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Jellyfish Engineering Analytics

Optimize engineering productivity and decision-making with data-driven insights.

Venture Funded$35MSeries BAmplify PartnersSusa VenturesPear VC

engineering productivitysoftware development analyticscode review optimizationresource management

About

Jellyfish Engineering Analytics provides enterprises with comprehensive visibility into engineering workflows, enabling data-driven decisions to improve productivity and resource allocation at scale. The platform supports compliance with industry standards and integrates seamlessly into existing development ecosystems to enhance code review and delivery processes.

This description came from a bulk import and has not yet been checked against the vendor's own page. Treat it as unverified.

Enterprise Readiness

from cataloged data

Not scored. Nobody has checked this entry against Jellyfish Engineering Analytics’s own site yet, so the signals below are unverified and we will not turn them into a rating. The breakdown shows what our record holds.

Security & ComplianceNot disclosed

No compliance certifications listed

Deployment FlexibilityStrong

Flexible deployment: Cloud, Hybrid

Integration DepthStrong

8 documented integrations

Proven AdoptionPartial

6 documented use cases

Company MaturityStrong

Founded 2017 · Series B

Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.

Independently sourced

Pulled directly from regulator filings and platform APIs. No vendor or editorial input.

Activity classifier

Active

last GitHub commit 0d ago

GitHub API2026-05-27

jellyfish-ai

SDK / client libraries· 17★· active 3mo ago

Python · JavaScript · PowerShell · TypeScript

steady · +0★ (+0%) 30d

PyPI registry

jf-agent

v0.0.22· released 7.1y ago

Status page2025-10-20

Operational

operational· via statuspage· 0 incidents (90d)

OSV vulnerability feed2026-08-24

No known advisories

Enterprise Use Cases

Engineering productivity measurement

Code review process optimization

Resource allocation and capacity planning

Cross-team collaboration analytics

Release cycle acceleration

Technical debt management

Integrations

GitHubGitLabJiraSlackAzure DevOpsBitbucketLinearCircleCI

How Jellyfish Engineering Analytics compares

Tool	Readiness	Pricing	Deployment	Compliance	Integrations
Jellyfish Engineering Analytics	Not scored	Enterprise	Cloud, Hybrid	—	8
Checkmarx	Not scored	Enterprise	Cloud, On-Premise, Hybrid, Self-Hosted	—	8
Snyk	Not scored	Freemium	Cloud, On-Premise, Hybrid	—	8
Snyk Code	70 · Strong	Freemium	Cloud, On-Premise, Hybrid	—	8

Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.

Frequently Asked Questions

What is Jellyfish Engineering Analytics used for?

Jellyfish Engineering Analytics is optimize engineering productivity and decision-making with data-driven insights. It is commonly used for engineering productivity measurement, code review process optimization, resource allocation and capacity planning, and cross-team collaboration analytics.

Is Jellyfish Engineering Analytics free, and how is it priced?

Jellyfish Engineering Analytics uses enterprise pricing, typically a custom quote based on seats, usage, and requirements. Contact the vendor for a quote.

How can Jellyfish Engineering Analytics be deployed?

Jellyfish Engineering Analytics supports Cloud and Hybrid deployment. It is delivered as a cloud-hosted service.

What does Jellyfish Engineering Analytics integrate with?

Jellyfish Engineering Analytics documents 8 integrations, including GitHub, GitLab, Jira, Slack, Azure DevOps, and Bitbucket.

When was Jellyfish Engineering Analytics founded?

Jellyfish Engineering Analytics was founded in 2017 and has raised $35M in funding.

Is Jellyfish Engineering Analytics enterprise-ready?

Based on cataloged data, Jellyfish Engineering Analytics has an Enterprise Readiness score of 60/100 (Established tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.

Quick Facts

PricingEnterprise

DeploymentCloud, Hybrid

Founded2017

Funding$35M

CategoryCode & Development

Procurement

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