Jellyfish
Jellyfish is a Boston-based software engineering intelligence platform founded in 2017 that normalizes fragmented SDLC signals via a patented data model, serving 500+ enterprise and mid-market engineering organizations with AI Impact, DevEx, Business Alignment, DevFinOps, and Operational Effectiveness modules.
- Company typePrivate
- Founded2017
- HeadquartersBoston, United States
- Headcount101–250
- GTM typeB2B
- OfferingSoftware
What Jellyfish does
Jellyfish is a Boston-based software engineering intelligence (SEI) platform founded in 2017 that ingests fragmented signals from across the software development lifecycle — issue tracking (Jira, Linear, Azure Boards), source code management (GitHub, GitLab, Bitbucket), CI/CD pipelines, HRIS, and financial systems — and normalizes them through a patented unified data model without requiring manual tagging, migrations, or process changes. The platform is delivered as a core data layer plus five modular add-ons (AI Impact, Operational Effectiveness, Business Alignment, DevEx, and DevFinOps), overlaid with AI-powered interfaces including the Jellyfish Assistant and Data Hub that enable natural-language queries and proactive insight surfacing. Patented IP includes a Unified Data Model for SDLC normalization and a Work Allocations Model that classifies engineering effort in FTEs regardless of source data hygiene.
The company serves enterprise and mid-market engineering organizations — disclosed customer logos include Box, Priceline, Blue Yonder, DraftKings, GoodRx, Acquia, Optimizely, CHG Healthcare, Clari, Jobvite, Siigo, Loadsmart, and TaskRabbit — targeting engineering executives, engineering managers, platform engineering teams, product leaders, finance teams, and indirectly individual software developers. Jellyfish reports covering 500+ companies and roughly 100,000 engineers worldwide, with its April 2026 AI Engineering Trends research drawing on data from over 1,000 companies, 200,000 engineers, and 20M+ pull requests.
Jellyfish operates a sales-led enterprise go-to-market with a quote-based, per-seat subscription priced across three primary module tiers (AI Impact, Developer Productivity, DevFinOps), complemented by a product-led 'Tour the Product' self-serve experience and direct inside-sales for mid-market accounts. Distribution is direct-only, with no channel/reseller program and no marketplace listing. Revenue is composed of recurring SaaS subscriptions, multi-year enterprise contracts, and ancillary professional services. As of late 2024 the company reported $31.9M in ARR and has cumulatively raised $114.5M, including a $71M Series C in February 2022 led by Accel, Insight Partners, and Tiger Global Management.
Jellyfish firmographics
Firmographics- Name
- Jellyfish
- Legal name
- Jellyfish
- Website
- https://jellyfish.co
- Company type
- Private
- Founded year
- 2017
- Operating status
- Operating
- Headcount range
- 101–250 employees
- Short description
- Jellyfish is a Boston-based software engineering intelligence platform founded in 2017 that normalizes fragmented SDLC signals via a patented data model, serving 500+ enterprise and mid-market engineering organizations with AI Impact, DevEx, Business Alignment, DevFinOps, and Operational Effectiveness modules.
- Ownership category
- akta.pro rank
Where Jellyfish is headquartered
LocationHeadquarters
- HQ city
- Boston
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Jellyfish business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Infrastructure, Operations
Revenue model
- Module-based SaaS subscriptions: Recurring SaaS revenue sold on a per-seat basis across three product modules (AI Impact, Developer Productivity, DevFinOps); pricing is quote-based and tailored to the seat count and modules selected. Module-based packaging enables land-and-expand as customers adopt additional capabilities.
- Enterprise contracts (multi-year): Enterprise sales motion with 'Request a Quote' / 'Talk to Sales' suggests multi-year enterprise contracts typical of large-account software sales.
- Professional services / enablement: Hands-on enablement, rollout support, and ongoing guidance implied by 'Guidance That Scales' differentiator and customer success-led adoption model.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Per seat | Annual | AI Impact module |
| Per seat | Annual | Developer Productivity module |
| Per seat | Annual | DevFinOps (R&D and finance) module |
Go-to-market motion3 records
Distribution channels3 records
Marketing channels9 records
Jellyfish product offering
Product offeringCore offering
Jellyfish is a Software Engineering Intelligence platform that ingests, cleans, normalizes, and links fragmented signals from issue tracking, SCM, CI/CD, HRIS, financial tools, and AI coding assistants into a single engineering data model. It sells this as a suite of modules — AI Impact, Operational Effectiveness, Business Alignment, DevEx, DevFinOps — that quantify engineering productivity, AI tool ROI, resource allocation, developer experience, and software capitalization for engineering, product, and finance leaders.
