Why Countly

Six reasons teams
move their analytics home

Analytics, engagement and AI are infrastructure decisions, not just tools. These are the reasons product, data and security teams choose Countly over a shared SaaS, in the order they usually come up.

01 · Ownership

Your data, in an
environment that’s yours

Countly runs in a dedicated environment: our private cloud in the region you choose, or your own infrastructure. Nothing is used to train someone else’s models, and on Enterprise, Countly has no access without your explicit permission.

Dedicated single-tenant environments only
EU, US, APAC on Flex; anywhere on Enterprise
No default vendor access on self-hosted deployments

03 · One system

Insight and action
in the same place

Most stacks glue an analytics SaaS to a messaging tool to an experimentation platform, each with its own copy of the data. Countly is one system: the cohort you build in Drill is the audience of the push you send and the segment of the experiment you run. Replace six tools with one connected platform.

Push, in-app, Journeys, A/B tests, surveys built in
No exports between insight and action
One set of permissions, one data model

04 · AI inside

AI that can run inside
your deployment

Cee, Countly’s AI analyst, answers questions, builds cohorts and drafts actions on your data. On Enterprise, its product agents can run fully inside your infrastructure when configured. Connect your own AI to Countly through MCP.

Plain-language questions, transparent queries
Drafts actions for human approval
Bring your own model endpoint on Enterprise

05 · Compliance

Privacy by architecture,
not by policy

Masking and hashing happen before storage, consent is enforced in the SDK, data subject requests are one screen. SOC 2 Type II examined, ISO 27001, 27017 and 27018 certified, TISAX® participant; GDPR, HIPAA, COPPA and PDPL requirements supported by how the system is built.

Masking and consent at ingestion
Export or purge a user in one click
Security reviews, made faster

06 · Proven

Trusted where data control
is non-negotiable

Banks, healthcare providers, automotive groups, telcos and public institutions run Countly because the answer to “where is our data?” is always the same. Exactly where you put it. 17,000+ apps in 126 countries, from regulated enterprises to fast-moving startups.

Regulated industries since 2013
Open-source roots, bootstrapped and independent
Migration path from any SaaS analytics

01Ownership
02Real time
03One system
04AI inside
05Compliance
06Proven

Unique challenges

Ready for the cases
a shared SaaS cannot serve

Internal applications

Employee tools, back-office systems and intranets analyzed inside the network, with no third-party script and data that stays inside your network.

Offline device analytics

SDKs queue events on devices that are offline for days or weeks: vehicles, kiosks, medical devices, field equipment. Data arrives when the device does.

Cross-device journeys

One profile across mobile, web, desktop and embedded, merged when the user identifies. The journey is read as one path, not four reports.

Custom dashboards

Every team builds its own view on the same live data: product, marketing, support, leadership. Scheduled by email, shared per app.

Highly regulated environments

Banks, healthcare and public sector run Countly because residency, masking, consent and audit are properties of the architecture.

Self-hosted deployment

Your cloud, your data center or an air-gapped network. Updates ship as packages you install. No default vendor access.

“At Countly, we believe data creates meaningful connections. Our platform empowers businesses to own analytics, protect privacy, and turn insights into action.”
Onur Alp SonerCEO and founder, Countly

Compared

Countly against
the usual stack

AspectTypical SaaS stackCountly

Where data livesVendor’s multi-tenant cloudYour region or your infrastructure

LatencyVaries by tool; syncs between tools add delayFresh data, no overnight jobs

Data detailSampling and limits depend on plan and volumeRaw events by default; sampling is your choice

EngagementSeparate tool, exported audiencesBuilt in, same cohorts

AIVendor AI on vendor copy of your dataCee can run inside your deployment; connect your own AI through MCP

ComplianceVendor-hosted controlsControls in your architecture: masking, consent, residency

PricingPer event or per MTU, grows with volumeFlex per MAU, Enterprise per deployment

Six reasons teams
move their analytics home

Your data, in an
environment that’s yours

Queryable the
moment it arrives

Insight and action
in the same place

AI that can run inside
your deployment

Privacy by architecture,
not by policy

Trusted where data control
is non-negotiable

Ready for the cases
a shared SaaS cannot serve

Internal applications

Offline device analytics

Cross-device journeys

Custom dashboards

Highly regulated environments

Self-hosted deployment

Countly against
the usual stack

Own the intelligence
behind your product.

Six reasons teamsmove their analytics home

Your data, in anenvironment that’s yours

Ready for the casesa shared SaaS cannot serve

Internal applications

Offline device analytics

Cross-device journeys

Custom dashboards

Highly regulated environments

Self-hosted deployment

Countly againstthe usual stack

Own the intelligencebehind your product.

Six reasons teams
move their analytics home

Your data, in an
environment that’s yours

Ready for the cases
a shared SaaS cannot serve

Countly against
the usual stack

Own the intelligence
behind your product.