optimize new features.
- Log analytics events with type-safe, custom payloads, and build flexible funnels and charts in the dashboard to measure the impact of every feature release.
- Local, synchronous, in-memory flag evaluation with zero network latency lets you safely access flags in any code path without affecting the end user experience.
- Static build-time snapshots of your feature flag logic let you use the SDK in local-only, offline mode and give you safe fallbacks in remote mode.
- Initialize the SDK with only the feature flags you need and partially evaluate flag logic on the edge for performance and security.

Hypertune scales beyond feature flags to powerful app configuration to let you manage:

- Permissions and access controls for features based on billing plan, organization, user, etc
- In-app copy for tooltips, modals, banners, error messages, etc
- Landing page content with embedded A/B tests, machine learning loops and personalization rules
- Allowlists, blocklists, redirect maps, timeouts, limits, magic numbers and more

Across all app configuration use cases, Hypertune lets your team:

- Update your app instantly — without needing a code change, build, deployment, app release or service restart, whether it’s rolling back a feature, changing permissions or tweaking in-app copy
- Decouple dependencies in your organization — so developers can focus on shipping to production and others are safely empowered to make changes themselves without the painful back and forth with engineering
- Optimize your app — via manual tuning, A/B testing, machine learning loops and personalization rules
- Reduce complexity — by extracting all configura