Product overview
Jellyfish offers a unified engineering intelligence platform with a core platform plus a portfolio of add-on modules and AI features rather than a single monolithic product. The core Jellyfish Platform ingests data from the software development lifecycle (issues, code, CI/CD, AI tools) and powers a set of named modules: AI Impact (with sub-modules Drive Adoption, AI Token Cost Management, Impact Insights, Workflow Optimization, Enable Teams, Vendor Comparison, and Report Builder for measuring AI coding tool adoption and ROI); Operational Effectiveness (with Engineering Metrics, Life Cycle Explorer, Team Workflow Analysis, People Management, and the standalone Engineering Benchmarks offering); Business Alignment (with Resource Allocations); DevEx; and DevFinOps (with Software Capitalization). On top of these modules, Jellyfish Assistant and Data Hub add AI-powered natural-language exploration and data-platform capabilities that span the modules. The modules share the same underlying data model and integrations, so engineering, product, and finance leaders see a single source of engineering truth.
Differentiator
Problem solved
Functional benefit
Products and services
- Jellyfish Platform Core engineering intelligence platform that ingests data from the software development lifecycle (issues, code, CI/CD, AI tools) and serves it to engineering, product, and finance leaders via dashboards, reports, and AI-powered interfaces.
- AI Impact Module that measures AI coding tool adoption and impact across AI coding assistants, including sub-capabilities for driving adoption, managing AI token cost, surfacing impact insights, optimizing workflows, enabling teams, comparing vendors, and building reports.
- Operational Effectiveness Module that provides operational metrics and analytics for engineering and product operations, including engineering metrics, lifecycle explorer, workflow analysis, people management, and team benchmarks.
- Business Alignment Module that connects engineering work to business outcomes by linking engineering investments and allocations to strategic priorities and product bets, using a patented multi-source data model.
- DevEx Module focused on developer experience, combining validated developer experience surveys with DORA, SPACE, and system metrics to produce a comparable DevEx Index and AI-driven recommendations.
- DevFinOps Module that brings finance and engineering together on the same platform, enabling software capitalization, R&D tax credit reporting, cost tracking, and FinOps-style management of engineering investment; SOC 1 Type II compliant.
- Engineering Benchmarks Standalone benchmarking product that lets engineering organizations compare their engineering performance metrics against industry and peer benchmarks.
- Jellyfish Assistant AI-powered natural-language assistant that lets engineering leaders ask questions of organizational engineering data and receive synthesized, actionable answers, with proactive surfacing of risks, trends, and guidance across delivery, planning, allocations, and AI Impact data.
- Data Hub Data platform layer that lets engineering, product, and finance teams explore, query, and reason about organizational engineering data (allocations, work, AI usage) via natural language and structured exploration, with custom dashboards and AI-assisted queries.
Quantifiable outcome
- Siigo: 30% increase in team performance and significantly more predictable delivery
- +11 more outcomes
Companies that use Jellyfish
Customer profileNamed customers40 records
Segments7 records
Ideal customer profiles3 records
Jellyfish technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration39 records
AI capability12 records
Feature8 records
Jellyfish partnerships and signals
Strategic signalPartnerships
17 partnerships are on record, tiered flagship and core.
- AugmentflagshipAugment and Jellyfish partnered to develop a system that measures the impact of AI tools on software development productivity and quality. The integration enables leaders to quantify AI's contribution through key metrics such as cycle time, code quality, and ROI.
- OpenAIflagshipJellyfish and OpenAI teamed up to measure the impact of AI coding tools; research collaboration featured in the Research Library and AI Impact Framework.
- HarvardcoreJoint Harvard & Jellyfish research on whether AI is making developers faster and where business impact shows up; published in the Research Library.
- Amazon (Amazon Q Developer)coreNative integration with Amazon Q Developer to evaluate adoption and impact across teams, repos, and initiatives. Co-marketed in 'Measuring Developer Productivity with Amazon Q Developer and Jellyfish' materials.
- GitHub CopilotflagshipFeatured integration that evaluates Copilot usage and impact to quantify AI productivity across teams; prominent in customer case studies.
- CursorflagshipFeatured integration that evaluates Cursor usage and team-level impact to measure AI-assisted development gains; cited in Hootsuite case study.
- Claude CodeflagshipFeatured integration to assess Claude Code adoption and outcomes to quantify AI-assisted productivity gains; central to the tokenmaxxing/token-spend research.
- CodexcoreIntegration to evaluate Codex adoption and impact to quantify AI-assisted developer productivity gains.
- KirocoreIntegration to evaluate Kiro adoption and usage to quantify the productivity impact of AI-assisted development.
- CodeRabbitcoreIntegration to evaluate AI-assisted code review speed and efficiency via the GitHub Copilot – Reviewer agent.
- DevincoreIntegration to assess the impact of Devin as an autonomous agent on engineering workflows.
- GreptilecoreIntegration to evaluate Greptile adoption and assess AI-assisted code review speed and efficiency.
- Gemini Code AssistcoreIntegration to measure Gemini Code Assist adoption and impact across developers and repos.
- Jira (Atlassian)flagshipFeatured integration that syncs epics, issues, and statuses to track delivery and investment allocation; foundation of the Resource Allocations product.
- GitHubflagshipFeatured integration that syncs repos, PRs, and issues to map work and measure cycle time; the primary data source for engineering metrics.
- LinearcoreFeatured integration that syncs issues and projects to visualize delivery progress and cycle times.
- Azure DevOpscoreFeatured integration that connects repos, pipelines, and boards for full delivery visibility.
Scale indicators19 records
Recent moves6 records
Expansion highlights7 records
Jellyfish competitors and assessment
Company assessmentDirect peers
- LinearB: LinearB is a direct competitor offering an engineering productivity platform with workflow automation, delivery forecasting, and developer metrics targeting engineering leaders — overlapping almost entirely with Jellyfish's Operational Effectiveness and Business Alignment modules.
- Swarmia: Swarmia is a direct peer in engineering effectiveness and developer experience measurement, with a strong focus on DORA/SPACE metrics, AI tool ROI, and team-level delivery insights — directly addressing the same buyer (VPs of Engineering, CTOs) and overlapping with Jellyfish's Developer Productivity and DevEx modules.
- Waydev: Waydev is a direct peer providing engineering analytics for software development leaders, with PR-cycle-time, sprint, and team performance dashboards — competing for the same engineering executive buyer on similar core metrics.
Emerging players
- Faros AI: Faros AI is an open-source engineering intelligence platform that aggregates SDLC data into a unified data model with AI-assisted queries — overlapping with Jellyfish's Data Hub and AI Assistant capabilities, and positioning as a more developer-led alternative.
- Code Climate: Code Climate provides engineering intelligence and code quality/maintainability analytics; it overlaps with Jellyfish on engineering metrics and velocity tracking while differentiating on code-quality dimensions (Velocity + Quality).
- Haystack: Haystack is an engineering productivity measurement tool focused on cycle time, pull request analytics, and developer experience — addressing a similar mid-market engineering leader with lighter-weight implementation than Jellyfish's enterprise stack.
Broad incumbents
- Planview: Planview (with Tasktop and LeanKit) is a broad incumbent in enterprise strategic portfolio and engineering work management, serving the same VP-Eng/CPO buyer as Jellyfish with overlapping resource allocation and flow metrics but as part of a much wider portfolio suite.
- Pluralsight Flow: Pluralsight Flow (formerly GitPrime) is an engineering analytics platform measuring developer productivity and team performance — a direct overlap with Jellyfish's metrics modules, now wrapped inside Pluralsight's broader developer-skills catalog.
- GitLab: GitLab is a broad DevOps platform whose Value Stream Analytics and GitLab Duo (AI) features overlap with Jellyfish's engineering metrics and AI Impact functionality as native capabilities bundled into a much larger DevOps suite.
- Atlassian: Atlassian's Jira Align and Atlassian Analytics extend into engineering resource planning and delivery analytics — competing for the same enterprise engineering/PMO buyer that Jellyfish targets, but as part of the broader Atlassian work-management ecosystem that Jellyfish sits on top of via Jira integration.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Jellyfish social profiles
Digital presenceJellyfish compliance and trust
Trust signalCompliance5 records
Jellyfish financial estimates
Financial estimateRevenue estimate
Valuation estimate
Jellyfish leadership team
Management profileNumber of profiles
Profiles9 records
Jellyfish funding detail
Funding detailFunding overview
Funding rounds4 records
Investors7 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Jellyfish M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Jellyfish
What does Jellyfish do?
Jellyfish is a Software Engineering Intelligence platform that ingests, cleans, normalizes, and links fragmented signals from issue tracking, SCM, CI/CD, HRIS, financial tools, and AI coding assistants into a single engineering data model. It sells this as a suite of modules — AI Impact, Operational Effectiveness, Business Alignment, DevEx, DevFinOps — that quantify engineering productivity, AI tool ROI, resource allocation, developer experience, and software capitalization for engineering, product, and finance leaders.
Is Jellyfish a public or private company?
Jellyfish is a private company. It is classified as venture growth investor backed and is currently operating.
When was Jellyfish founded?
Jellyfish was founded in 2017. It employs 101 to 250 people.
Where is Jellyfish based?
Jellyfish is headquartered in Boston, United States, in the North America region.
How does Jellyfish make money?
Three revenue lines are on record. Module-based SaaS subscriptions are the primary driver. The others are enterprise contracts (multi-year) and professional services / enablement.
Who are Jellyfish's main competitors?
Direct peers on record are LinearB, Swarmia and Waydev. Emerging players are Faros AI, Code Climate and Haystack. Broad incumbents are Planview, Pluralsight Flow, GitLab and Atlassian.
Does Jellyfish have an API?
Yes. Jellyfish offers an API that exposes engineering platform data, enabling developers to query and integrate metrics, allocations, and engineering intelligence data into external tools and AI assistants. The API was demonstrated in a blog post exploring engineering data alongside Amazon Q Business (Amazon's GenAI Assistant), enabling in-depth, natural-language-driven insights from Jellyfish data. Jellyfish also offers an MCP (Model Context Protocol) server, referenced in a customer story describing how Ably uses Jellyfish's MCP to connect the platform's data into AI workflows.